A Data-Driven Model-Reference Adaptive Control Approach Based on Reinforcement Learning
2021 IEEE International Symposium on Robotic and Sensors Environments (ROSE)(2021)
摘要
Model-reference adaptive systems refer to a consortium of techniques that guide plants to track desired reference trajectories. Approaches based on theories like Lyapunov, sliding surfaces, and backstepping are typically employed to advise adaptive control strategies. The resulting solutions are often challenged by the complexity of the reference model and those of the derived control strategies. ...
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关键词
Adaptation models,Adaptive learning,Atmospheric modeling,Integral equations,Process control,Reinforcement learning,Mathematical models
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