Localization from inertial data and sporadic position measurements

International audience; A novel estimation strategy for inertial navigation in indoor/outdoor environments is proposed with a specific attention to the sporadic nature of the non-periodic measurements. After introducing the inertial navigation model, we introduce an observer providing an asymptotic estimate of the plant state. We use a hybrid dynamical systems representation for our results, in order to provide an effective, and elegant theoretical framework. The estimation error dynamics with the proposed observer shows a peculiar cascaded interconnection of three subsystems (allowing for intuitive gain tuning), with perturbations occurring either on the jump or on the flow dynamics (depen…

Use of accelerometers and gyros for hip and knee angle estimation

In this paper a wearable sensor system, consisting of accelerometers and gyros, has been studied to estimate hip and knee angles. The proposed algorithm, developed in order to avoid the error accumulation due to gyroscopes drift, has been tested on angle measurement of the hip and knee of a commercial device for assisted gait. The results have shown a good accuracy of the angles estimation, also in high angle rate movement

Least squares and genetic algorithms for parameter identification of induction motors

Abstract This paper deals with off-line parameter identification of induction motors by means of least square (LS) techniques and genetic algorithms (GA), using stator voltages, stator currents and velocity as input–output data. For analytical identification by LS algorithms, filtering of experimental data is performed by means of anticausal filters. Two models useful for identification are derived in which the products of acceleration and rotor fluxes, usually neglected, are taken into account. The GA-based identification method consists of the determination of the best parameters which match input–output behaviour of the motor. Both methods are investigated and compared by means of experi…

Parameter identification of linear induction motor model in extended range of operation by means of input-output data

This paper proposes a technique for the off-line estimation of the electrical parameters of the equivalent circuit of linear induction machines (LIM), taking into consideration the end effects, and focuses on the application of an algorithm based on the minimization of a suitable cost function involving the differences of measured and computed by simulation inductor current components. This method exploits an entire start-up transient of the LIM to estimate all the 4 electrical parameters of the machine (Rs, L s, σ Ls, Tr). It proposes also a set of tests to be made to estimate the variation of the magnetic parameters of the LIM versus the magnetizing current as well as the magnetizing curv…

System identification via optimised wavelet-based neural networks

Nonlinear system identification by means of wavelet-based neural networks (WBNNs) is presented. An iterative method is proposed, based on a way of combining genetic algorithms (GAs) and least-square techniques with the aim of avoiding redundancy in the representation of the function. GAs are used for optimal selection of the structure of the WBNN and the parameters of the transfer function of its neurones. Least-square techniques are used to update the weights of the net. The basic criterion of the method is the addition of a new neurone, at a generic step, to the already constructed WBNN so that no modification to the parameters of its neurones is required. Simulation experiments and compa…

Nonlinear Modeling of DC/DC Converters Using the Hammerstein's Approach

This paper deals with the modelling of highly nonlinear switching power-electronics converters using black-box identification methods. The duty cycle and the output voltage are chosen, respectively, as the input and the output of the model. A nonlinear Hammerstein-type mathematical model, consisting of a static nonlinearity and a linear time-invariant model, is considered in order to cope with the well-known limitations of the more common small-signal models, i.e. the entity of the variations of the variables around a well-defined steady-state operating point and the incorrect reproduction of the steady-state behavior corresponding to input step variations from the above steady-state operat…

Hybrid Observer for Indoor Localization with Random Time-of-Arrival Measurments

In this work an indoor position estimation algorithm will be proposed. The position will be measured by means of a sensor network composed by fixed beacons placed on the indoor environment and a mobile beacon mounted on the object to be tracked. The mobile beacon communicates with all the fixed beacons by means of ultra wide-band signals, and the distance between them is computed by means of time of flight techniques. Moreover, inertial measurements will be used when the position measurements are not available. Two main problems will be considered in the proposed architecture: the fact that the beacons work with a lower update rate than the IMU, and that the mobile beacon can comunicate wit…

Method for designing PI-type fuzzy controllers for induction motor drives

The paper illustrates a new systematic method for designing PI-type fuzzy controllers for direct field-oriented controlled induction motor drives. First, linear and decoupled models expressing the dynamics of speed, rotor flux, direct and inquadrature stator currents are derived using a nonlinear static compensator and choosing convenient input variables. Then, to guide the dynamics of the above quantities, four conventional PI controllers are designed independently, choosing their bandwidths conveniently. Finally, the input and output scale factors of PI-type fuzzy controllers are derived from the conventional PI controller parameters. The whole drive controller also includes a rotor flux …

Globally convergent adaptive and robust control of robotic manipulators for trajectory tracking

