scholarly journals Design of Stable Controllers for Model Following Discrete Time Systems Using Approximate Inverse System.(Dept.M)

2021 ◽  
Vol 26 (4) ◽  
pp. 1-13
Author(s):  
Gamal El-Bayoumi
Keyword(s):  
Discrete Time ◽  
Inverse System ◽  
Approximate Inverse ◽  
Model Following ◽  
Discrete Time Systems ◽  
Time Systems

On Self-Tuning Control of Nonminimum Phase Discrete-Time Systems Using Approximate Inverse Systems

1993 ◽  
Vol 115 (1) ◽  
pp. 12-18 ◽  
Author(s):  
Takashi Yahagi ◽  
Jianming Lu
Keyword(s):  
Discrete Time ◽  
Stochastic Systems ◽  
Output Data ◽  
Approximate Inverse ◽  
Nonminimum Phase ◽  
Discrete Time Systems ◽  
Inverse Systems ◽  
Self Tuning ◽  
The Stability ◽  
Time Systems

This paper presents a new method for self-tuning control of nonminimum phase discrete-time stochastic systems using approximate inverse systems obtained from the least-squares approximation. We show how unstable pole-zero cancellations can be avoided, and that this method has the advantage of being able to determine an approximate inverse system independently of the plant zeros. The proposed scheme uses only the available input and output data and the stability using approximate inverse systems is analyzed. Finally, the results of computer simulation are presented to show the effectiveness of the proposed method.

Robust tracking and model-following for uncertain discrete-time systems

2017 ◽  
Vol 40 (10) ◽  
pp. 3211-3221
Author(s):  
Behrooz Rahmani
Keyword(s):  
Discrete Time ◽  
Sliding Mode ◽  
Lyapunov Theory ◽  
Control Input ◽  
Robust Tracking ◽  
Parameter Uncertainties ◽  
Model Following ◽  
Discrete Time Systems ◽  
Time Systems ◽  
Tracking And Model Following

This paper proposes a robust control strategy for robust tracking and model-following of a class of uncertain linear discrete-time systems. This method is based on the discrete-time sliding mode control and ensures stability, robustness and output tracking against the modelling uncertainties even for large sampling periods. In this way, two strategies are used: firstly, the well-known Lyapunov theory is used to achieve a set of linear matrix inequalities, which is then utilized to design the sliding surface; secondly, a control input is designed to reach the quasi-sliding mode. Simulation studies show the effectiveness of the proposed method in the presence of parameter uncertainties.

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