Based On Adaptive Fuzzy Algorithm For Brushless Dc Motor Controller Design And Development

Because of the advantages of no excitations, simple structure, high reliability and good speed performance, Brushless DC motor (BLDCM) has been widely used in various fields. At present, many experts and scholars studying in the brushless DC motor control are with a view to exploit the full advantages of BLDCM. In the motor control algorithm area, the strategy researchers are mainly depends on are fuzzy control, adaptive control, neural network control, and so on.Fuzzy control, which is based on fuzzy set theory, fuzzy linguistic variables and fuzzy logic, is one important computer mathematic, and is a kind of non-linear controls. Fuzzy control is playing an important role in intelligent control and becoming more and more effective. It shows enormous strength during fuzzy control integrates with some disciplines such as neural network control, genetic s and theory. Given the superiority of fuzzy control performances in modern control, this paper presents adaptive fuzzy algorithm that the adaptive algorithm is integrated in the fuzzy algorithm. Besides, a brushless DC motor controller which owns a DSP core is devised by this paper, and the motor can look forward to better the static and dynamic characteristics.First, BLDC motor's development condition and the research situation are introduced. In order to have a clear understanding on control for BLDC motor, the working principles of BLDCM are described in detail, so is the motor mathematical model. This paper will be mainly focus on motor control by using fuzzy algorithm, therefore the fuzzy algorithm are presented as well. Since it is difficult to build a precise mathematical model for BLDCM, it's quite bad when using mathematical model through Matlab/Simulink directly. Thus, at the motor controller design stage, HWIL simulation technology is adopted. After a brief introduction for the dSPACE HWIL simulation system characteristics, the mathematical models of each of the drive controller modules are constituted, and the adaptive fuzzy control algorithm is tested by dSPACE simulation system.Next, a brushless DC motor controller is designed by this paper. As the hardware module, power inverter circuit, position sensors, power supply systems, as well as speed calculation module are decrypted particularly. And the components of software system, composed of main program process, interrupt service routine process and control algorithm design on, are explained clearly. In order to test the effectiveness of adaptive fuzzy algorithm, a 1.1kw BLDC motor is taken as an experiment object to show the control performance. The PID control algorithm is compared with adaptive fuzzy algorithm at the motor start-up phase and the load mutations phase. Both the speed overshot, overshot-time, as well as overshoot recovery time are all keep records in detail.Finally, the experimental results confirmed the adaptive fuzzy control algorithm is feasible by comparing with traditionally PID algorithm. At the same time, the use of HWIL simulation technology on design a control algorithm would gain a high enthusiasm.