Learning-based Event-triggered Adaptive Optimal Output Regulation of Linear Discrete-time Systems

Author(s):  
Fuyu Zhao ◽  
Weinan Gao ◽  
Tengfei Liu ◽  
Zhong-Ping Jiang
2020 ◽  
Vol 50 (7) ◽  
pp. 3147-3156 ◽  
Author(s):  
Yi Jiang ◽  
Bahare Kiumarsi ◽  
Jialu Fan ◽  
Tianyou Chai ◽  
Jinna Li ◽  
...  

Author(s):  
Yaoli Zhang ◽  
Jun Zhao

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.


2019 ◽  
Vol 13 ◽  
Author(s):  
Zuchang Zhang ◽  
Dongliang Lin ◽  
Xingyi Wang ◽  
Zhenhua Shao ◽  
Wenzhong Lin

Sign in / Sign up

Export Citation Format

Share Document