Design of Takagi-Sugeno Fuzzy Controller Based on Improved Quantum Genetic Algorithm
Panchi Li · Jisuanji gongcheng · 2011
Frequent decoding operations severely reduce the optimization efficiency when the binary Quantum Genetic Algorithm(QGA) based on qubits measure is applied to the continuous space optimization.Aiming at the problem,an improved QGA based on phase of qubits encoding is proposed.The chromosomes are encoded by the phase of qubits,updated by quantum rotation gates,and mutated by quantum Pauli-Z gates.As the optimization process is performed in,the algorithm has good adaptability for a variety of optimization problems in the different scale space.Taking parameter optimization of Takagi-Sugeno(T-S) fuzzy controller of single level inverted pendulum as example,the simulation results show that the algorithm has advantages in search ability and optimize efficiency.