Optimal Output Regulation of Linear Discrete-Time Systems With Unknown Dynamics Using Reinforcement Learning

2020 ◽  
Vol 50 (7) ◽  
pp. 3147-3156 ◽  
Author(s):  
Yi Jiang ◽  
Bahare Kiumarsi ◽  
Jialu Fan ◽  
Tianyou Chai ◽  
Jinna Li ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Discrete Time ◽  
Output Regulation ◽  
Optimal Output ◽  
Discrete Time Systems ◽  
Time Systems

Output regulation for switched discrete-time systems with output signal quantization

2021 ◽  
pp. 014233122198988
Author(s):  
Yaoli Zhang ◽  
Jun Zhao
Keyword(s):  
Discrete Time ◽  
Pulse Width ◽  
Pulse Width Modulation ◽  
Output Regulation ◽  
Feedback Controllers ◽  
Signal Quantization ◽  
Discrete Time Systems ◽  
Output Regulation Problem ◽  
Time Systems ◽  
Coordinates Transformation

This paper investigates the output regulation problem for switched discrete-time systems with output quantization. We adopt the quantized output in feedback controllers and allow each subsystem to have its own quantization density, so that the communication network can be efficiently utilized. By using the different coordinates transformation, the solvability of the output regulation problem is guaranteed under deigned output feedback controllers with the switching signals satisfying a dwell time constraint. In the simulation, a pulse-width modulation driven boost converter model is employed to validate the result.

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