Research Of Nn Self-Adaptive Controler

The process of industrial production is sometimes nonlinear anduncertain and is difficult to establish accurate mathematic module, sousing routine PID controller is hard to achieve perfect controlling effect.Neural network (NN) has favorable nonlinear mapping performance andhigher parallel information processing capability, and it has been the mostengaging theory and method for nonlinear system modeling, recognitionand control.On the base of consulting literatures both here and abroad, themodel of NN identification, PID controller based single-neuron, PIDadaptive controller and the NN adaptive controller are discussed. Aimed atthe shortages of PID, the connection between NN and adaptive controllerare researched in order to accelerating convergence-speed and theaccuracy. This paper are based on the researching of the model,realizations and the performance of the algorithms. The main task can beconcluded as follows:(1) Aimed at the a sort of Non-linear system, the paper proposed an state observer based on the BP NN inverse-model, this model can observethe state of system in real time. And the analysis of theory and simulationshowed that the state observer is very good.(2) There have some problems in the single-neuron adaptivecontroller:①the choosing of weight coefficient. The initial value of theparameter has strong effect on the control performance②The slicingproblem of weight coefficient. when the parameter is impregnated, thestudy ability will lost.③The rise time is long, anti-jamming capability isinfirmness.In order to solve the problem, two improved method are proposed:the first is using GA to optimize the parameter, and the simulation showedthe way can find the best parameter and eliminating the effect of initialvalue. The second is a compounded adaptive PID controller based onCMAC. the study process of CMAC involved the total control process ofsystem, the simulation showed the method had the strong adaptive abilityand anti-jamming capability etc.(3) Analyzed the model, algorithm and characters of the adaptivecontroller based on BP NN. In order improve the effect on control, theappropriated model must be seted. Using the idea of NN contrary modelrecognition, the text put forward a designing scheme that NN model makes self-adaptive controller as reference and lists the designingapproach and arithmetic. It applies to any nonlinear system, so it is closerto engineering practicality. The theory analysis and emulate result provethe rationality and validity of this project.(4) Aiming at a kind of unknown, uncertain and time-variant SISOdiscrete nonlinear system, the text uses the forward model recognition forNN to the controlled object and makes the output of NN as prediction ofthe output of controlled object, and based on this the text works out thecontrolling rule and forms the project of neural self-revise control. Theresult of emulation indicates the controlling arithmetic is effective.(5) Using the idea of NN contrary model recognition, the text putforward a designing scheme that NN model makes self-adaptive controlleras reference and lists the designing approach and arithmetic. It applies toany nonlinear system, so it is closer to engineering practicality. The theoryanalysis and emulate result prove the rationality and validity of thisproject.