This paper deals with a globally convergent adaptive and robust control of robotic manipulators for trajectory tracking in the presence of friction modelled as static nonlinearities. Two control loops are designed according to the cascade control scheme: (a) an inner adaptive control loop, which includes computed torque and PD control actions and friction compensation and (b) an outer robust control loop for unmodelled dynamics compensation. With reference to item (a), two friction compensation schemes are presented; one of them uses both the reference and the actual velocities, whereas the other employs only the actual velocity. Experimental tests carried out on a two-link SCARA manipulato…

A new method for optimal synthesis of wavelet-based neural networks suitable for identification purposes

Abstract This paper deals with a new method for optimal synthesis of Wavelet-Based Neural Networks (WBNN) suitable for identification purposes. The method uses a genetic algorithm (GA) combined with a steepest descent technique and least square techniques for both optimal selection of the structure of the WBNN and its training. The method is applied for designing a predictor for a chaotic temporal series

Trajectory robust control of autonomous quadcopters based on model decoupling and disturbance estimation

In this article, a systematic procedure is given for determining a robust motion control law for autonomous quadcopters, starting from an input–output linearizable model. In particular, the suggested technique can be considered as a robust feedback linearization (FL), where the nonlinear state-feedback terms, which contain the aerodynamic forces and moments and other unknown disturbances, are estimated online by means of extended state observers. Therefore, the control system is made robust against unmodelled dynamics and endogenous as well as exogenous disturbances. The desired closed-loop dynamics is obtained by means of pole assignment. To have a feasible control action, that is, the fo…

Construction of a webgis tool based on a gis semiautomated processing for the localization of p2g plants in sicily (Italy)

The recent diffusion of RES (Renewable Energy Sources), considering the electric energy produced by photovoltaic and wind plants, brought to light the problem of the unpredictable nature of wind and solar energy. P2G (Power to Gas) implementation seems to be the right solution, transforming curtailed energy in hydrogen. The choice of the settlement of P2G plants is linked to many factors like the distances between the gas grid and the settlement of RES plants, the transportation networks, the energy production, and population distribution. In light of this, the implementation of a Multi-Criteria Analysis (MCA) into a Geographic Information System (GIS) processing represents a good strategy …

Tracking control of network distributed systems in presence of variable time delay and loss of information

This paper deals with the control of network distributed systems which has been at the centre of interest in a wide area of research in the last few year. The control of such systems is very difficult because the communication networks inevitably introduce variable time delays and possible lost of samples. In particular, it is proposed an extension of the approach, derived in the contest of the optimal stochastic regulator problem [1], [2], to the remote tracking problem considering a distributed control system in which the signals from the transducers to the controller and from the controller to the actuator are transmitted through a communication network with variable delays and possible …

Contact Estimation in Robot Interaction

In the paper, safety issues are examined in a scenario in which a robot manipulator and a human perform the same task in the same workspace. During the task execution, the human should be able to physically interact with the robot, and in this case an estimation algorithm for both interaction forces and a contact point is proposed in order to guarantee safety conditions. The method, starting from residual joint torque estimation, allows both direct and adaptive computation of the contact point and force, based on a principle of equivalence of the contact forces. At the same time, all the unintended contacts must be avoided, and a suitable post-collision strategy is considered to move the r…

An adaptive multi-rate system for visual tracking in augmented reality applications

The visual tracking of an object is a well-known problem, and it involves many fields of applications. Often a single sensor, the camera, could not provide enough information in order to track the whole object trajectory due to a low updating rate; therefore a multi-sensor system, based also on inertial measurements, could be necessary to improve the tracking accuracy. This leads to the fundamental question: how can information from different sensors be combined when they work at different rates? In this paper an approach based on recursive parameter estimation focusing on multi-rate situations is suggested. The problem is here formulated as the state-of-the-art problem of the visual tracki…

Robust control for high performance induction motor drives based on partial state-feedback linearization

This paper deals with a robust input-output feedback linearization control technique for induction motors. Indeed, classic feedback linearization presents two main disadvantages: 1) the accuracy of the dynamic model; and 2) the corresponding correct knowledge of the model parameters. To address this issue, the linear controller has been substituted with a suitably controller designed to be robust to the variations of the main parameters of the induction motor, like stator and rotor resistances, and the three-phase magnetizing inductance. The proposed controller has been tested both in numerical simulation and experimentally on a suitably designed test setup. Moreover, it has been compared w…

GA-based Off-Line Parameter Estimation of the Induction Motor Model Including Magnetic Saturation and Iron Losses

