scholarly journals PD-Type Iterative Learning Control for Uncertain Spatially Interconnected Systems

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1528
Author(s):  
Longhui Zhou ◽  
Hongfeng Tao ◽  
Wojciech Paszke ◽  
Vladimir Stojanovic ◽  
Huizhong Yang
Keyword(s):  
Iterative Learning Control ◽  
Process Model ◽  
Singular System ◽  
Learning Control ◽  
Iterative Learning ◽  
Interconnected Systems ◽  
Space Model ◽  
Repetitive Process ◽  
Spatially Interconnected Systems ◽  
The Stability

This paper puts forward a PD-type iterative learning control algorithm for a class of discrete spatially interconnected systems with unstructured uncertainty. By lifting and changing the variable of discrete space model, the uncertain spatially interconnected systems is converted into equivalent singular system, and the general state space model is derived in view of singular system theory. Then, the state error and output error information are used to design the iterative learning control law, transforming the controlled system into an equivalent repetitive process model. Based on the stability theory of repetitive process, sufficient condition for the stability of the system along the trial is given in the form of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed algorithm is verified by the simulation of ladder circuits.

Robust Iterative Learning Control for Spatially Interconnected Systems using 2D Control Theory*

2021 ◽  
Author(s):  
Bartlomiej Sulikowski ◽  
Krzysztof Galkowski ◽  
Daniel Trzcinski ◽  
Eric Rogers ◽  
Anton Kummert
Keyword(s):  
Control Theory ◽  
Iterative Learning Control ◽  
Learning Control ◽  
Iterative Learning ◽  
Interconnected Systems ◽  
Spatially Interconnected Systems

Iterative learning control for spatially interconnected systems

2014 ◽  
Vol 237 ◽  
pp. 438-445 ◽  
Author(s):  
Byeong-Yeon Kim ◽  
Taekyung Lee ◽  
Young-Soo Kim ◽  
Hyo-Sung Ahn
Keyword(s):  
Iterative Learning Control ◽  
Learning Control ◽  
Iterative Learning ◽  
Interconnected Systems ◽  
Spatially Interconnected Systems

scholarly journals Output Information Based Fault-Tolerant Iterative Learning Control for Dual-Rate Sampling Process with Disturbances and Output Delay

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Hongfeng Tao ◽  
Yan Liu ◽  
Huizhong Yang
Keyword(s):  
Iterative Learning Control ◽  
Fault Tolerant ◽  
Sampling Rate ◽  
Sufficient Conditions ◽  
Learning Control ◽  
Iterative Learning ◽  
Repetitive Process ◽  
Sampling Process ◽  
Output Delay ◽  
Output Information

For a class of single-input single-output (SISO) dual-rate sampling processes with disturbances and output delay, this paper presents a robust fault-tolerant iterative learning control algorithm based on output information. Firstly, the dual-rate sampling process with output delay is transformed into discrete system in state-space model form with slow sampling rate without time delay by using lifting technology; then output information based fault-tolerant iterative learning control scheme is designed and the control process is turned into an equivalent two-dimensional (2D) repetitive process. Moreover, based on the repetitive process stability theory, the sufficient conditions for the stability of system and the design method of robust controller are given in terms of linear matrix inequalities (LMIs) technique. Finally, the flow control simulations of two flow tanks in series demonstrate the feasibility and effectiveness of the proposed method.

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