A DRL-Based Adaptive Control Design for a Class of Nonlinear Systems With Mismatched Disturbances: From Algorithm to Application

Focusing on control performance enhancement for a general class of nonlinear systems with mismatched disturbances, an intelligent composite regulator is investigated by integrating disturbance observation, nonrecursive nonsmooth control (NRNSC), and deep reinforcement learning (DRL) techniques in th...

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Vydané v:IEEE transactions on industrial informatics Ročník 21; číslo 5; s. 4126 - 4135
Hlavní autori: Dong, Xin, Zhang, Chuanlin, Chen, Hongtian, Zhang, Weidong
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway IEEE 01.05.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Adaptive algorithms
Adaptive control
Bandwidth
Control systems
Control theory
Deep learning
Deep reinforcement learning
Deep reinforcement learning (DRL)
Disturbances
Estimation
Feedback control systems
Feedback loops
mismatched disturbance
Nonlinear systems
nonrecursive nonsmooth control (NRNSC)
Optimization
parameter optimization
Performance enhancement
permanent magnet synchronous motor (PMSM)
Permanent magnets
Robust control
Robustness
Servomotors
Steady-state
Switches
Synchronous motors
Trajectory
Transient analysis
Tuning
ISSN:1551-3203, 1941-0050
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Popis
Shrnutí:Focusing on control performance enhancement for a general class of nonlinear systems with mismatched disturbances, an intelligent composite regulator is investigated by integrating disturbance observation, nonrecursive nonsmooth control (NRNSC), and deep reinforcement learning (DRL) techniques in this article. With the help of the self-learning ability delivered by the DRL algorithm, a robust adaptive control scheme is constructed for handling the challenge of parameter configuration difficulty in the traditional NRNSC synthesis approach. A new feature is that the bandwidth factor optimization in both feedforward and feedback loops is simultaneously considered. While ensuring the system maintains certain robustness, the most suitable adaptive bandwidth factors are self-tuned to optimize the control performance. Thereafter, an appropriate tradeoff is promisingly achieved between the two performances. To enhance the persuasiveness of the proposed method in terms of performance improvement, numerical simulations, and experiment tests on a permanent magnet synchronous motor (PMSM) position servo platform are conducted.
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content type line 14
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2024.3507191