This paper, starting from recent papers in the scientific literature dealing with Rotating Induction Motor (RIM) dynamic modelling, as a first step, improves its space-vector dynamic model, including both the magnetic saturation and iron losses; The main original aspects of the proposed model are the following: 1) the magnetic saturation of the iron core has been described on the basis of both current versus flux and flux versus current functions, 3) it includes the iron losses, separating them in hysteresis and eddy current ones, 4) it includes the effect of the load on the magnetic saturation. Afterwards, it proposes an off-line technique for the estimation of electrical parameters of thi…

Task scheduling control of BGA solder joint process in flexible manufacturing system

This paper describes an open loop control method of the solder joint process in a rework station for faulty printed circuit board (PCBs) containing electronic components in packages ball grid arrays (BGAs). In particular, a mathematical model describing the solder joint process is, first of all, obtained. Then, the desired thermal profile of the junctions BGA-PCB is determined according to the physical constraints of the rework station framework. The control parameters corresponding to the above desired thermal profile are identified using the above mathematical model. Finally, the open loop control algorithm is implemented on the supervisor interface of the rework station in order to carri…

The Use of Accelerometers and Gyroscopes to Estimate Hip and Knee Angles on Gait Analysis

In this paper the performance of a sensor system, which has been developed to estimate hip and knee angles and the beginning of the gait phase, have been investigated. The sensor system consists of accelerometers and gyroscopes. A new algorithm was developed in order to avoid the error accumulation due to the gyroscopes drift and vibrations due to the ground contact at the beginning of the stance phase. The proposed algorithm have been tested and compared to some existing algorithms on over-ground walking trials with a commercial device for assisted gait. The results have shown the good accuracy of the angles estimation, also in high angle rate movement.

Robust control of a Hammerstein model of DC/DC converters

This paper deals with the robust control of a Hammerstein mathematical model of DC/DC converters, consisting of the nonlinear static characteristics of the converter followed by one of a few number of linear time- invariant models which describe the converter in the useful working range. One of these models is assumed as the nominal model of the system and the remaining models are used for describing the model uncertainty. Nominal behaviour is assured using H-2 optimal control method, Robust stability and behaviour are assured by imposing H-infin specifications. The closed loop control system consisting of the converter Hammerstein model and the robust controller is analyzed by means of sim…

A New Method of Velocity Estimation Based on Variable Temporal Basis Using Incremental Encoder

Abstract This paper deals with analysis and synthesis of algorithms for digital conditioning of signals generated by incremental encoders to estimate velocity of rotating devices for control purposes. Main objectives are to obtain high accuracy at low and high velocity and low tracking delays during accelerations. A digital conditioning method is described, Which uses a polynomial of order n whose coefficients are updated so as to fit the n+1 most recent velocity data acquired on a variable temporal basis. Digital sinlulations and experimental findings are shown with the ainl to validate the proposed estimation method and compare it with other methods.

Adaptive interaction robot control with estimation of contact force

Abstract This paper deals with a new adaptive force-position control of a robotic manipulator based on force estimation. First, an adaptive position controller is derived with contact force component as estimated parameters. Second, a supervisory external loop is added in order to regulate the contact force to the desired value. Extensive simulations with 2-DOF manipulator illustrate the followed approach.

Identification of Nonlinear Systems Described by Hammerstein Models

This paper deals with a method for identification of nonlinear systems suitable to be described by Hammerstein models consisting of a static nonlinearity followed by an ARX linear model. The estimation of the static nonlinearity is carried out supplying the system with a sequence of step signals of various amplitude and determining the corresponding steady-state responses. The estimation of the parameters of the ARX linear system is carried out by means of a least square estimator using data generated supplying the system with a Pseudorandom Binary Sequence (PRBS). The method in question is able to identify static nonlinearities of general type, also with hysteresis and/or discontinuities. …

Design and Low-Cost Implementation of an Optimally Robust Reduced-Order Rotor Flux Observer for Induction Motor Control

The aim of this paper is to design and analyze reduced-order observers of the rotor flux of induction motors. The design is carried out in two steps. In the first step, a boundary of the stability region of the observation error is obtained corresponding to a chosen Lyapunov function. In the second step, the boundary is translated into a performance index that is minimized with respect to stator and rotor resistance variations and differences of voltages supplying the motor and those supplying the observer in order to obtain the largest stability region. Implementation of the observer on a low-cost fixed-point digital signal processor using look-up tables is described. Experimental results …

A multi-sensor multi-rate algorithm for motor rehabilitation with Augmented Reality devices

