scholarly journals Robust Superstabilizing Controller Design from Open-Loop Experimental Input/Output Data**This work was supported in part by NSF grants IIS-1318145and ECCS-1404163; AFOSR grant FA9550-12-1-0271, and the Alert DHS Center of Excellence under Award Number 2008-ST-061-ED0001.

2015 ◽  
Vol 48 (28) ◽  
pp. 1337-1342 ◽  
Author(s):  
Y. Cheng ◽  
M. Sznaier ◽  
C. Lagoa
Keyword(s):  
Controller Design ◽  
Open Loop ◽  
Input Output ◽  
Output Data ◽  
Center Of Excellence

Model-Matching Controller Design With Input-Output Data—A Numerical Approach for Redundantly Actuated Systems

1994 ◽  
Vol 116 (4) ◽  
pp. 800-805
Author(s):  
Jenq-Tzong H. Chan
Keyword(s):  
Explicit Knowledge ◽  
Controller Design ◽  
Numerical Technique ◽  
Open Loop ◽  
Loop System ◽  
Synthesis Process ◽  
Model Matching ◽  
Input Output ◽  
Output Data ◽  
Redundantly Actuated

A numerical technique for control system synthesis based on input-output data is presented. The method is applicable when the system is open-loop stable and redundantly actuated. The major merits of the method are as follows. First, the closed-loop system equation may be arbitrarily assigned. Second, explicit knowledge of an open-loop system model is not needed for controller synthesis. Third, the stability of the synthesized system may be verified during the synthesis process; hence, the workability of the controller is ensured.

FUZZY PREDICTIVE CONTROL OF UNCERTAIN CHAOTIC SYSTEMS USING TIME SERIES

1999 ◽  
Vol 09 (04) ◽  
pp. 757-767 ◽  
Author(s):  
LIANG CHEN ◽  
GUANRONG CHEN
Keyword(s):  
Chaotic System ◽  
Controller Design ◽  
Recursive Least Squares ◽  
Input Output ◽  
Output Data ◽  
Lyapunov Stability Criterion ◽  
System Input ◽  
Prediction And Control ◽  
And Control ◽  
Fuzzy Predictive Control

In this paper, a simple fuzzy logic based intelligent mechanism is developed for predicting and controlling a chaotic system to a desired target, using only input–output data obtained from the unknown (or uncertain) underlying chaotic system. In the chaos prediction phase, a fuzzy system approach incorporating with Gaussian type of fuzzy membership functions is used. Only system input–output data are needed for prediction, and a recursive least-squares computational algorithm is employed for the calculation. In the controller design phase, the Lyapunov stability criterion is used, which forms the basis of the main design principle. Some simulation results on the chaotic Sin map and Hénon map are given, for both prediction and control, to illustrate the effectiveness and control performance of the proposed method.

Optimal Output Feedback Regulator—A Numerical Synthesis Approach for Input-Output Data

1996 ◽  
Vol 118 (2) ◽  
pp. 360-366 ◽  
Author(s):  
Jenq-Tzong H. Chan
Keyword(s):  
Output Feedback ◽  
Output Feedback Control ◽  
Numerical Approach ◽  
Open Loop ◽  
Input Output ◽  
Linear Quadratic ◽  
Output Data ◽  
Optimal Output ◽  
Synthesis Approach ◽  
Feedback Regulator

A numerical approach is proposed in this work for computing a linear quadratic optimal regulator from input-output data. The method is applicable whenever the plant is open-loop stable. The major advantages of the method are two-fold. First, it involves an output feedback control law; hence, no state estimation is required for implementation. Second, the computation of this optimal controller can be conducted without explicit identification of the plant model.

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