1 Introduction
2 Related work
2.1 Fuzzy PID controller
2.2 Adaptive controller based on neural network
2.3 Reinforcement learning adaptive controller
3 Basic structure of PID controller
4 A3C adaptive PID control
4.1 Structure of A3C-PID controller
4.2 A3C learning with neural networks
4.3 The network initialization of A3C-PID controller
4.4 Working process of A3C-PID controller
5 Experiments
5.1 Simulation experiment of nonlinear signal
Kinds of controllers | RMSE | MAE |
---|---|---|
PID | 0.1547 | 0. 0705 |
CPS-PID | 0.1201 | 0.0620 |
MN-PID | 0.1203 | 0.0628 |
AC-PID | 0.1196 | 0.0621 |
A3C-PID | 0.0884 | 0.0326 |
5.2 Simulation experiment of inverted pendulum
5.3 Position control of two phase hybrid stepping motor
5.3.1 Closed loop control structure of stepping motor
5.3.2 Modeling and simulation of two-phase hybrid stepping motor
Controller | Overshoot (%) | Rise time (ms) | Steady state error | Adjustment time (ms) |
---|---|---|---|---|
A3C-PID | 0.1571 | 18 | 0 | 33 |
AC-PID | 0.1021 | 21 | 0 | 48 |
BP-PID | 2.1705 | 12 | 0 | 32 |