外文翻譯---plc變頻調(diào)速的網(wǎng)絡(luò)反饋系統(tǒng)的實(shí)現(xiàn)-plc設(shè)計(jì)-全文預(yù)覽
【正文】 t i c e t o a c h i e v e i t f u l l e c o n o mi c a n d s o c i a l b e n e f i t s In this paper, firstly the neural work inverse system method is introduced, and mathematic model of the variable frequency speedregulating system in vector control mode is presented. Then a reversible analysis of the system is performed, and the methods and steps are given in constructing NNinverse system with PLC control system. Finally, the method is verified in experiments, and pared with traditional PI control and NNinverse control. Network Inverse System Control Method The basic idea of inverse control method [6] is that: for a given system, anαth integral inverse system of the original system is created by feedback method, and bining the inverse system with original system, a kind of decoupling standardized system with linear relationship is obtained, which is named as a pseudo linear system as shown in . Subsequently, a linear closeloop regulator will be designed to 3 achieve high control mathematic model of the variable performance. Inverse system control method with the features of direct, simple and easy to understand does not like differential geometry method [7], which is discusses the problems in geometry domain. The main problem is the acquisition of the inverse model in the applications. Since nonlinear system is a plex system, and desired s t r i c t a n a l y t i c a l i n v e r s e i s v e r y obtain, even impossible. The engineering application of inverse system control doesn’t meet the expectations. As neural work has nonlinear approximate ability, especially for nonlinear plexity system, it bees with the powerful e x p e c t a t i o n s t o o l t o s o l v e t h e p r o b l e m . a ? th NN inverse system integrated inverse system with nonlinear ability of the neural work can avoid the troubles of inverse system method. Then it is possible to apply inverse control method to a plicated nonlinear system. a ? th NN inverse system method needs less system information such as the relative order of system, and it is easy to obtain the inverse model by neural work training. Cascading the NN inverse system with the original system, a pseudolinear system is pleted. Subsequently, a linear closeloop regulator will be designed. 3. Mathematic Model of Induction Motor Variable Frequency SpeedRegulating System and Its Reversibility Induction motor variable frequency speedregulating system supplied by the inverter of tracking current SPWM can be expressed by 5th order nonlinear model in dq twophase rotating coordinate. The model was simplified as a 3order nonlinear model. If the delay of inverter is neglected system original system, the model is e x p r e s s e d a s f o l l o w s : (1) 4 where denotes synchronous angle frequency, and is rotate speed. are s ta tor’s c urre nt, a nd are rotor’s fl ux li nka ge i n (d,q)axis. is number of poles. is mutual inductance, and is rotor’s inductance. J is moment of inertia. is rotor’s time constant, and is l o a d y nc hr o no us a n gl e fr e q ue nc y to r q ue . I n v e c to r mo d e , t he n Substituted it into formula (1), then (2) Taking reversibility analyses of forum (2), then The state variables are chosen as follows Input variables are Taking the derivative on output in formula(4), then (5) (6) Then the Jacobi matrix is Realization of Neural Network Inverse System with PLC 5 (7)
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