Robust Non-Fragile Controller Design for Discrete Time Systems with FWL Consideration

2001 ◽  
pp. 213-228 ◽  
Author(s):  
Guang-Hong Yang ◽  
Jian Liang Wang ◽  
Yeng Chai Soh
Keyword(s):  
Discrete Time ◽  
Controller Design ◽  
Discrete Time Systems ◽  
Time Systems

Stability and robustness for discrete-time systems with control signal saturation

2000 ◽  
Vol 214 (1) ◽  
pp. 65-76 ◽  
Author(s):  
A R Plummer ◽  
C S Ling
Keyword(s):  
Discrete Time ◽  
Controller Design ◽  
Control Signal ◽  
Design Stage ◽  
System Control ◽  
Stability Robustness ◽  
Discrete Time Systems ◽  
The Stability ◽  
Time Systems ◽  
Signal Saturation

All practical control systems exhibit control signal saturation. The effect that this saturation has on the control system performance, especially stability and robustness, can be significant and must be understood at the controller design stage. This paper presents conditions for global asymptotic stability and measures of stability robustness for such systems. These are demonstrated through simulation examples, and it is shown how an understanding of the stability conditions can inform the controller design process. The off-axis circle criterion is used as the basis for a sufficient condition for stability, and it is argued that this is not overly restrictive in practice. The derivations are carried out in discrete time, and servo-system control is envisaged as an important application area for the techniques; however, the results are applicable more widely.

scholarly journals Design of a Preview Controller for Discrete-Time Systems Based on LMI

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Li Li ◽  
Fucheng Liao
Keyword(s):  
Steady State ◽  
Discrete Time ◽  
Controller Design ◽  
Design Method ◽  
Reference Signal ◽  
Original System ◽  
Disturbance Attenuation ◽  
Linear Matrix ◽  
Discrete Time Systems ◽  
Time Systems

A preview controller design method for discrete-time systems based on LMI is proposed. First, we use the difference between a system state and its steady-state value, instead of the usual difference between system states, to transform the tracking problem into a regulator problem. Then, based on the Lyapunov stability theory and linear matrix inequality (LMI) approach, the preview controller ensuring asymptotic stability of the closed-loop system for the derived augmented error system is found. And an extended functional observer is designed in this paper which can achieve disturbance attenuation in the estimation process; as a result, the state of the system can be reconstructed rapidly and accurately. The controller gain matrix is obtained by solving an LMI problem. By incorporating the controller obtained into the original system, we obtain the preview controller of the system under consideration. To make sure that the output tracks the reference signal without steady-state error, an integrator is introduced. The numerical simulation example also illustrates the effectiveness of the results in the paper.

Two-Stage Feedback Control Design for a Class of Linear Discrete-Time Systems With Slow and Fast Modes

2015 ◽  
Vol 137 (8) ◽  
Author(s):  
Verica Radisavljevic-Gajic
Keyword(s):  
Time Scales ◽  
Discrete Time ◽  
Controller Design ◽  
Feedback Controller ◽  
Two Stage ◽  
Stage Design ◽  
Design Algorithm ◽  
Discrete Time Systems ◽  
Two Stage Design ◽  
Time Systems

In this paper, we first review the new algorithm for the two-stage feedback controller design of linear discrete-time systems, and then provide conditions for its applicability. The design algorithm is specialized and simplified for a class of linear systems with slow and fast modes (multitime scale systems or singularly perturbed systems). The proposed design significantly reduces computational full-state feedback design requirements and provides independent and accurate feedback controller design techniques in slow and fast time scales. We present also conditions needed for applicability of the proposed two-stage design in two time scales. The power of the two-stage design lies in the fact that different types of controllers can be designed for different subsystems using the corresponding feedback gains obtained by performing calculations only with the subsystem (reduced-order) matrices.

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