Abstract: The purpose of
Linear Quadratic Regulator (LQR) optimal control system is to stabilize the
system, so that the output of the system towards a steady state by minimizing
the performance index. LQR-invinite horizon is a special case of LQR in
thecontinuous time area where the terminal time of the performance index value
for infinite time and infinite outputsystem is zero. Performance index will be
affected by the weighting matrix. In this paper will be discussed about the
application of Particle Swarm Optimization algorithm (PSO) and Differential
Evolution Algorithm (DEA) to determine the state feedback of a closed loop
system and weighting matrices in the LQR to minimize performance index. PSO
algorithm is a computational algorithm inspired by social behavior of flocks of
birds and fishes in searching of food. While the DEA is an optimization
algorithm that is adopted from evolution and genetics of organisms. Simulations
of the PSO algorithm will be compared with DEA. Based on case study, DEA is
faster then PSO to get convergence to the optimum solution.
Keywords: LQR-invinite
horizone, weighting matrix, Particle Swarm Optimization (PSO), Differential
Evolution Algorithm (DEA)
Penulis: Madchan Anis,
Widowati Widowati
Kode Jurnal: jpmatematikadd120035
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