Robustness and performance of an indirect adaptive control scheme in presence of bounded disturbances

1999 ◽  
Vol 44 (4) ◽  
pp. 789-793 ◽  
Author(s):  
G. Bartolini ◽  
A. Ferrara ◽  
A.A. Stotsky
Keyword(s):  
Adaptive Control ◽  
Control Scheme ◽  
Bounded Disturbances ◽  
Indirect Adaptive Control ◽  
And Performance ◽  
Adaptive Control Scheme

Stability analysis of adaptive control using fuzzy adapting rate neural emulator: Experimental validation on a thermal process

2021 ◽  
pp. 095965182098818
Author(s):  
Fatma Ezzahra Rhili ◽  
Asma Atig ◽  
Ridha Ben Abdennour ◽  
Fabrice Druaux ◽  
Dimitri Lefebvre
Keyword(s):  
Adaptive Control ◽  
Control Strategy ◽  
Thermal Process ◽  
Experimental Validation ◽  
Experimental Simulation ◽  
Neural Controller ◽  
Control Scheme ◽  
Stability Method ◽  
Indirect Adaptive Control ◽  
Adaptive Control Scheme

In this study, an adaptive control based on fuzzy adapting rate for neural emulator of nonlinear systems having unknown dynamics is proposed. The indirect adaptive control scheme is composed by the neural emulator and the neural controller which are connected by an autonomous algorithm inspired from the real-time recurrent learning. In order to ensure stability and faster convergence, a neural controller adapting rate is established in the sense of the continuous Lyapunov stability method. Numerical simulations are included to illustrate the effectiveness of the proposed method. The performance of the proposed control strategy is also demonstrated through an experimental simulation.

An Robust Adaptive Control Scheme for Hydraulic Servo Systems

2006 ◽  
Author(s):  
Torben Ole Andersen ◽  
Michael Ryygaard Hansen
Keyword(s):  
Adaptive Control ◽  
Tracking Error ◽  
Adaptive Controller ◽  
Robust Adaptive Control ◽  
Region Of Attraction ◽  
Control Scheme ◽  
Whole Space ◽  
Bounded Disturbances ◽  
Robust Adaptive ◽  
Adaptive Control Scheme

The paper looks into Model Reference Adaptive Control (MRAC) based on a linear plant model with constant or slowly varying parameters. The actual plant is non-linear, of a higher model order, subjected to time-varying bounded disturbances, and the measured values may be corrupted by noise. These problems are explored and the adaptive algorithms are modified to counteract instability mechanisms and for improved robustness with respect to bounded disturbances and non-modeled dynamics. The adaptive controller identifies the dominant dynamics and uses feedforward to provide anticipative actions in tracing task while an adaptive feedback part stabilizes the tracking error dynamics. Also the effects of non-modeled high frequency dynamics and bounded disturbances on stability and performance are analyzed. The adaptive control scheme is robust in the sense that it guarantees the existence of a large region of attraction from which all the trajectories remain bounded. The size of the region of attraction depends on the non-modeled dynamics in such a way that if the non-modeled dynamics is infinitely fast, the region of attraction becomes the whole space. Simulation and experimental results are presented and discussed to demonstrate the strength of the proposed algorithm.

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