Design of Optimized Fuzzy PD Cascade Controller Based on Parallel Genetic Algorithms
Seunghyun Jung, Jeoung‐Nae Choi, Sung-Kwun Oh, Hyunki Kim · Journal of Korean institute of intelligent systems · 2009
In this paper, we propose the design of an optimized fuzzy cascade controller for rotary inverted pendulum system by means of Hierarchical Fair Competition-based Genetic Algorithms (HFCGA) which is a kind of parallel genetic algorithms. The rotary inverted pendulum system is the system for controlling the inclination of pendulum axis through the adjustment of rotating arm. The control objective of the system is to control the position of rotating arm and to make the pendulum maintain the unstable equilibrium point of vertical position. To control rotary inverted pendulum system, we designs the fuzzy cascade controller scheme consisted of two fuzzy controllers and optimizes the parameters of the designed controller by means of HFCGA. A comparative analysis between the simulation and the practical experiment demonstrates that the proposed HFCGA based fuzzy cascade controller leads to superb performance in comparison with the conventional LQR controller as well as HFCGA based PD cascade controller.