• Corpus ID: 241033326

A Self-adaptive LSAC-PID Approach based on Lyapunov Reward Shaping for Mobile Robots

  title={A Self-adaptive LSAC-PID Approach based on Lyapunov Reward Shaping for Mobile Robots},
  author={Xinyi Yu and Siyu Xu and Yuehai Fan and Linlin Ou},
To solve the coupling problem of control loops and the adaptive parameter tuning problem in the multi-input multi-output (MIMO) PID control system, a self-adaptive LSAC-PID algorithm is proposed based on deep reinforcement learning (RL) and Lyapunovbased reward shaping in this paper. For complex and unknown mobile robot control environment, an RL-based MIMO PID hybrid control strategy is firstly presented. According to the dynamic information and environmental feedback of the mobile robot, the… 



A Self-adaptive SAC-PID Control Approach based on Reinforcement Learning for Mobile Robots

The combination of 24-neighborhood method and polynomial fitting is developed to improve the adaptability of SAC-PID control method to complex environments and has merits of strong robustness, generalization and real-time performance.

A Proposal of Adaptive PID Controller Based on Reinforcement Learning

Double Q-PID algorithm for mobile robot control

Adaptive PID Controller based on Reinforcement Learning for Wind Turbine Control

A self tuning PID control strategy using reinforcement learning is proposed in this paper to deal with the control of wind energy conversion systems (WECS) and it is perfectly adaptable and strongly robust, which is better than that of a conventional PID controller.

Reinforcement Learning Adaptive PID Controller for an Under-actuated Robot Arm

An actor-critic based reinforcement learning is employed for tuning of parameters of the adaptive PID controller for real time applications as well as update rules to verify good performance of the controller in tracking and disturbance rejection tests.

Gain Tuning of Fuzzy PID Controllers for MIMO Systems: A Performance-Driven Approach

A new methodology for tuning the scaling factors, or gains, of fuzzy proportional-integral-derivative controllers, by taking explicitly into account the closed-loop system performance is proposed in

Principled reward shaping for reinforcement learning via lyapunov stability theory

Robust Adaptive Fault-Tolerant PID Control of MIMO Nonlinear Systems With Unknown Control Direction

This paper shows that the structurally simple and computationally inexpensive PID control, popular with single-input single-output (SISO) linear time-invariant systems, can be generalized and