Fuzzy PID control of phase-shifted full-bridge based on improved particle swarm optimization
[Objective]As a typical DC-DC topology,phase-shifted full-bridge(PSFB)converter has been widely employed in aerospace,rail transit,and power systems among other fields.Numerous intelligent control methods of the converter help improve its energy conversion efficiency.To obtain a PSFB control scheme with ideal dynamic characteristics,herein we propose a fuzzy proportional-integral-derivative(PID)control method based on improved particle swarm optimization(IPSO).[Methods]Based on the operation principle of PSFB,a small signal model of PSFB was established.Afterwards,a fuzzy controller was introduced to improve the parameters of PID.Then adaptive inertia weight and compression factor method were used to optimize global characteristics and the convergence of PSO,which contributed to the computation of proportion factors and quantization factors of fuzzy controller.Conventional PID,fuzzy PID,and fuzzy PID optimized by IPSO were conducted to control the output voltage of PSFB in simulink and a hardware experimental platform based on TMS320F28034,respectively.Finally,anti-interference tests were conducted to verify the effectiveness of the proposed control strategy.[Results]First,the average computational time complexity of PSO and IPSO was evaluated from the average number of operations and average optimization results under different iterations.Results showed that,compared with PSO,IPSO could achieve the same optimization result with 80％fewer iterations and 5％less computational complexity.This outcome demonstrated that IPSO could achieve higher control precision in shorter total operation time.Simulation results also showed that,compared with conventional PID,the adjusting time of fuzzy PID and fuzzy PID optimized by IPSO was reduced by 65.9％and 79.6％respectively.In addition,compared with fuzzy PID,the steady-state error of fuzzy PID optimized by IPSO was reduced by 87.5％,and voltage ripples and overshoots were also improved to some extent.In taking ITAE as the adaptive value function,results showed that the ITAE value of fuzzy PID optimized by IPSO was clearly minimum,approximately 8.3％of conventional PID and 50％of fuzzy PID.Because incremental PI control is used in hardware experiments,corresponding results showed that the output voltage of PSFB under incremental PI control endured high frequency noises.In comparison,steady-state errors,overshoots and output ripples of output voltages under fuzzy PI control optimized by IPSO appeared all optimal,with reduction rates as 46.7％,56.4％and 75.0％respectively.In addition,time for output voltage's stabilization under fuzzy PI control optimized by IPSO shortened to the least,i.e.approximately 0.510 s.Results of simulations and hardware experiments showed that those two systems with the fuzzy controller secured stronger robustness and stability.[Conclusions]The proposed method manages to compensate for the defect of fuzzy control so that the automatic optimization of controller parameters is attained.Fuzzy PID optimized by IPSO secures higher control precision,faster convergence speed,stronger anti-interference ability and the fastest error-elimination speed.The optimal balance between control accuracy and convergence speed is achieved by fuzzy PID optimized by IPSO.Hopefully,the proposed control strategy provides an effective way to accomplish the intelligent control of other DC-DC converters.
万方数据
维普
