Multiobjective robust discrete dynamic output-feeback control synthesis based on closed-loop reference model

2011 ◽  
Author(s):  
Wagner Eustaquio Gomes Bachur ◽  
Eduardo Nunes Goncalves ◽  
Valter Junior de Souza Leite ◽  
Reinaldo Martinez Palhares
Keyword(s):  
Closed Loop ◽  
Reference Model ◽  
Control Synthesis ◽  
Discrete Dynamic ◽  
Dynamic Output

Robust ℋ2/ℋ∞/reference model dynamic output-feedback control synthesis

2011 ◽  
Vol 84 (12) ◽  
pp. 2067-2080 ◽  
Author(s):  
E.N. Gonçalves ◽  
W.E.G. Bachur ◽  
R.M. Palhares ◽  
R.H.C. Takahashi
Keyword(s):  
Feedback Control ◽  
Output Feedback ◽  
Reference Model ◽  
Output Feedback Control ◽  
Control Synthesis ◽  
Dynamic Output Feedback ◽  
Dynamic Output

Multiobjective robust dynamic output-feeback control synthesis based on reference model

2010 ◽  
Author(s):  
Wagner Eustaquio Gomes Bachur ◽  
Eduardo Nunes Goncalves ◽  
Reinaldo Martinez Palhares ◽  
Ricardo Hiroshi Caldeira Takahashi
Keyword(s):  
Reference Model ◽  
Control Synthesis ◽  
Dynamic Output

scholarly journals H∞ Tracking Control of Fuzzy Dynamic Output for Nonlinear Networked System with Packet Dropouts

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Yang Wang ◽  
Jinna Li ◽  
Xiaolei Ji
Keyword(s):  
Output Feedback ◽  
Tracking Control ◽  
Closed Loop ◽  
Reference Model ◽  
Sufficient Conditions ◽  
Fuzzy Model ◽  
Loop System ◽  
Dynamic Output Feedback ◽  
Closed Loop System ◽  
Dynamic Output

The tracking control of H∞ dynamic output feedback is proposed for the fuzzy networked systems of the same category, in which each system is discrete-time nonlinear and is missing measurable data. In other words, the loss of data packet occurs randomly in both the uplink and the downlink. The independent variables that are called the Bernoulli random variables are considered to design the loss of data packets. The method of parallel distributed compensation (PDC) in terms of the T-S fuzzy model is applied to investigate the dynamic controller of tracking control on the systems. Then, it is presented that the analytical H∞ performance of the output error between the reference model and the fuzzy model for the closed-loop system containing dynamic output feedback controller is proven. Furthermore, the achieved sufficient conditions in terms of LMIs ensure that the closed-loop system is stochastically stable in the H∞ sense. Finally, a numerical system is offered to show the effectiveness of the established technique.

The Implementation of the Minimal Control Synthesis Algorithm on a Web Control Problem

1994 ◽  
Vol 208 (1) ◽  
pp. 53-60 ◽  
Author(s):  
D P Stoten ◽  
M G Dye ◽  
M Webb
Keyword(s):  
Closed Loop ◽  
Control Synthesis ◽  
Time Varying ◽  
Closed Loop System ◽  
Synthesis Algorithm ◽  
Time Varying Parameters ◽  
Transport Control ◽  
Adaptive Control Strategy ◽  
Web Control ◽  
Experimental Comparisons

The minimal control synthesis (MCS) algorithm is an adaptive control strategy that requires no prior knowledge of plant dynamic parameters, and yet is guaranteed to provide global asymptotic stability of the closed-loop system. The purpose of this paper is to present MCS as applied to web tension und transport control a class of plant that has highly non-linear dynamics and time-varying parameters. The plant is difficult to control by conventional methods over its full operating range. A typical example and model of such a plant is presented along with the implementation of MCS. Experimental comparisons of MCS with conventional control benchmarks are provided. It will be seen that MCS significantly outperforms the conventional controller.

An Optimal Preview Acceleration Driver Model with a Correction Factor for Vehicle Directional Control

2013 ◽  
Vol 437 ◽  
pp. 623-628 ◽  
Author(s):  
Hsin Guan ◽  
Li Zeng Zhang ◽  
Xin Jia
Keyword(s):  
Correction Factor ◽  
Closed Loop ◽  
Reference Model ◽  
Driver Model ◽  
Closed Loop System ◽  
Moving Vehicle ◽  
Directional Control ◽  
Modeling Errors ◽  
Acceleration Model ◽  
Model Reference Adaptive

Parameters of the optimal preview acceleration driver model for vehicle directional control are determined by drivers delay/lag time and parameters of the reference model of the controlled vehicle. A moving vehicle is a time-varying and nonlinear system, so it is difficult to obtain accurate parameters of the reference model. If large modeling errors of the reference model occur, the classic driver model cannot ensure the driver/vehicle closed-loop system have a satisfactory performance. In this paper, an improved optimal preview acceleration model with a correction factor was proposed, which is based on sensitivity analysis and MRAC (the model reference adaptive control). Simulation results show that the improved driver model has more satisfactory adaptability and robustness comparing with the classic driver model.

The error-based minimal control synthesis algorithm with integral action

2003 ◽  
Vol 217 (3) ◽  
pp. 187-201 ◽  
Author(s):  
D P Stoten ◽  
S A Neild
Keyword(s):  
Closed Loop ◽  
Control Synthesis ◽  
Closed Loop System ◽  
Synthesis Algorithm ◽  
The Core ◽  
Gain Term ◽  
Integral Action ◽  
Implementation Studies ◽  
Hyperstability Theory ◽  
Integral Gain

This paper presents a new form of the direct adaptive minimal control synthesis (MCS) algorithm. As its name suggests, the error-based minimal control synthesis with integral action (Er-MCSI) algorithm is solely driven by error signals that are generated within the closed-loop system, and contains an explicit integral gain term. The purpose of this new structure is, respectively, to remove the problem of variable adaptive effort with changes in the operating set point, and to remove gain ‘wind-up’ effects due to plant disturbances and signal offsets. The core of this paper contains a proof of stability for Er-MCSI, based on hyperstability theory, together with supporting simulation and implementation studies.

On discrete dynamic output feedback min–max controllers

Automatica ◽  
2005 ◽  
Vol 41 (10) ◽  
pp. 1783-1790 ◽  
Author(s):  
Christopher Edwards ◽  
Nai One Lai ◽  
Sarah K. Spurgeon
Keyword(s):  
Output Feedback ◽  
Dynamic Output Feedback ◽  
Discrete Dynamic ◽  
Dynamic Output
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