Research On The Control Strategy Of Hydraulic Power Source Driven By Permanent Magnet Motor Based On Intelligent Optimization Method

Permanent magnet servo motor driven the quantitative pump as the power sourceof the hydraulic system, overcome the disadvantage of complex structure of traditionalhydraulic valve system, high energy consumption and high requirements on thehydraulic oil. Hydraulic power system driven by the servo motor with advantages ofcompact structure, high reliability, wide speed range, high control accuracy, goodenergy saving effect, as well as easy to achieve closed-loop control strategy. At present,PID control is still widely used, due to the strong coupling characteristics of thehydraulic system flow and pressure in the load changing, the control object is stilluncertain, time-varying and highly nonlinear, so simple PID linear controller often cannot get better control performance. Therefore, a variety of advanced control technologycombined with intelligent control applied to hydraulic system has achieved goodcontrol effect. However, due to the development of the basic theory of the variousIntelligent product is still immature, there are much points be worth to improve in theapplication of intelligent control method. Therefore, this paper designs reasonablecontrol structure combining with fuzzy logic, neural networks, genetic algorithms,particle swarm optimization algorithm, which can effectively improve the qualitycontroller,and to study the parameter optimization method. Specific work includes thefollowing:Firstly, establish the model of permanent magnet servo motor-driven dosingpumps (the hydraulic source) system, the research on permanent magnet motorphysical equation, torque equation based on the mathematical model of servo drivesystem can provides theoretical support for the subsequent chapters, then study various control algorithms.Secondly, in view of fixed parameters of genetic algorithm are easy to fall intopremature convergence and local optimum situation, genetic parameter adaptiveadjustment algorithm is proposed, that is establishing a fuzzy logic controller based oncrossover rate and mutation rate to achieve the genetic algorithm parameters adaptivelyadjustment,in order to Improve the convergence speed and optimization of the abilityof the global solution. Through the use of conventional optimization methods andimproved optimization algorithms, complete the control of hydraulic flow driven by（PMSM）.The results show that: Using proposed algorithms allows hydraulic systemachieve good control performance and strong robustness in typical operatingconditions.Thirdly, in view of the serious random interference, multi-variable, nonlinear,strong coupling, difficult to establish precise mathematical model characteristics ofhydraulic system, proposed particle swarm optimization and BP hybrid Optimizationforward Neural Network (FNN) PID control system. The control system uses aself-learning ability to adjust the PID controller parameters, using particle swarmoptimization algorithm global search ability to overcome the BP algorithm easy to fallinto local minimum, and apply it to hydraulic system, the simulation and experimentalresults verify that the system has good dynamic and static performance in a variety oftypical conditions.Fourth, a novel control scheme integrating the merits of fuzzy inference, neuralnetwork adaptation and simple PID method is presented. The parameters of thecontroller are optimized by PSO algorithm offline and error back propagation (BP)algorithm online, and a RBF network is built to identify the system online. Simulationresults of flow following at the typical working conditions of the hydraulic sourceshow that the controller and its optimization algorithm can effectively improve thesystem performance, and the system has good robustness.Fifth, on the basis of depth study of traditional PID control and fuzzy control,thereal-time online control of flow of hydraulic source is realized. Combined with thespecific conditions, analyze the characteristics of the traditional PID and fuzzy control, and conclude that fuzzy control has more robustness than PID control on the sinusoidalload conditions, and suited to the occasions processed rapid frequency changes of load.Sixth, since the PID control algorithm is simple, so most of the industrial controlstill using the traditional PID control, Although easy to implement, but there are someflaws. For example, quick response and small overshoot are difficult to achieveoptimal simultaneously. Therefore, PID control can not meet the requirements.In viewof the problems mentioned above, proposed fuzzy PID composite control strategy,combine the rapidity of fuzzy control with high precision of PID control sufficiently,and realize the real-time online control of hydraulic power source. Experimental resultsshow that composite control possess fast response, no overshoot, high accuracy, andhigh performance better than single control method, and suitable for higherrequirements occasion.