"Stochastic PCA Algorithm for Industrial Planar Manipulator Control

Intelligent Adaptive Motion Control for Ground Wheeled Vehicles

In this paper a new intelligent adaptive control is applied to solve a problem of motion control of ground vehicles with two independent wheels actuated by a differential drive. The major objective of this work is to obtain a motion control system by using a new fuzzy inference mechanism where the Lyapunov’s stability can be assured. In particular the parameters of the kinematical control law are obtained using an intelligent Fuzzy mechanism, where the properties of the Fuzzy maps have been established to have the stability above. Due to the nonlinear map of the intelligent fuzzy inference mechanism (i.e. fuzzy rules and value of the rule), the parameters above are not constant, but, time a…

Fuzzy/Kalman Hierarchical Horizontal Motion Control of Underactuated ROVs.

A new closed loop fuzzy motion control system including on-line Kalman's filter (KF) for the two dimensional motion of underactuated and underwater Remotely Operated Vehicle (ROV) is presented. Since the sway force is unactuated, new continuous and discrete time models are developed using a polar transformation. A new hierarchical control architecture is developed, where the high level fuzzy guidance controller generates the surge speed and the yaw rate needed to achieve the objective of planar motion, while the low level controller gives the thruster surge force and the yaw torque control signals. The Fuzzy controller ensures robustness with respect to uncertainties due to the marine envi…

A Neuro Fuzzy Controller for Planar Robot Manipulators

Hierarchical fuzzy/Lyapunov control for horizontal plane trajectory tracking of underactuated AUV

A new hierarchical closed loop fuzzy control system for horizontal plane trajectory tracking of underactuated Autonomous Underwater Vehicles (AUV) is presented. A model for the AUV is formulated introducing a polar coordinates transformation for the velocities in the body fixed frame. It is employed to control the unactuated sway direction, the longitudinal position and the yaw by using the surge force and the yaw torque only. The highest level control is developed by employing a fuzzy inference system for obtaining the guidance control laws. The properties of the fuzzy system ensure forward surge velocity, fast convergence and Lyapunov's stability of the motion errors. A new low level kine…

Real-Time Remote Control of a Robot Manipulator using Java and Client-Server Architecture

“A Neuro Fuzzy Controller for Planar Manipulators”

A New Dynamic Robust Fuzzy Controller for Vehicles with Nonholonomic Constraints

On-line adaptive neural network in very remote control system

Remote control involves several issues that degrade seriously the performance of the plant to be controlled. This paper presents a strategy improving the characteristics of the remote control system, using an on-line adaptive neural net, in order to learn the variations of the remote system parameters to minimize the errors. This strategy is successfully applied to a client-server remote control system for a two link robot arm. Tests show that an error position in a remote control brushless motor can be highly reduced since its first "reference command" using a prevision of that error to modify the original reference. The neural net, used only by the client, is previously trained using loca…

A New Kinematic and Dynamic Direct Adaptive Fuzzy Control of Constrained Mobile Wheeled Vehicles

In this paper a new kinematic and dynamic adaptive Fuzzy control is applied to a trajectory tracking problem of a constrained vehicle with two indipendent wheels. The vehicle dynamics and kinematics are completely unknown. A dynamical and kinematical adaptive control provide to on line estimation of the dynamic and kinematic parameters of the vehicle model. Moreover the parameters of the kinematic control law are obtained using a Fuzzy controller and they are time varying and dependent on tracking errors. The stabililty of the kinematic and dynamic adaptive Fuzzy control system and the convergence of tracking errors to zero are proved using Lyapunov's method and Barbalat's Lemma. The effect…

A New Fuzzy Lyapunov Controller for Nonholonomic Mobile Vehicles

Model Identification using a Statistical Cluster LPC approach with Application to Motion of a Brushless Motor

This paper presents a new statistical method based on Cluster Last Principal Component (CLPC) algorithm to identify nonlinear, time-varying, dynamical models from input-output data clusters of black boxes. Each of data clusters is on a time window. For every data cluster an appraiser updates the parameters of a Gaussian time-varying model via an optimality design criterion that maximises the Likelihood function and the estimated steady-state parameters of this model are quasi-constant values. An application to identify the nonlinear model of a control system of a brushless motor is developed. By applying of CLPC algorithm to this system, the actual angular positions of the brushless motor a…

Trajectory Decentralized Fuzzy Control of Multiple UAVs.

