A FICTITIOUS REFERENCE ITERATIVE TUNING (FRIT) IN THE TWO-DEGREE OF FREEDOM CONTROL SCHEME AND ITS APPLICATION TO CLOSED LOOP SYSTEM IDENTIFICATION

2005 ◽  
Vol 38 (1) ◽  
pp. 626-631 ◽  
Author(s):  
Osamu Kaneko ◽  
Shotaro Soma ◽  
Takao Fujii
Keyword(s):  
System Identification ◽  
Closed Loop ◽  
Loop System ◽  
Degree Of Freedom ◽  
Closed Loop System ◽  
Control Scheme ◽  
Two Degree Of Freedom

Two Degree-of-Freedom Hysteresis Compensation for a Dynamic Mirror With Antagonistic Piezoelectric Stack Actuation

2013 ◽  
Author(s):  
James A. Mynderse ◽  
George T. C. Chiu
Keyword(s):  
Input Signal ◽  
Control Strategy ◽  
Closed Loop ◽  
Loop System ◽  
Degree Of Freedom ◽  
Closed Loop System ◽  
Loop Control ◽  
Hysteresis Compensation ◽  
Hysteresis Control ◽  
Two Degree Of Freedom

A methodology for designing a low-computation, high-bandwidth strategy for closed-loop control of a hysteretic system without a priori knowledge of the desired trajectory is presented. The resulting two degree-of-freedom hysteresis control strategy is applied to a dynamic mirror with antagonistic piezoelectric stack actuation. Hysteresis compensator is performed by a finite state machine switching polynomials for hysteresis inversion based on the input signal slope. Residual error after hysteresis compensation is corrected by an LQR feedback controller. Experimental results demonstrate effectiveness of the hysteresis compensator and closed-loop system under the proposed hysteresis control strategy. For the triangular input signal tested, the closed-loop system achieves a 91.5% reduction in hysteresis uncertainty with 60 kHz sample rate.

scholarly journals Adaptive Stabilization Control for a Class of Complex Nonlinear Systems Based on T-S Fuzzy Bilinear Model

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Jinsheng Xing ◽  
Naizheng Shi
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Complex Systems ◽  
Closed Loop ◽  
Loop System ◽  
Asymptotically Stable ◽  
Bilinear Model ◽  
Closed Loop System ◽  
Fuzzy Modelling ◽  
Control Scheme

This paper proposes a stable adaptive fuzzy control scheme for a class of nonlinear systems with multiple inputs. The multiple inputs T-S fuzzy bilinear model is established to represent the unknown complex systems. A parallel distributed compensation (PDC) method is utilized to design the fuzzy controller without considering the error due to fuzzy modelling and the sufficient conditions of the closed-loop system stability with respect to decay rateαare derived by linear matrix inequalities (LMIs). Then the errors caused by fuzzy modelling are considered and the method of adaptive control is used to reduce the effect of the modelling errors, and dynamic performance of the closed-loop system is improved. By Lyapunov stability criterion, the resulting closed-loop system is proved to be asymptotically stable. The main contribution is to deal with the differences between the T-S fuzzy bilinear model and the real system; a global asymptotically stable adaptive control scheme is presented for real complex systems. Finally, illustrative examples are provided to demonstrate the effectiveness of the results proposed in this paper.

CLOSID - A Matlab Toolbox for Closed-Loop System Identification

2000 ◽  
Vol 33 (15) ◽  
pp. 857-861
Author(s):  
Paul Van den Hof ◽  
Raymond de Callafon ◽  
Edwin van Donkelaar
Keyword(s):  
System Identification ◽  
Closed Loop ◽  
Loop System ◽  
Closed Loop System ◽  
Matlab Toolbox
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