710 A Robust Controller Design Method for Single-Input-Single-Output Systems by Using a Nonlinear Optimization Technique

2000 ◽  
Vol 2000.53 (0) ◽  
pp. 223-224
Author(s):  
Yuichi KONDO ◽  
Tetsuji SHIMOGAWA ◽  
Chang-jun LIN ◽  
Hiroaki OZAKI
Keyword(s):  
Nonlinear Optimization ◽  
Controller Design ◽  
Design Method ◽  
Optimization Technique ◽  
Robust Controller ◽  
Single Input Single Output ◽  
Single Output ◽  
Single Input ◽  
Robust Controller Design

scholarly journals D-Optimal Design for Information Driven Identification of Static Nonlinear Elements

2021 ◽  
Author(s):  
Nalika Ulapane ◽  
Karthick Thiyagarajan ◽  
sarath kodagoda ◽  
Linh Nguyen
Keyword(s):  
Optimal Design ◽  
Model Calibration ◽  
Design Method ◽  
Single Input Single Output ◽  
Single Output ◽  
Order Polynomial ◽  
Information Maximization ◽  
Pros And Cons ◽  
Single Input ◽  
Optimal Design Method

<div>Identification of static nonlinear elements (i.e., nonlinear elements whose outputs depend only on the present value of inputs) is crucial for the success of system identification tasks. Identification of static nonlinear elements though can pose several challenges. Two of the main challenges are: (1) mathematical models describing the elements being unknown and thus requiring black-box identification; and (2) collection of sufficiently informative measurements. With the aim of addressing the two challenges, we propose in this paper a method of predetermining informative measurement points offline (i.e., prior to conducting experiments or seeing any measured data), and using those measurements for online model calibration. Since we deal with an unknown model structure scenario, a high order polynomial model is assumed. Over fit and under fit avoidance are achieved via checking model convergence via an iterative means. Model dependent information maximization is done via a D-optimal design of experiments strategy. Due to experiments being designed offline and being designed prior to conducting measurements, this method eases off the computation burden at the point of conducting measurements. The need for in-the-loop information maximization while conducting measurements is avoided. We conclude by comparing the proposed D-optimal design method with a method of in-the-loop information maximization and point out the pros and cons. The method is demonstrated for the single-input-single-output (SISO) static nonlinear element case. The method can be extended to MISO systems as well.</div>

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.

Robust Controller Design for Active Vibration Control

1993 ◽  
Author(s):  
S. Jagannathan ◽  
A. B. Palazzolo ◽  
A. F. Kascak ◽  
G. T. Montague
Keyword(s):  
Vibration Control ◽  
Controller Design ◽  
Design Method ◽  
Active Vibration Control ◽  
Single Input Single Output ◽  
Background Theory ◽  
Single Output ◽  
Performance Specifications ◽  
Bearing Stiffness ◽  
Active Vibration

A novel frequency-domain technique, having its roots in Quantitative Feedback Theory (QFT), has been developed to design controllers for active vibration control (AVC). The advantages are a plant-based design according to performance specifications, and the ability to include structured uncertainties in the critical plant parameters like passive bearing stiffness or damping. In this paper, we describe the background theory of single-input, single-output (SISO) and multi-input, multi-output (MIMO) QFT design, followed by development of the theory adapted for AVC. Application examples are considered next, outlining the design method for both cases. Simulation results for the systems studied are presented showing the effectiveness of the technique in attenuating vibration.

Control of Exoskeletons Inspired by Fictitious Variable Gain in Human

2008 ◽  
Author(s):  
Kyoungchul Kong ◽  
Masayoshi Tomizuka
Keyword(s):  
Control System ◽  
Control Algorithm ◽  
Controller Design ◽  
Assistive Device ◽  
Single Input Single Output ◽  
Variable Gain ◽  
Single Output ◽  
Single Input ◽  
Parallel Control ◽  
The Brain

A human wearing an exoskeleton-type assistive device results in a parallel control system that includes two controllers: the human brain and a digital exoskeleton controller. Unknown and complicated characteristics of the brain dynamically interact with the exoskeleton controller which makes the controller design challenging. In this paper, the motion control system of a human is regarded as a feedback control loop that consists of a brain, muscles and the dynamics of the extended human body. The brain is modeled as a control algorithm amplified by a fictitious variable gain. The variable gain compensates for characteristic changes in the muscle and dynamics. If a human is physically impaired or subjected to demanding work, the exoskeleton should generate proper assistive forces, which is equivalent to increasing the variable gain. In this paper, a control algorithm that realizes the fictitious variable gain is designed and its performance and robustness are discussed for single-input single-output cases. The control algorithm is then verified by simulation results.

scholarly journals A Robust Controller Design Method Based on Parameter Variation Rate of RBF-ARX Model

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 160284-160294 ◽  
Author(s):  
Feng Zhou ◽  
Hui Peng ◽  
Ganglin Zhang ◽  
Xiaoyong Zeng
Keyword(s):  
Controller Design ◽  
Design Method ◽  
Parameter Variation ◽  
Robust Controller ◽  
Arx Model ◽  
Variation Rate ◽  
Robust Controller Design
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