Unstable System Control Using an Improved Particle Swarm Optimization-Based Neural Network Controller
Keyword(s):
In this study, an improved particle swarm optimization (IPSO)-based neural network controller (NNC) is proposed for solving a real unstable control problem. The proposed IPSO automatically determines an NNC structure by a hierarchical approach and optimizes the parameters of the NNC by chaos particle swarm optimization. The proposed NNC based on an IPSO learning algorithm is used for controlling a practical planetary train-type inverted pendulum system. Experimental results show that the robustness and effectiveness of the proposed NNC based on IPSO are superior to those of other methods.
2008 ◽
Vol 23
(6)
◽
pp. 3067-3078
◽
2009 ◽
Vol 45
(8)
◽
pp. 3151-3165
◽
2013 ◽
Vol 333-335
◽
pp. 1384-1387