Simulating Human Intelligent Fuzzy Control to the Throttle Actuator of AMT

This paper discusses the idea and design procedures of applying the fuzzy controller with simulating human intelligent control to throttle actuator of automobile engine of AMT. It is presented that the structure of electronic-controlled hydraulic throttle actuator, the composition of the control system, the control algorithms and the experiment results of the fuzzy controller with simulating human intelligent control. The experiment results and the application show that applying fuzzy controller with simulating human intelligent control to the electronic-controlled hydraulic throttle actuator can ensure the fast response, the stability and the higher control precision and meet the requirements of the actual application.     

THE CHARACTERISTICS OF FUZZY AND ADAPTIVE PI COORDINATE DECISION CONTROLLER

On the basis of analysing problems of conventional fuzzy controller in the design of the structure and algorithm, this paper puts forward a kind of control algorithm that is fuzzy and Adaptive PI coordinate decision controller (FACDC) . It adopts the hierarchial control structure imitating intelligent control and combines fuzzy controller and adaptive PI controller. It takes full advantage of two controllers. Since the algorithm of FACDC in model reference fuzzy adaptive algorithm, it avoids the complexity of conventional adaptive algorithm.     

Intelligent Control to the Automatic Cruise System of AMT Vehicle

A dual closed-loop automatic cruise control system is proposed according to the properties of the AMT system with cruise control function inside, which is developod by the authors. The human simulated intelligent fuzzy control is applied to the inner loop of throttle position control while the conventional fuzzy control is applied to the outer loop of vehicle speed control. The scheme of the whole control system and the design process of the controller are presented. The experimental results show that with the proposed dual closed-loop control system, the unstable phenomena of engine speed can be eliminated and the throttle control responses fast without buffeting. Moreover, the system has the advantages of easy manipulation and reliable operation. The controller has the advantages of free of accurate mathematical model and easy to carry out and high robust and so on.     

Improvement Methods of Fuzzy Control with Intelligent Integration

Fuzzy controller can achieve satisfactory dynamic performance even for complicated process without mathematical model of the process.Its main imperfection is the existence of steady state error and ultimate oscillatory in the process output. This limits its application area. How to eliminate the steady state error while keep its good dynamic performance has been paid much attention. The strategy to introduce integral function to the conventional fuzzy control system is put forward in this paper to overcome the above problem. After expound two key factors on introducing integral action,an intelligent integral algorithm has been employed,and two methods on introduction of the intelligent integral to the fuzzy control system are proposed. Their characteristics and applied situations are summarized.     

Intelligent Sliding-mode Control of Switched Reluctance Motor

Base finite element solution for the calculations of flux and torque of Switched Reluctance Motor, the state equation of SRM is thus educed. In addition, according to the fact that it is difficult to attain the ideal effect with the regulatory linear control method because of the double salient pole SRM structure of stator and rotor, fuzzy control is proposed and used in the sliding mode control to form a intelligent sliding mode control. We emphasize the introduction of the design method of the intelligent sliding mode control and present the control diagram. The simulation results show that the method of intelligent sliding mode Variable Structure Control is simple, with good dynamic performance and robust property.     

Fuzzy Control and Simulation of Regulating System for Permanent Magnet Synchronous Motor

This paper researches the fuzzy control and simulation of regulating system for PMSM in electrical vehicle. The mathematics model is set up.The PMSM,the PMSM measures demux, dq to abc converter and the three phrase PWM converter models are set up in MATLAB/ Simulink. The fuzzy controller is designed with two dimension fuzzy design method, and take E and EC as input variable, U is the output variable. According to the controller and models, the fuzzy control model of regulating system for PMSM is created in matlab/simulink. At last, to test the accuracy of the control method with the simulation result.     

A NEW SELF-TUNING PID CONTROL ALGORITHM BASED ON PROCESS PARMETER IDENTIFICATION

In this paper,the open loop response curve is computed by a computer after the process paramter estimatio The parameters of PI or PID controller are computed by the method of respose curve. Then in order to obtain better control performance, the parameters of PI or PID controller are gradually optimized.This algorithm is with wider application range compared with the other self-tuning PID control algorithms. The computer simulation and real-time control trials shows a good result.     

An Expert System Approach to the Computer Aided Design of Intelligent Controllers

The idea for an expert system approach to the computer aided design of intelligent controllers (ESCAD1C) is discussed and the idea of two step modelling of an intelligent controller is presented on the basis of emulating human control behaviours to solve complex problems. The structure, functions and characteristics of ESCADTC system , and the design procedures of intelligent controllers are gived. The knowledge base and simulating functions for designing intelligent controllers are also described.     

Research on Fuzzy Control Based Two-level Handstand Pendulum System

The two-level handstand pendulum system based on fuzzy control is designed. It is impossible to adopt classical control theory, for the mathematical modeling of the system is nonlinear, the fuzzy control is proposed to improve the former linear control algorithms. For the key to fuzzy control is control rule, it becomes most important to design suitable fuzzy rules. Two methods, one based on experience and the other based on system simulation, are presented to set u Pan effective rule base. The practice proves that the control result is of well stability. A control example for two-level handstand pendulum system shows that the control law is efficient and more robust than the classical state feedback optimal control law with respect to errors produced by the external disturbances.     

The Algorithm of Pole-Assignment Self Tuning Robust Control

An control algorithm with goed robustness has been developed,based on the combination of poletassignment self- tuning control algorithm with robust estimation and control al-gorithms,while the input signal and process parameters are varied on a large scale. The design of controller based on presented algorithm is simple,with good robustness for parameter changes and a strong ability for overcoming determined disturbance.The simulating research results proved the ef-fectiveness of the pole- assienment self-tuning robust control algorithm.     