This paper considers a complete position and heading rate control system for multiple unmanned aerial vehicles (UAVs) with constant altitude. A decentralized trajectory planning algorithm is proposed, where the UAVs will avoid collisions while moving. In order to stabilize the UAVs in the reference planned trajectories and ensure the boundedness of the control velocities, a fuzzy control law is proposed with Lyapunov's stability proof. Simulation experiments developed in Matlab environment confirm the effectiveness and the robustness of the proposed control algorithm with respect to possible turbulence disturbances perturbing the nominal motion of the UAVs.

On-line Adaptive Neural Netwrok in Very Remote Control System

Predictive Intelligent Fuzzy Control for Cooperative Motion of Two Nonholonomic Wheeled Cars

In this paper a problem of intelligent cooperative motion control of two wheeled nonholonomic cars (target and follower) is considered. Once a target car converges to a fixed state (position and orientation), a follower car coming from different position and orientation, converges to the state above, without excessive delay between the known arrival time of the target car and the arrival time of the follower. In this sense we present a new predictive fuzzy control system. A Kalman's filter and an odometric model are used to predict the future position and orientation of the target car. The prediction above is employed to plane a circular nonholonomic reference motion for the follower car. A…

Stochastical Real Time Finite State Machine LPC for Planar Manipulator Control System Model estimation

This paper presents a new stochastical real-time LPC (Last Principal Component) algorithm to estimate single-input-single-output (SISO) and multiple-input-multiple-output (MIMO) varying time models from input output data clusters of non stationary black boxes. Each of data clusters is on a time window. An application to estimate the control system model of a planar manipulator is developed. In fact many mathematical models of physical systems are non stationary such as industrial manipulator model. A real time estimation algorithm via stochastical LPC algorithm and an appraiser called "finite state machine" is then described For every data cluster the finite state machine updates the parame…

Controllo Remoto con Architettura Client Server

Exponentially Stable Trajectory Tracking Control for Wheeled Nonholonomic Robots

A new fuzzy robust dynamic controller for autonomous vehicles with nonholonomic constraints

Abstract In this paper a novel algorithm with a dynamic fuzzy controller applied to the control of trajectory of vehicles with two independent wheels is proposed. An automatic control of trajectory of a vehicle can behave in a not efficient way. It is necessary to consider the friction of the actuators and possible perturbations coming from the outside environment, as for instance the variable characteristics of the ground where the vehicle moves. These perturbations, which depend also on the contact between the wheel and the ground, involve violations of nonholonomic constraints. Thus it is necessary to compensate for these perturbations to obtain a robust control system. The controller sy…

A NEURO FUZZY CONTROLLER FOR PLANAR ROBOT MANIPULATOR

Fuzzy motion control strategy for cooperation of multiple automated vehicles with passengers comfort

This paper considers motion control for a cooperative system of automated passenger vehicles. It develops a cooperative scheme based on a decentralized planning algorithm which considers the vehicles in an initial open chain configuration. In this scheme the trajectories are intersections-free, and each trajectory is planned independently of the others. To ensure the stabilization of each vehicle in the planned trajectory, a fuzzy closed loop motion control is presented, where, based on the properties of the Fuzzy maps, the Lyapunov’s stability of the motion errors is demonstrated for all the vehicles. Based on the ISO 2631-1 standard, the saturation property of the Fuzzy maps guarantees lo…

Remote control systems of industrial manipulators by short-message

Fuzzy Control Strategy for Cooperative Non-holonomic Motion of Cybercars with Passengers Vibration Analysis

The cybercars are electric road wheeled non-holonomic vehicles with fully automated driving capabilities. They contribute to sustainable mobility and are employed as passenger vehicles. Non-holonomic mechanics describes the motion of the cybercar constrained by non-integrable constraints, i.e. constraints on the system velocities that do not arise from constraints on the configuration alone. First of all there are thus with dynamic nonholonomic constraints, i.e. constraints preserved by the basic Euler-Lagrange equations (Bloch, 2000; Melluso, 2007; Raimondi & Melluso, 2006-a). Of course, these constraints are not externally imposed on the system but rather are consequences of the equations…

Manipulator Control System Model Estimation Unsing a Real Time Finite State Machine based on Statistical LPC Analysis

