Research on the positioning control of asynchronous motor - fuzzy controller

 (1) to determine the fuzzy controller input variables and output variables (2) design control rules of fuzzy controller (3) establish the blurred with the fuzzy method (4) select the fuzzy controller input variable and output variable in the theory field and determine the parameters of the fuzzy controller (quantitative factor and scaling factor) (5) the preparation of the application of fuzzy control algorithm (6) the rational selection of sampling time fuzzy control algorithm electric vehicle motor Generally use a two-dimensional fuzzy controller to the change of the error and error as input variables, to control the change of the quantity of output. The design of the fuzzy control rules generally includes: choose the word set of input/output variables, define a fuzzy variable fuzzy subsets and establish the control rules of fuzzy controller. The word set input and output variables, as a general rule, be {NB, NM, NS, NO, PO, PS, PM, PB}. Fuzzy variables of the fuzzy subset is to determine the shape of membership function of fuzzy ac electric motor subset. General use normal distribution. Control rules available conditional statements describe, that is, If A and B, Then C, Then control rules table is established. 


Blur is the accurate quantity into fuzzy quantity, can use formula: Y = 12 X (a + b) / 2 / (b - a) accurate quantity is the actual range [a, b]. The output of the fuzzy control is a fuzzy quantity, it cannot directly control the controlled object, needs to be converted into precise volume. There are three methods: (1) selection of maximum membership degree method. The method is simple, less but the use of information; (2) take the median method; (3) the weighted average decision method, the use of information, but the large amount of calculation. Controller of the control algorithm can be written as if E = A (I) then EC = B (j) then U = C (ij) (I = 1, 2, 3,... m; j = 1, 2, 3,..., n) based on the sampling error, error change, can calculate the corresponding control quantity changes, to all the X, Y all the elements in the entire portfolio to calculate the corresponding control quantity change, U can be written as matrix (ij) (n * m) will be made table electricalmotor1.blogspot.com matrix, as A lookup table, to be stored in memory. After the real-time control, based on the fuzzy quantitative error value and error changes of look-up table directly, then set the scaling factor can be as the output to control the controlled object.