Data-driven tracking control approach for linear systems by on-policy Q-learning approach

2020 ◽  
Author(s):  
Zhang Yihan ◽  
Xiao Zhenfei ◽  
Li Jinna
Keyword(s):  
Linear Systems ◽  
Tracking Control ◽  
Data Driven ◽  
Learning Approach ◽  
Control Approach ◽  
Q Learning

New Approach of Tracking Control for a Class of Non-Minimum Phase Linear Systems

2007 ◽  
Author(s):  
Bo Xie ◽  
Bin Yao
Keyword(s):  
Linear Systems ◽  
Trajectory Planning ◽  
Tracking Control ◽  
Controller Design ◽  
Tracking Error ◽  
Trajectory Design ◽  
Minimum Phase ◽  
Control Approach ◽  
Tracking Controller ◽  
Phase Systems

The paper presents a new tracking control approach for a class of non-minimum phase linear systems. The proposed approach consists of two parts: trajectory planning and tracking controller design. The trajectory planning is solved as an optimization problem to improve the achievable transient performance under the fundamental constraints associated with perfect tracking of non-minimum phase systems. The recently proposed adaptive robust tracking controller for a class of non-minimum phase systems is then applied to guarantee that the tracking error dynamics can be stabilized with bounded internal states. The effectiveness of the proposed approach is illustrated through simulation on tracking control of a second order non-minimum phase linear system. Further works are underway to extend the proposed control strategy and trajectory design to a class of non-minimum phase nonlinear systems.

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