Hybrid Controller based Intelligent Speed Control of Induction Motor
presented hybrid controller combines the benefits of fuzzy logic controller and … a wide range of operation are assured through application of the vector-control…
I. INTRODUCTION
The traditional approach to building system controllers requires a prior model of the system. The quality of the model, that is, loss of precision from linearization and/or uncertainties in the system’s parameters negatively influences the quality of the resulting control. At the same time, methods of soft computing such as fuzzy logic possess non-linear mapping capabilities, do not require an analytical model and can deal with uncertainties in the system’s parameters. Although fuzzy logic deals with imprecise information, the information is processed in sound mathematical theory [1].
Based on the nature of fuzzy human thinking, Lofti Zadeh originated the “fuzzy logic” or “fuzzy set theory”, in 1965. Fuzzy logic deals with the problems that have fuzziness or vagueness. In fuzzy set theory based fuzzy logic a particular object has a degree of membership in a given set that may be anywhere in the range of 0 (completely not in the set) to 1 (completely in the set) [2]. For this reason fuzzy logic is often defined as multi-valued logic (0 to 1), compared to bi-valued Boolean logic [3].
The induction machine is an important class of electric machines which finds wide applicability as a motor in industry and in its single phase form in several domestic applications. More than 85% of industrial motors in use today are in fact induction motors [4]. It is substantially a constant speed motor with a shunt characteristic. Various methods have been developed for this purpose including direct torque control, vector control etc. But due to their peculiar
limitations none of them has been found failure-proof.
Here speed of induction motor is successfully controlled
over wide range with appreciable accuracy using fuzzy
logic controller in vector control method.
II. CONTROL PRINCIPLE
The fuzzy controller in a vector-controlled drive system is used as presented in Fig. 1. The controller observes the pattern of the speed loop error signal and correspondingly updates the output DU so that the actual speed wr matches the command speed wr*. There are two input signals to fuzzy controller, the error E = wr* – wr and the change in error, CE, which is related to the derivative dE/dt of error. In a discrete system, dE/dt = ?E/?r = CE/Ts, where CE = ?E in the sampling time Ts. with constant Ts, CE is proportional to dE/dt. The controller output DU in a vector controlled drive is ?iqs* current. This signal is summed or integrated to generate the actual control signal U or current iqs*.
A. Fuzzy Controller as P-I Controller
The fuzzy controller is basically an input/ output static non-linear mapping, the controller action can be written in the form
K1E + K2 CE = DU
Where K1 and K2 are non-linear coefficients or gain factors. Including the summation process above equation can be written as
or
which is a fuzzy P-I controller with non-linear gain
factors.
? DU = ? K Edt + ? K CEdt
u = K 1 ? Edt + K 2 E
…
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