Fuzzy PID control of motor speed

1、 Content abstract

Research and development of intelligent motor controller for electric coach
435- Can communicate 、 consulting 、 Answering question

2、 Content description

With the rapid development of national economy and automobile industry , Cars have become a common means of transportation , And driving skills have become a necessary ability , Therefore, the demand for driving school coach cars is increasing . On the other hand , Traditional fuel vehicles face the dual problems of environment and energy , In addition, the characteristics of the low-speed running condition of the coach car , It will emit more car exhaust , Therefore, the research, development and use of zero emission electric training vehicle is imperative .

According to the characteristics of the coach car , Compare the control characteristics of ordinary electric vehicles , Determine the layout of the driving system of the electric coach , According to the working requirements of the drive motor , Compare the types of motors, the key components in the drive train , Select the model of drive motor and introduce the principle of motor speed regulation , Complete the structural design of the power system of the electric training car . Then according to the functional requirements of the controller of the training car , Choose Freescale microcontroller to complete the design of motor controller hardware circuit , It mainly includes the minimum system circuit , Power circuit , Input and output signal processing circuit and motor drive circuit , Provide hardware support for software programming . take PID Combined with fuzzy control, a fuzzy adaptive PID controller , Realize and optimize the closed-loop control process of motor speed , stay SIMULINK Establish the controller model and simulate the speed change process . Last , Formulate the control strategy of electric coach , According to the control strategy, formulate the main program and the flow chart of each module , Realize the start of the vehicle 、 Idle speed 、 Accelerated operation condition , The motor 、 The protection of the controller and the function of simulating the clutch operation of the fuel vehicle , Complete the preparation of the program . And the designed controller function is tested through experiments , Verify the feasibility and rationality of the control process and Algorithm .

It turns out that , The controller can realize the starting of the electric training car 、 Idle speed 、 Speed up 、 Slow down 、 The hardware protection function can also simulate the parking phenomenon caused by improper clutch operation during the starting process of the fuel trainer , Meet the control requirements of electric trainer .

key word ： Electric coach car ; Motor controller ; Fuzzy adaptive PID control ;SIMULINK modeling

DC motor has stable performance 、 Good speed regulation , It has been widely recognized and applied in engineering practice , The improvement of DC motor control algorithm has increasingly become the focus of research , From traditional thyristor rectifier motor technology to classic and modern control , Then to intelligent control , Control theory and technology have been quite perfect and are booming . Motor control mainly adopts conventional PID control technology , It is the oldest and longest used control strategy in motor control , It has simple control algorithm 、 Low error rate and strong stability , Its usage has accounted for the total amount of industrial control 90% The above proportion [37]. besides , There are various control strategies based on PID Intelligent control strategy , Such as expert system 、 neural network 、 The fuzzy logic 、 Grey system theory, etc , And PID Integrate and derive all kinds of intelligence PID Class controller , Greatly improved the tradition PID Control performance [38].

In this paper, we use fuzzy adaptive PID Control algorithm , It's with tradition PID The algorithm is compared with , The nonlinearity of the controlled object 、 Time varying and uncertainty have good control effect , And there is no need to establish an accurate mathematical model of the control process , Weak dependence on mathematical model . So combine the two , Make the system have PID Advantages of high control accuracy , There is also strong strain of fuzzy control .

Because the vehicle dynamics system has great nonlinearity , Its parameter changes make a single proportion 、 integral 、 Differential control is difficult to meet fast response 、 High precision requirements , Therefore, fuzzy control rules are introduced to improve the robustness of the system .
4.2.1 Introduction to fuzzy logic control

Fuzzy logic control (Fuzzy Logic Control), Based on human experience . In the process of dealing with affairs , Different complex processes can be controlled by experience , If you can sum up these experiences one by one in words , We can get a qualitative but not precise control rule , Then it is quantitatively converted into fuzzy control algorithm by mathematical method , Then the fuzzy control theory can be formed [39].
Fuzzy control theory uses fuzzy language variables 、 Based on fuzzy set theory and fuzzy logic reasoning , Simulate human brain
Approximate reasoning and decision-making process . It is characterized by ：
(1) Although the fuzzy control theory algorithm uses the fuzzy set theory algorithm , But the control rules are quantitative 、 Definite conditional statement [40].
(2) Fuzzy control theory does not need to establish an accurate mathematical model of the controlled object , Establishing an accurate mathematical model is very difficult for some systems , It's not even possible .
(3) Different from other control theories , The core of fuzzy control is behavior rule base . Because the rules of natural language expression are closer to people's way of thinking and reasoning habits , It is convenient for users to understand and apply , Get more effective control effect .
(4) From the perspective of software writing , Fuzzy control theory is actually a software controller composed of a series of conditional statements .
Through the operation of fuzzy logic , The computer can process ambiguous data and information like the human brain , Decision making and process control .

3、 Simulation analysis

4、 Reference paper

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