Using Augmented Reality (AR) could offer stimuli to rehabilitation from neuro-motor disorders, since the patient can be aided in a better known reality than Virtual Reality (VR). The main goal for an AR system is to achieve a good quality of tracking the real object to align with virtual contents. Often a single sensor could not provide enough information to that end due to a low updating rate; therefore joining an other high updating rate sensor could be indispensable, but how to combine data from different sensors especially when they work all at different rates? In this paper an approach based on recursive parameter estimation, focusing on multi-rate tracking in AR devices is suggested. …

Interaction Control of Robotic Manipulators Without Force Measurement

This paper deals with a new adaptive force-position control of a robotic manipulator based on force estimation. Based on Lyapunov techniques will be proved that the control law guaranties tracking of the desired Cartesian trajectory along the contact plane and of a constant desired force along reciprocal direction, without force measuring. Extensive simulations with 2-DOF manipulator illustrates the followed approach.

A CONTROL LAW FOR ROBOTIC MANIPULATORS BASED ON A FILTERED SIGNAL TO GENERATE PD ACTION AND VELOCITY ESTIMATES

This paper deals with an adaptive control law for robotic manipulators based on a filtered signal to generate both the PD action and velocity estimates of the joints, suitable for trajectory tracking tasks, with the particular aim of reducing the harmonic content of the mechanical torques developed at the joints and thus avoiding excitation of unmodelled dynamics and instability. The practical aspects relative to the implementation of the control law are considered as relevant and, consequently, are detailed. In particular, several methods suitable to compute velocity estimates are discussed and compared with the method described in the paper. All of the above methods are illustrated by mea…

Descriptor-type Kalman Filter and TLS EXIN Speed Estimate for Sensorless Control of a Linear Induction Motor.

This paper proposes a speed observer for linear induction motors (LIMs), which is composed of two parts: 1) a linear Kalman filter (KF) for the online estimation of the inductor currents and induced part flux linkage components; and 2) a speed estimator based on the total least squares (TLS) EXIN neuron. The TLS estimator receives as inputs the state variables, estimated by the KF, and provides as output the LIM linear speed, which is fed back to the KF and the control system. The KF is based on the classic space-vector model of the rotating induction machine. The end effects of the LIMs have been considered an uncertainty treated by the KF. The TLS EXIN neuron has been used to compute, in …

Design and experimental validation of a high voltage ratio DC/DC converter for proton exchange membrane electrolyzer applications

Abstract This paper deals with hydrogen production via water electrolysis, which is considered the most attractive and promising solution. Specifically, the use of renewable energy sources, such as wind electric power generators, is hypothesized for supplying the electrolyzer, aiming to strongly reduce the environmental impact. In particular, micro-wind energy conversion systems (μWECSs) are attractive for their low cost and easy installation. In order to interface the μWECS and the electrolyzer, suitable power conditioning systems such as step-down DC-DC converters are mandatory. However, due to the requested high conversion ratio between the DC bus grid, i.e. the output of a three-phase d…

Design and Sensitivity Analysis of a Reduced-Order Rotor Flux Optimal Observer for Induction Motor Control

This paper aims to give simple and effective design criteria of rotor flux reduced-order observers for motion control systems with induction motors. While the observer is optimized for rotor and stator resistance variations, a sensitivity analysis is carried out in the presence of variations of all the motor parameters by means of either transfer function from true to observed rotor flux or simulation in a MATLAB-SIMULINK environment, assuming the voltages supplying the motor to be different from those supplying the observer. The sensitivity analysis makes it possible to establish design criteria for the observer in question. The behaviour of the proposed reduced order observer is compared …

Convergence Analysis of Extended Kalman Filter for Sensorless Control of Induction Motor

This paper deals with convergence analysis of the extended Kalman filters (EKFs) for sensorless motion control systems with induction motor (IM). An EKF is tuned according to a six-order discrete-time model of the IM, affected by system and measurement noises, obtained by applying a first-order Euler discretization to a six-order continuous-time model. Some properties of the discrete-time model have been explored. Among these properties, the observability property is relevant, which leads to conditions that can be directly linked with the working conditions of the machine. Starting from these properties, the convergence of the stochastic state estimation process, in mean square sense, has b…

Tuning of Extended Kalman Filters for Sensorless Motion Control with Induction Motor

This work deals with the tuning of an Extended Kalman Filter for sensorless control of induction motors for electrical traction in automotive. Assuming that the parameters of the induction motor-load model are known, Genetic Algorithms are used for obtaining the system noise covariance matrix, considering the measurement noise covariance matrix equal to the identity matrix. It is shown that only stator currents have to be acquired for reaching this objective, which is easy to accomplish using Hall-effect transducers. In fact, the Genetic Algorithm minimizes, with respect to the system covariance matrix, a suitable measure of the displacement between the stator currents experimentally acquir…