This paper presents a new statistical method based on a real-time Last Principal Component (LPC) algorithm to estimate single-input-single-output (SISO) and multiple-input-multiple-output (MIMO) varying time dynamical models from input output data clusters of non stationary black boxes. Each of data clusters is on a time window. A real time estimation algorithm via statistical LPC algorithm and an appraiser called "finite state machine" is then described. For every data cluster the finite state machine updates the parameters of a Gaussian varying time model via an optimality design criterion that maximises the Likelihood function. Using the LPC algorithm and the finite state machine, the es…

Closed Loop Fuzzy/Lyapunov Control System for Planar Motion of Multiple Autonomous ROVs

Stochastic Estimate PCA Algorithm for Industrial Planar Manipulator Control

Adaptive Control and Data Fusion using EKF for Wheeled Robots with Parametric Uncertainties

Hibrid Adaptive/EKF Motion Control and Data Fusion for Ground Vehicles with Kinematical and Dynamical Uncertainties

This paper considers the motion control problem of ground vehicles with nonholonomic constraints and parametric uncertainties both in the kinematic and in the dynamic model. The presence of uncertainties above is treated using adaptation laws where the Lyapunov's stability of the position and orientation errors is proved. Now, if the feedback signals are position and orientation provided by incremental encoders only, then noises of the odometric sensors above can damage the control in terms of difference between the desired and the actual motion of the vehicle and in terms of performances of the parametric adaptation. So an extended Kalman's filter (EKF) is inserted in the feedback for meas…

ROBUST TRAJECTORY TRACKING CONTROL AND LOCALIZATION BASED ON EXTENDED KALMAN FILTER FOR NONHOLONOMIC ROBOTS

Real Time Control of Robot Manipulators using Java and Client Server Architecture

Noised Trajectory tracking Control based on Fuzzy Lyapunov approach for Wheeled Vehicles

This paper solves a trajectory tracking control problem whit outside perturbations for wheeled nonholonomic vehicles using a Fuzzy Lyapunov method. Trough a symbiosis between classical backstepping techniques and fuzzy logic, the control system ensures a good robustness with respect to outside perturbations. Possible causes of perturbations are the characteristics of the ground and the contact between the wheels and the ground. These perturbations can interact with the vehicle, they are sources of uncertainty for the system model and can perturb the validity of the nonholonomic constraints. The convergence of the tracking errors to the origin and the asymptotic stability of the equilibrium …

Fuzzy EKF Control for Wheeled Nonholonomic Vehicles

In this paper a new Fuzzy extended Kalman robust control system for position and orientation tracking of nonholonomic vehicles with two wheels actuated by two independent DC motors is presented. The problem of robustness and localization are solved simultaneously. About the robustness, some perturbations coming from the outside environment and depending on the contact between the wheels and the ground, involve violations of the nonholonomic constraints. The fuzzy controller of this work is able to obtain a dynamic term of robustness with respect to the perturbations above. However, by using encoders only, the measures of actual position and orientation of the vehicle are with Gaussian noise…

A Neuro Fuzzy Controller for a Planar Robot Manipulator

Stability and Noises Evaluation of Fuzzy Kalman UAV Navigation System.

In this paper a new Fuzzy/Kalman navigation system for Unmanned Aerial Vehicles (UAV) is presented. A closed loop velocity Fuzzy navigation system is proposed for stabilizing the UAV in a reference trajectory generated dynamically and for obtaining a forward velocity command. The Kalman's filter (KF) is included in the feedback line of the fuzzy control system to filter the internal noise of the sensors and to evaluate the external noise due to possible perturbations of the nominal motion. The efficiency of the navigation system has been shown through experimental tests in a Matlab environment.

Fuzzy cooperative control of automated ground passenger vehicles

In this paper a fuzzy motion control for cooperative passenger automated vehicles where there are not collisions between the closest ones is proposed. Based on the position of the target and on the initial position of each cooperative vehicle, a supervisory plans nonholonomic circular trajectories which are without intersections, while a fuzzy control strategy assures the asymptotical stability of the motion errors and the reaching of the target with low acceleration values along the planned trajectories. Based on the ISO 2631-1 standard, the saturation properties of the fuzzy maps guarantees low values of the longitudinal and lateral accelerations to assure the comfort of the passengers. T…