Design And Application Of Fuzzy Controller Based On Particle Swarm Optimization

In recent years,with the continuous development of fuzzy control,the control object gradually expanded from cement kiln,household appliances,etc to robots,machine tools,etc.As a result,we have a higher demand on the control performance and the design method of the fuzzy controller.Fuzzy control inspired by the decision-making behavior of human brain has good performance for nonlinear system as its strong robustness.However,fuzzy control has the disadvantages of low control precision and long development period.It has been an important direction to shorten the design cycle through using optimization algorithm to automatically optimize the fuzzy controller.Particle swarm optimization(PSO)algorithm is an optimization algorithm for simulating swarm intelligence.The algorithm is gradually introduced into the parameter optimization of fuzzy controller by the advantages of less parameters,simplicity and excellent global search ability.First,the standard particle swarm optimization algorithm and its parameter setting method are studied.On this basis,a new adaptive simulated annealing particle swarm optimization(ASAPSO)algorithm is proposed.In this algorithm,each learning factor is automatically adjusted based on each particle's fitness and the acceptable rule of simulated annealing is applied in the process of the particle position updating.The optimization results of multimodal test function show that this algorithm has advantage of jumping out of local optimum and getting better accuracy.Furthermore,by studying the principle of PID fuzzy simulation,a PI type fuzzy controller based on ASAPSO design method is proposed.The PI type fuzzy controller based on ASAPSO is achieved by initialization of the fuzzy rules by PI fuzzy simulation and optimization of the weights of the fuzzy rules and quantitative scaling factor by ASAPSO algorithm.At the same time,the fuzzy controller design process and algorithm procedures are given.The performance of the fuzzy controller is tested by a typical two order industrial process function.The simulation results show that the fuzzy controller designed by this method inherits the accuracy of the PI controller,and has faster response speed than the PI controller.Finally,in order to further verify the effectiveness of the proposed fuzzy controller design method,the fuzzy controller is applied to control the speed of brushless dc motor and the hand holding force of surgical robot.The simulation results show that the fuzzy controller has better anti disturbance performance than a PI controller when the brushless dc encounter a mutation load or start with a load;it also has a more stable control performance than a PI controller when the elastic modulus of objects gripped by the surgical robot hand have great changes.