Adaptive Robot Control – An Experimental Comparison

This paper deals with experimental comparison between stable adaptive controllers of robotic manipulators based on Model Based Adaptive, Neural Network and Wavelet -Based control. The above control methods were compared with each other in terms of computational efficiency, need for accurate mathematical model of the manipulator and tracking performances. An original management algorithm of the Wavelet Network control scheme has been designed, with the aim of constructing the net automatically during the trajectory tracking, without the need to tune it to the trajectory itself. Experimental tests, carried out on a planar two link manipulator, show that the Wavelet-Based control scheme, with…

Adaptive feedback linearizing control of linear induction motor considering the end-effects

This paper proposes an input-output feedback linearization techniques for linear induction motors, taking into consideration the dynamic end-effects. As a main original content, this work proposes a new control law based on the on-line estimation of the induced-part time constant. The estimation law is obtained thanks to a Lyapunov based analysis and thus the stability of the entire control system, including the estimation algorithm, is intrinsically guaranteed. Moreover, with such an approach even the on-lihe variation of the induced-part time constant with the speed is retrieved, thus improving the behavior of previously developed approaches where such a variation vs. speed is considered …

Estimation of turbulence and state based on EKF for a tandem Canard UAV

This paper deals with the state and turbulence estimation of a model describing the longitudinal dynamics of an Unmanned Aerial Vehicle (UAV). Due to both the high nonlinearities of the model and the stochastic nature of disturbances, an Extended Kalman Filter (EKF) is proposed. To allow the estimator to be employed on low cost UAV systems, it is assumed that the aircraft is equipped with a low performance GPS, characterized by a relatively low refresh rate. The designed EKF is able to work efficiently in both turbulent and calm atmosphere. In order to obtain information about the performances of the proposed estimator for control purposes, a control system, consisting of the EKF, a PID-typ…

A GIS-based optimization model finalized to the localization of new power-to-gas plants: The case study of Sicily (Italy)

In 2020 the European Commission approved the GND (Green New Deal), a strategic plan aimed at the decarbonization of the EU by 2050. In this scenario, the diffusion of alternative renewable energy sources (RESs) play a key role, particularly electric energy production from wind and photovoltaic power plants. Regardless, the nonprogrammable nature of these power sources led recent studies to focus the interest on the power-to-gas solution (PtG), consisting of the electrolytic transformation of excesses of unused electric energy into hydrogen. The complexity of this technology requires the development of strategic optimization models aimed at finding the best locations for new PtG plants in sp…

Turbolence and State Estimation Via Extended Kalman Filter for a Non Conventional UAV

Adaptive Control of Underactuated Underwater Vehicles

This paper deals with a control strategy for underactuated underwater vehicles whose target is trajectory tracking. A cascade approach is employed which brings to a control law consisting of: a) an outer loop, obtained from the vehicle kinematic model, which forces this model to track the reference trajectory; b) an inner adaptive control loop which forces the system to track the reference signals given by the outer control loop. Conditions for asymptotic tracking of the trajectory and boundness of the unactuated velocities are given. Simulation tests illustrate the proposed approach.

Robustness Analysis of an Extended Kalman Filter for Sensorless Control of Induction Motors

This paper deals with robustness analysis of Extended Kalman Filters (EKFs) for sensorless motion control of induction motors. Analysis is carried out by means of simulation experiments considering a conventional EKF, in which system and measurement noise covariance matrices are constant, and an adaptive EKF in which the system noise covariance matrix is updated on-line using a PID-type algorithm driven by the stator current estimation errors.

IDENTIFICATION OF HAMMERSTEIN MODELS FOR DC/DC CONVERTERS OPERATING IN CCM

Identification of a Hammerstein model for DC/DC converters operating in CCM

This paper deals with a method for identification of a Hammerstein model of DC-DC converters operating in continuous conduction mode (CCM). This model has the duty cycle and the output voltage as input and output, respectively; it consists of a static nonlinearity and a linear and time-invariant model. The aim of the modeling the system by means of a Hammerstein model is due to its capability of describing the converter in a range of steady-state operating points instead of a desired well defined operating point as occurs for the small-signal models which are the more common mathematical description to approach the study of the converters themselves. The nonlinear characteristic of the Hamm…

Decentralized Kalman Filter Based Robot Control

Hammerstein Model-Based Robust Control of DC/DC Converters

This paper deals with model-based robust control of DC/DC power electronic converters. The converter is modelled by means of its static characteristic and a few continuous-time linear and time-invariant (LTI) models corresponding to contiguous ranges of duty-cycle. The model appears as a Hammerstein model in which the values of the parameters of the LTI part depend on the actual duty-cycle operating range. This suggests to describe the converter as an uncertain system to be controlled using robust control techniques. Frequency domain approach is used for describing the nominal model and the uncertainty. In view of applying robust control, identification of the LTI models is performed by mea…

