TY - JOUR
T1 - Gain optimization for inertia wheel pendulum stabilization using particle swarm optimization and genetic algorithms
AU - Martinez-Soto, Ricardo
AU - Rodriguez, Antonio
AU - Castillo, Oscar
AU - Aguilar, Luis T.
PY - 2012/6
Y1 - 2012/6
N2 - We describe in this paper the optimization of the gains of a PID controller to stabilize the inertia wheel pendulum (IWP) using bio-inspired and evolutionary methods. Particle swarm optimization and genetic algorithms are used tond the optimal gain values of the PID controller. Computer simulations and experiments are presented showing the control results using the optimal gain values to stabilize the inertia wheel pendulum. Both particle swarm optimization (PSO) and genetic algorithms (GAs) are shown to be effective tools for gain optimization of the inertia wheel.
AB - We describe in this paper the optimization of the gains of a PID controller to stabilize the inertia wheel pendulum (IWP) using bio-inspired and evolutionary methods. Particle swarm optimization and genetic algorithms are used tond the optimal gain values of the PID controller. Computer simulations and experiments are presented showing the control results using the optimal gain values to stabilize the inertia wheel pendulum. Both particle swarm optimization (PSO) and genetic algorithms (GAs) are shown to be effective tools for gain optimization of the inertia wheel.
KW - Genetic algorithms
KW - Optimization methods
KW - Particle swarm optimization
KW - Stabilization control
UR - http://www.scopus.com/inward/record.url?scp=84861414270&partnerID=8YFLogxK
M3 - Artículo
SN - 1349-4198
VL - 8
SP - 4421
EP - 4430
JO - International Journal of Innovative Computing, Information and Control
JF - International Journal of Innovative Computing, Information and Control
IS - 6
ER -