Open AccessController parameter tuning using actor-critic algorithm
Author(s) -
Ayman E. M. Ahmed
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/610/1/012054
Subject(s) - overshoot (microwave communication) , missile , pid controller , control theory (sociology) , reinforcement learning , aerodynamics , computer science , schedule , missile guidance , control engineering , process (computing) , convergence (economics) , controller (irrigation) , engineering , control (management) , artificial intelligence , aerospace engineering , temperature control , telecommunications , agronomy , economic growth , economics , biology , operating system
In this paper a new reinforcement learning strategy is used for on-line tuning the control system of the aerodynamic missile. Aerodynamics missile automatic control system’s mission is to overcome the missile’s flight various disturbances encountered in the process of precise and real-time control of missiles attitude. Reinforcement learning algorithm (RL) is used to tune a PID controller to replace “gain schedule” Technique usually used. The result shows that RL with the new reward function is able to optimize the PID parameters with advantage over old method in terms of convergence speed and smaller overshoot.