Identification and robust control of DC/DC converter Hammerstein model

Abstract—This paper deals with model-based robust control of dc/dc power electronic converters. The converter is described by means of a Hammerstein model consisting of the nonlinear static characteristics of the converter and a linear time-invariant (LTI) uncertainmodel whose parameters depend on the actual duty-cycle operating range. This suggests that the controller be designed using robust control techniques. In view of applying robust control, identification of the earlier LTI models is performed by means of simulation experiments, carried out on a converter switching model implemented onMATLAB/SIMULINK environment. Internal model control (IMC) structure is employed for the controller …

Input-Output Feedback Linearization Control with On-Line Inductances Estimation of Synchronous Reluctance Motors

This paper proposes an adaptive input-output Feedback Linearization (FL) techniques for Synchronous Reluctance Motor (SynRM) drives, taking into consideration the iron losses. As a main original content, this work proposes a control law based on a new dynamic model of the SynRM including iron losses as well as the on-line estimation of the static inductances. The on-line estimation of the SynRM static inductances permits to inherently take into consideration the magnetic saturation phenomena occuring on both axes. The estimation law is obtained thanks to a Lyapunov-based analysis and thus the stability of the entire control system, including the estimation algorithm, is intrinsically guaran…

Descriptor-type Robust Kalman Filter and Neural Adaptive Speed Estimation Scheme for Sensorless Control of Induction Motor Drive Systems

Abstract This paper deals with robust estimation of speed and rotor flux for sensorless control of motion control systems which use induction motors as actuators. Due to the observability lack of five and six order Extended Kalman Filters, speed is here estimated by means of a Total Least Square algorithm with Neural Adaptive mechanism. This allows the use of a fourth-order Kalman Filter for estimating rotor flux and to filter stator currents. To cope with motor-load parameter variations, a descriptor-type robust Kalman Filter is designed taking explicitly into account these variations. The descriptor-type structure allows direct translation of parameter variations into variations of the co…

ROAD -Robotic Assisted Diving: physiology of diving

ROAD project: Robotics for assisted diving

The activities associated to underwater diving are of great importance in many areas. In the second half of the last century, diving technologies have greatly progressed, but diving is still characterized by significant risks, especially for professional divers who works at high depth, and limited practicability. The use of robotic systems and automatic procedures would allow, as in other situations where safety is of concern (for example, in case of hazardous works or in relation to hostile environments), a reliable monitoring and assessment of the physiological conditions of human operators during their activities. Moving from currently available technologies in underwater robotics, the R…

Hybrid nonlinear observer for Inertial Navigation

This paper considers the problem of designing an observer for navigation and localization of inertial systems. Since the measurement systems used in this field have a low update rate with respect to the control algorithm, the design of a suitable observer with sampled measurements is required. Here a hybrid non-linear observer is proposed, combining two different observers with different characteristics. A theoretical treatment is given in order to prove the convergence of the observer and it will be contextualized in the framework of the hybrid systems, providing an elegant setting for the proposed solution. Finally experimental results show the feasibility of the proposed observer and the…

A hybrid observer for localization of mobile vehicles with asynchronous measurements

The aim of this paper is the design of a hybrid nonlinear observer for mobile vehicles. The main problem is that position and velocity measurements are provided with a very low frequency, and the time between two consecutive measurements could be not constant, but it could vary randomly within a certain interval of time. For this reason the proposed observer has been contextualized in the hybrid systems framework. The convergence analysis of the estimation error has been carried out, and the sensitivity analysis has been performed in order to evaluate the bound of the estimation error when the measurements are biased and/or noisy. Simulation and experimental results, carried out on a mobile…

Active Disturbance Rejection Control of Synchronous Reluctance Motors

This paper describes how the ADRC (Active Disturbance Rejection Control) strategy can be successfully applied to SynRM (Synchronous Reluctance Motor) drives. The ADRC is an adaptive robust extension of the input-output Feedback Linearization Control (FLC). Its main feature is that the nonlinear transformation of the state is computed on-line and not by using the model. As a consequence, any unmodelled dynamics or uncertainty of the parameters can be addressed. The control strategy has been verified successfully with experimental tests confirming the high dynamic response of the drive.

