Search results for "Adaptive Control"
showing 10 items of 80 documents
Aircraft wing rock oscillations suppression by simple adaptive control
2020
Abstract Roll angular motion of the modern aircraft operating in non-linear flight modes with a high angle of attack often demonstrates the limit cycle oscillations, which is commonly known as the wing rock phenomenon. Wing rock dynamics are represented by a substantially non-linear model, with parameters varying over a wide range, depending on the flight conditions (altitude, Mach number, payload mass, etc.) and angle of attack. A perspective approach of the wing rock suppression lies in the adaptation methods. In the present paper an application of the simple adaptive control approach with the Implicit Reference Model (IRM) is proposed and numerically studied. The IRM adaptive controller …
A CNN Adaptive Model to Estimate PM10 Monitoring
2006
In this work we introduce a model for studying the distribution and control of atmospheric pollution from PM10. The model is based on the use of a cellular neural network (CNN) and more precisely on the integration of the mass-balance equation; at the same time it simulates the scenario regarding a planar grid describing the whole studied area (the city of Palermo) by means of a CNN and a set of Bayesian networks. The CNN allows us to define a grid system whose dynamic evolution is a redefinition of the diffusion equation that considers contributions coming from near cells for each element of the grid. Dynamics of each cell is influenced by meteorological effects and by parameters related t…
Schedulability analysis of window-constrained execution time tasks for real-time control
2003
Feasibility tests for hard real-time systems provide information about the schedulability of a set of tasks. However, this information is a yes or no answer whether the task set achieves the test or not. From the system design point of view, it would be useful to have more information, for example, how much can one vary some task parameters, such as computation time, without jeopardizing the system feasibility. The aim of the work is to provide a method to determine how much a task can increase its computation time, maintaining the system feasibility under a dynamic priority scheduling. This extra time can be determined not only in all the task activations, but in n of a window of m task in…
Towards Robust Adaptive Least-Squares Parameter Estimation with Internal Feedback
1998
Abstract The new concepts of the ‘covariance matrix normalization’ and the ‘cascade’ structure of the adaptive least-squares estimator are shown to generalize and extend the use of internal information feedback in various robustness/alertness-oriented modifications to the standard ALS estimation algorithm. In the cascade estimation structure it is possible to ‘naturally’ stabilize, rather than maximize, the information matrix so that the covariance windup and blowup are effectively eliminated and the celebrated square root update of the covariance matrix is no longer needed Consequently, a new, ‘single-loop/cascade’ ALS MIMO estimation algorithm, enabling to effectively track both slow and …
Distributed Adaptive Control for Asymptotically Consensus Tracking of Uncertain Nonlinear Systems With Intermittent Actuator Faults and Directed Comm…
2019
In this article, we investigate the output consensus tracking problem for a class of high-order nonlinear systems with unknown parameters, uncertain external disturbances, and intermittent actuator faults. Under the directed topology conditions, a novel distributed adaptive controller is proposed. The common time-varying trajectory is allowed to be totally unknown by part of subsystems. Therefore, the assumption on the linearly parameterized trajectory signal in most literature is no longer needed. To achieve the relaxation, extra distributed parameter estimators are introduced in all subsystems. Besides, to handle the actuator faults occurring at possibly infinite times, a new adaptive com…
Event-triggered robust adaptive control for discrete time uncertain systems with unmodelled dynamics and disturbances
2019
In practice, modelling errors caused by high-order unmodelled dynamics and external disturbances are unavoidable. How to ensure the robustness of an adaptive controller with respect to such modelling errors is always a critical concern. In this study, the authors consider the design of event-triggered robust adaptive control for a class of discrete-time uncertain systems which involve such modelling errors and also are allowed to be non-minimum phase. Unlike some existing event-triggered control schemes, the developed controllers do not require that the measurement errors meet the corresponding input-to-state stable condition. Global stability of the closed-loop system which means that all …
Linear parameter estimation and predictive constrained control of wiener/hammerstein systems
2003
Abstract A new, analytical, orthonormal basis functions (OBF)-based design methodology for adaptive predictive constrained control of open-loop stable, possibly nonminimum phase, time-varying Wiener and Hammerstein systems is presented. A linear adaptive least-squares parameter estimation algorithm is applied both to a nonlinear static part and a linear dynamic, OBF-modeled factor of the Wiener/Hammerstein system. A notion of inverse systems is crucial for linear estimation of both Wiener and Hammerstein systems, with in verses of the nonlinear or linear parts respectively involved. The adaptive estimator is coupled with a simple but robust, predictive control strategy called Extended Horiz…
Intelligent Adaptive Motion Control for Ground Wheeled Vehicles
2014
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…
Globally convergent adaptive and robust control of robotic manipulators for trajectory tracking
2004
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…
Control of uncertain highly nonlinear biological process based on Takagi–Sugeno fuzzy models
2015
This note deals with the control of uncertain highly nonlinear biological processes. Indeed, an adaptive fuzzy control (AFC) scheme is developed for the pre-treatment of wastewater represented by a Takagi-Sugeno (TS) fuzzy model. The proposed approach uses a fuzzy system to approximate the unknown substrate consumption rate in designing the adaptive controller, and then an observer is designed to estimate the concentration in substrate at the outlet bioreactor. The observer is employed to generate an error signal for the adaptive control law which permits to minimize the influence of the measurement noise on the estimation of the substrate concentration. An update of the fuzzy models parame…