Design of Dual-Range Linear Controllers for Nonlinear Systems

1991 ◽  
Vol 113 (4) ◽  
pp. 590-596 ◽  
Author(s):  
A. Nassirharand
Keyword(s):  
Closed Loop ◽  
Loop Model ◽  
Model Matching ◽  
Matching Problem ◽  
Single Input Single Output ◽  
Stabilizing Controllers ◽  
Closed Loop Systems ◽  
Single Output ◽  
Highly Nonlinear ◽  
Linear Controllers

A new procedure for synthesis of dual-range linear controllers for use with highly nonlinear, deterministic, time-invariant, and single-input single-output systems in a unity feedback configuration is developed. The procedure uses a factorization approach coupled with optimization which is used to parameterize and search the class of all stabilizing controllers for linear systems with integrity. The objective of the synthesis approach is to arrive at robust closed-loop systems that are solutions to the closed-loop model matching problem. The procedure is presented in an algorithmic form, and it is demonstrated via example problems. The results are compared with those previously obtained using a frequency domain approach.

Measurement Errors in Closed-Loop Frequency Response Estimates

1980 ◽  
Vol 102 (1) ◽  
pp. 13-20
Author(s):  
P. W. Davall ◽  
P. N. Nikiforuk
Keyword(s):  
Frequency Response ◽  
Measurement Errors ◽  
Closed Loop ◽  
Power Spectra ◽  
Open Loop ◽  
Feedback Signal ◽  
Single Input Single Output ◽  
Closed Loop Systems ◽  
Single Output ◽  
Single Input

The sampling distributions associated with frequency response estimates of single input, single output closed-loop systems are derived for the case where both the output and feedback signal measurements are subject to added noise. This work is an extension of that done by Goodman [1-3] and Akaike [4, 5] on open-loop systems. Conditions for response estimate bias are investigated and approximate distributions for the power spectra estimates of the added noise terms are derived.

Realization of Prefilter for Virtual Reference Feedback Tuning Using Closed-Loop Step Response Data

2016 ◽  
Vol 28 (5) ◽  
pp. 707-714 ◽  
Author(s):  
Yoshihiro Matsui ◽  
◽  
Hideki Ayano ◽  
Shiro Masuda ◽  
Kazushi Nakano ◽  
...  
Keyword(s):  
Closed Loop ◽  
Least Squares Method ◽  
Reference Model ◽  
Step Response ◽  
Model Matching ◽  
Matching Problem ◽  
Virtual Reference ◽  
Response Data ◽  
Closed Loop Systems ◽  
The Time Domain

[abstFig src='/00280005/13.jpg' width='300' text='VRFT model matching problem with prefilter F(z)' ] Prefilters for Virtual Reference Feedback Tuning (VRFT) in the time domain are realized by the least-squares method with step reference response data acquired from the closed-loop system to be tuned and are used to obtain controller parameters for making closed-loop systems as close as possible to the desired reference model. The usefulness of this proposal is shown in numerical examples in which fifth-order and PID controllers for a flexible transmission system are tuned by VRFT with prefilters.

scholarly journals The discrete-time tracking problem with H∞ model matching approach plus integral control

2019 ◽  
Vol 292 ◽  
pp. 01018
Author(s):  
Murat Akın ◽  
Tankut Acarman
Keyword(s):  
Discrete Time ◽  
Closed Loop ◽  
Controller Design ◽  
Model Matching ◽  
Matching Problem ◽  
Design Algorithm ◽  
Integral Control ◽  
Loop Transfer Function ◽  
Model Transfer ◽  
Static Output

In this study, the discrete-time H∞ model matching problem with integral control by using 2 DOF static output feedback is presented. First, the motivation and the problem is stated. After presenting the notation, the two lemmas toward the discrete-time H∞ model matching problem with integral control are proven. The controller synthesis theorem and the controller design algorithm is elaborated in order to minimize the H∞ norm of the closed-loop transfer function and to maximize the closed-loop performance by introducing the model transfer matrix. In following, the discrete-time H∞ MMP via LMI approach is derived as the main result. The controller construction procedure is implemented by using a well-known toolbox to improve the usability of the presented results. Finally, some conclusions are given.