Extended Kalman Filter for sensorless control of induction motors

This paper deals with speed and rotor flux estimation of induction motors via Extended Kalman Filter (EKF). The filter is designed starting from a discrete time model obtained by means of a first order discretization of the original nonlinear model of the induction motor (IM). In order to obtain accurate estimation of the above mentioned variables, the load torque is included into the state variables and then estimated, thus constructing a sixth order EKF. Experimental results are shown with reference to a closed loop sensorless control system, consisting of a 750 W induction motor supplied by a voltage source inverter, a cascade controller consisting of four PI control loops and the design…

Sensorless Control of Induction-Motor Drive Based on Robust Kalman Filter and Adaptive Speed Estimation

This paper deals with robust estimation of rotor flux and speed for sensorless control of motion control systems with an induction motor. Instead of using sixth-order extended Kalman filters (EKFs), rotor flux is estimated by means of a fourth-order descriptor-type robust KF, which explicitly takes into account motor parameter uncertainties, whereas the speed is estimated using a recursive least squares algorithm starting from the knowledge of the rotor flux itself. It is shown that the descriptor-type structure allows for a direct translation of parameter uncertainties into variations of the coefficients appearing in the model, and this improves the degree of robustness of the estimates. E…

Speed and rotor flux estimation of induction motors via on-line adjusted extended kalman filter

This paper deals with the estimation of speed and rotor flux of induction motors via Extended Kalman Filter (EKF) with on-line adjusting of the system noise covariance matrix. The predictor of EKF consists of a discrete time model obtained by means of a second order discretization of the original nonlinear model of the induction motor. In order to obtain accurate estimation of the above mentioned variables, the load torque is included in the state variables and then estimated. Three different system noise models are also illustrated and compared each other by simulations carried out in Matlab/Simulink environment. For one of these models, EKF is adjusted on-line by means of an additional PI…

Sensorless interaction robot control

An estimator algorithm for the rotation time of magnetization vector in nuclear magnetic resonance for imaging (NMRI)

The purpose of this paper is to propose a useful method to investigate the rotation time of the magnetization vector in the nuclear magnetic resonance for imaging (NMRI) system. The ninety degrees rotation of the magnetization vector is the first step in order to establish the free induction decay that radiates electromagnetic energy inside the NMRI chamber. The estimator involved in this research is called Luenberger's observer which is a state estimator of a dynamical system. The Bloch's equation is a dynamical system characterized by a radio frequency (RF) impulse located inside the dynamic matrix, which means the system is not linear. The observer algorithm involved in this paper estim…

State Estimation of a Mobile Manipulator via Non-uniformly Sampled Position Measurements

Abstract We derive an exact deterministic nonlinear estimator to compute the continuous state of a nonlinear time-varying system based on discrete, non uniformly time spaced, state measurements. The system consists of a robot arm mounted on a mobile non holonomic vehicle. The paper also discusses the effect on the estimation error of a bounded input additive noise.

A navigation and control algorithm for the position tracking of underwater vehicles

In this paper we consider position control of underwater vehicles through inversion of differential kinematics based on uncalibrated, relative to the water, velocity sensors and unknown marine current. An estimation algorithm, based on the above measurements, estimates calibration parameters and marine current, assuring convergence of the estimated velocities to the true quantities. A kinematic control algorithm assures convergence to zero of the position tracking error. An extension of the basic estimation algorithm has been considered, in which position measurements are considered sampled at low rate and randomly spaced in time. Computer simulations are given of the proposed position trac…

Robust Active Disturbance Rejection Control of Induction Motor Systems Based on Additional Sliding-Mode Component

This paper deals with motion control systems with induction motor, subject to severe requirements on both dynamics and steady-state behavior. The proposed control methodology could be viewed as an advancement of the standard field oriented control. It consists of two control loops, i.e., the rotor flux and the speed control loops, designed using the active disturbance rejection control method, with the aim to cope with both exogenous and endogenous disturbances, which are estimated by means of two linear extended state observers and then compensated. Moreover, with the aim of achieving total robustness, a sliding-mode based component is designed, in order to take into account disturbance es…

An adaptive control law for robotic manipulator without velocity feedback

In this paper, a new adaptive control law is designed for robotic manipulators, based on the use of reference velocities instead of the actual ones and feedback signals generated from position errors. The law in question is suitable for trajectory tracking and positioning tasks. Its peculiarities are implementation without velocity measurements and estimation, high signal-to-noise ratio in control torques and absence of parameter drift in positioning tasks. Experimental tests are shown with the aim to confirm the validity of the control law and to illustrate its actual effects on the behaviour of the system.

Localization Based on Parallel Robots Kinematics as an Alternative to Trilateration

In this article, a new scheme for range-based localization is proposed. The main goal is to estimate the position of a mobile point based on distance measurements from fixed devices, called anchors, and on inertial measurements. Due to the nonlinear nature of the problem, an analytic relation to compute the position starting from these measurements does not exist, and often trilateration methods are used, generally based on least-square algorithms. The proposed scheme is based on the modeling of the localization process as a parallel robot, thereby methodologies and control algorithms used in the robotic area can be exploited. In particular, a closed-loop control system is designed for trac…

Trajectory tracking of underactuated underwater vehicles

This paper deals with a control strategies for underactuated underwater vehicles whose target is the tracking of a space trajectory. A cascade control strategy is employed which brings to a control law consisting of: 1) a kinematic control law, derived from the vehicle kinematic model, which forces this model to track the reference trajectory; and 2) a dynamic control law which forces the system to track the reference signals given by the kinematic control law. Conditions for asymptotic tracking of the trajectory are given with reference to the standard dynamical model of the above vehicle. An observer of the marine current is also added in order to process the control law. Simulation tests…

Parameter identification of induction motor model using genetic algorithms

The paper deals with methods of identification of the parameters of an induction motor model using genetic algorithms. It is supposed that the inverter supplying the motor is directly accessible for control of the conduction sequences of its power switches. This makes it possible to carry out a test consisting of a transient from standstill to steady-state operation at a given frequency and successive free motion to standstill. During this test, data are acquired referring to stator voltages, and currents and speed. Then, a genetic algorithm is employed with the aim of determining the mechanical and electrical parameters of the model, so as to reproduce the input-output behaviour of a real …

Sliding Mode Control of Quadratic Boost Converters Based on Min-Type Control Strategy

The paper deals with the control of a quadratic boost converter supplied by low-voltage energy sources, such as photovoltaic panels, fuel cells, or batteries. The control scheme consists of two control loops. A min-type controller governs the inner loop to force the current state of the nominal model to converge in a neighborhood of the equilibrium state. The external loop processes the output tracking error using an integrator, and it allows reconfiguring the converter's working point by changing the equilibrium state given in the input to the internal loop. This configuration assures both zero tracking error of the output voltage and robustness against load and input voltage variations an…

Design of a robust controller for DC/DC converter–electrolyzer systems supplied by μWECSs subject to highly fluctuating wind speed

Abstract A buck-based, isolated, high-voltage-ratio DC/DC converter that allows supplying a proton exchange membrane (PEM) electrolyzer from a micro-wind energy conversion system ( μ WECS) has been recently presented. It exhibits low ripple at the switching frequency on the output voltage and current and represents an attractive solution for low-cost hydrogen production. In this paper, a more accurate mathematical model of such a converter is derived and discussed. Then, a model-based robust controller is designed in the frequency domain using the Internal Model Control structure and in the context of H 2 ∕ H ∞ optimal control. The controller satisfies the condition of robust stability and …

ROTOR FLUX OPTIMAL ESTIMATION FOR INDUCTION MOTOR CONTROL

Abstract The aim of this paper is to analyze and design reduced order observers of the rotor flux of induction motors. The design requirements are: a) the convergence rate of the rotor flux estimation error; b) a low sensitivity to stator and rotor resistance variations; c) a low sensitivity to errors due to the implementation of the observers on microprocessor-based systems. It is shown that, in order to satisfy the requirements a)-c), it is sufficient to solve a constrained optimization problem according to a criterion in which these requirements appear explicitly. The implementation of the observer is discussed. The observer is tested by simulation and experiments.

A Model-Based Control Strategy for Wind Turbines with Asynchronous Generator

In this paper a model based control methodology is described with reference to a wind turbine for production of alternative energy. The mathematical model of a 600 kW wind turbine is taken into account assuming a well defined profile of the rotor blades. A set of reference angular speeds of the asynchronous generator and a set of reference pitch angles of the blade wind turbine are obtained in order to maximize the extracted wind power and to reach equilibrium conditions between the wind-generated torque and the electric torque of the generator. Finally a PID model based controller is designed and then tested by means of simulation experiments.

TAKEOFF AND LANDING ROBUST CONTROL SYSTEM FOR A TANDEM CANARD UAV

In spite of modern wide improvements in UAV’s technologies, a few number of such a vehicles is fully autonomous from takeoff to landing . So, either autonomous operation or operation with minimal human intervention is, actually, the primary design goal for the UAV’s researchers. The core of the problem is the design of the landing and takeoff control system. The objective of this paper is to design a control system in which the same state variables are controlled during both the descending/ascending path and the flare, tacking into account the actual ground effect. Robust control techniques are employed with the aim to cope with atmospheric turbulence, measurement noise, parameter variation…

State Estimation of a Nonlinear Unmanned Aerial Vehicle Model using an Extended Kalman Filter