Analytic Loop Shaping Methods in Quantitative Feedback Theory

1994 ◽  
Vol 116 (2) ◽  
pp. 169-177 ◽  
Author(s):  
D. F. Thompson ◽  
O. D. I. Nwokah
Keyword(s):  
Uncertain Systems ◽  
Closed Loop ◽  
Design Method ◽  
Control Design ◽  
Quantitative Feedback Theory ◽  
Single Input Single Output ◽  
Single Output ◽  
Direct Design ◽  
Single Input ◽  
Robust Control Design

Quantitative Feedback Theory (QFT), a robust control design method introduced by Horowitz, has been shown to be useful in many cases of multi-input, multi-output (MIMO) parametrically uncertain systems. Prominent is the capability for direct design to closed-loop frequency response specifications. In this paper, the theory and development of optimization-based algorithms for design of minimum-gain controllers is presented, including an illustrative example. Since MIMO QFT design is reduced to a series of equivalent single-input, single-output (SISO) designs, the emphasis is on the SISO case.

New algorithm for closed-loop model matching

1991 ◽  
Vol 27 (24) ◽  
pp. 2260 ◽  
Author(s):  
L.A. Aguirre
Keyword(s):  
Closed Loop ◽  
Loop Model ◽  
Model Matching

Algorithm for Approximate Model Matching for Loops With Non-Negligible Feedback Dynamics

1998 ◽  
Vol 120 (3) ◽  
pp. 394-398
Author(s):  
Luis Antonio Aguirre
Keyword(s):  
Closed Loop ◽  
Reference Model ◽  
Approximate Model ◽  
New Method ◽  
Moment Matching ◽  
Model Matching ◽  
Closed Loop System ◽  
Matching Problem ◽  
New Approach ◽  
Numerical Examples

This paper develops a new algorithm to solve the model matching problem in cases where the feedback dynamics should be taken into account in the design of the closed-loop system. One of the main features of the new method is that the matching is carried out by moment matching and is therefore approximate. The new algorithm is computationally simple and it permits the designer to choose relatively simple structures for the reference model and the controller. Numerical examples are included to illustrate the new approach.

Closed-Loop System Identification Based on Data Correlation

2013 ◽  
Vol 136 (1) ◽  
Author(s):  
Hassene Jammoussi ◽  
Matthew Franchek ◽  
Karolos Grigoriadis ◽  
Martin Books
Keyword(s):  
System Identification ◽  
Instrumental Variables ◽  
Closed Loop ◽  
Linear Time ◽  
Open Loop ◽  
Loop System ◽  
Loop Model ◽  
Closed Loop System ◽  
Engine Operation ◽  
Single Input Single Output

A closed-loop system identification method is developed to estimate the parameters of a single input single output (SISO) linear time invariant system (LTI) operating within a feedback loop. The method uses the reference command in addition to the input–output data and establishes a correlation framework to structure the system. The correlation-based method is capable of delivering consistent estimates provided that the specific conditions on the signals are met. The method parallels the instrumental variables four step algorithm (IV4) and is comprised of three steps. First a model is estimated using cross correlation calculations between the reference input signal and the control and measured output signals. In the second step, a prefilter is identified to reduce estimation bias. In the final step, the prefilter, the instrumental variables and the measured signals are employed to estimate the final model. A consistency proof is provided for the proposed estimation process. The method is demonstrated on two examples. The first uses data collected from a diesel engine operation, and an open-loop model relating fueling to engine speed is sought. The identification process is complicated by the presence of nonmeasurable external torque disturbances and stochastic sensor noise. The second example uses data obtained from a time domain simulation of a closed-loop system where high levels of nonmeasured noise and disturbances were considered and a comparison with existing methods is made.

Controller Design For Nonlinear Systems Based on Simultaneous Stabilization Theory and Describing Function Models

1988 ◽  
Vol 110 (2) ◽  
pp. 134-142 ◽  
Author(s):  
A. Nassirharand ◽  
J. H. Taylor ◽  
K. N. Reid
Keyword(s):  
Position Control ◽  
Controller Design ◽  
Design Procedure ◽  
Describing Function ◽  
Simultaneous Stabilization ◽  
Single Input Single Output ◽  
Single Output ◽  
Highly Nonlinear ◽  
Sinusoidal Input ◽  
Function Models

A new systematic and algebraic linear control system design procedure for use with highly nonlinear plants is developed. This procedure is based on simultaneous stabilization theory and sinusoidal-input describing function models of the nonlinear plant, and is presently applicable to single-input single-output, time-invariant, deterministic, stable, and continuous-time systems which are representable in standard state-variable differential equation form. Three software utilities to implement the controller design procedure are also outlined. This method and the associated software is applied to a position control problem of the sort encountered in robotics, and the results are compared with those previously obtained using both linear and nonlinear PID control.

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