Intelligent Control of the Nonlinear Seismic Response of a 3 Story Benchmark Building

Intelligent materials, control devices and intelligent control algorithm research and development in recent years have opened a new world for seismic resistance and disaster reduction in civil engineering. We designed and fabricated a new piezoelectric friction damper. In our research, we regarded the piezoelectric friction damper as the control device. We proposed a fuzzy control algorithm for reducing nonlinear seismic response of a 3 story benchmark building and established the interactive relationships between structural responses and fuzzifier factors, defuzzifier factor. A numerical simulation is carried out to analyze the nonlinear seismic responses of the controlled 3 story benchmark building. The simulation results are compared to those of other control strategies. The results show that the fuzzy control can reduce the nonlinear seismic response of 3 story benchmark building and minimize the structural damage caused by strong earthquakes.     

Research of UD2UU with human simulated intelligent control for a double inverted pendulum

Double pendulum has four equilibrium points (down down, down up, up down, and up up). Twelve transfer actions and eight spin actions can be formed with these equilibrium points. One of the transfer action, up down to up up (UD2UU) with human simulated intelligent control (HSIC) theory based on sensor motor intelligent schema is studied. Control system designed by HSIC has following advantages: hierarchic control architecture with multi controller and multi control mode; hybrid control law combining close loop and open loop control as well as positive feedback and negative feedback control; associating schema based on characteristic model which takes charge of switch between each control mode. The design process of HSIC controller for UD2UU is discussed. The real time control results demonstrate the validation of the proposed theory and method.     

One Auto-optimized Fuzzy Control of Car-engines Based on GA

One new auto-optimized fuzzy control model of car-engines based on genetic arithmetic was introduced aiming at the problem that the parameters of car-engine are of the discreteness, the nonlinear and the uncertain characteristics, with which it is difficult to control accurately the excess air coefficient and the spark advance angle in dynamic procedure when using a conventional control model. The rule of the design scheme of the controller achieving the model based on embedded operating system is discussed. Further more, it is probed that the fuzzy control parameters are optimized automatically using GA based on on-line real-time simulation. The results of experiments show that the dynamic indexes and the fuel economy indexes are all improved greatly and the advantage of the model on reducing fuel consumption is obvious.     

Temperature Fuzzy PID Control for Variable Air Volume System

Fuzzy PID controller was applied in variable air volume system. The task was to control the temperature of supply air and the temperature of air conditioned room (the return air temperature) close to their respective targets. The fuzzy PID control system of supply air temperature and return air temperature was designed respectively. The supply air temperature was controlled through adjusting the valve opening of chilled water. And the indoor temperature was controlled through adjusting the rotational speed of variable frequency ventilator. The supply air temperature and the indoor temperature (return air temperature) were controlled online by fuzzy PID controller. Thus, it was shown that the design of fuzzy PID controller was reasonable and the effect of fuzzy PID control was well.     

温室环境参数智能控制系统的设计

依据温室控制要求,介绍了模糊控制技术在温室控制系统中的应用,给出了模糊控制器的实现过程。实践表明,该控制器具有良好的控制效果。     

Fuzzy Control Strategy and Simulation for ISG-Type Hybrid Electric Vehicles

Fuzzy control strategy is used to study the fuel economy of ISG-Type hybrid electric vehicle with CVT.Based on the instantaneous state of vehicle,the fuzzy logic controller is built aiming to get minimum fuel consumption.In order to avoid the subjective factor,the control rules are established with the optimized results from the sequence quadratic programming(SQP) method.Through the second development of ADVISOR,the simulation for ISG hybrid electric vehicle at different cycles has been accomplished.The results show that the fuzzy logic control strategy is efficient in improving the fuel economy of hybrid electric vehicle.     

AN EXPERT CONTROLLER BASED ON PREDICTOR ALGORITHM

This paper presents a new method of expert controller, which is gotten by means of combining the technique of expert system with predictor control. The method adopts the multimode control as well as on-line characteristic identification so that the controller could not only give full play to the expert' s experience but also reflect the accuracy of predictor algorithm in control process. The simulation shows that the method has strong Robustness and good adaptability even when the object varies or the load changes suddenly, or something unexpected happenes with the system.     

The Research and Simulation of the Fuzzy-PID Control System for Ball Mill Pulverizing of Power Plant

This paper focuses on the main problems in the operation control for ball mill pulverizing system, proposes the dynamic mathematical model for the steel ball mill pulverizing system , simulates and analyzes the dynamic character of the system. A Fuzzy-PID controller with on-line self-tuning parameters based on fuzzy control technology is proposed .The simulation results show that the Fuzzy-PID control system can improve the controlling effect and the ability of suppressing disturbances.     

Human Simulated Intelligence Motion Control for Three-link Acrobot on Horizontal Bar

The design of multi-controller and multi-mode control law is presented for the three-link Acrobot on horizontal bar by employing Human simulated intelligent control method based on sensory-motor Schema.Imitated the characteristics of gymnast's swing-up and handstand movement,the control process of robot is divided by six sequence phase.Then the sensory cell and motor cell and the group of sensory-motor schema is designed based on the analysis of quality-quantity combination.The simulation results show that the controller ensures the gesture and the energy to the desired goal,farther more the motion control of giant swing backword is realized in the simulation.     

PID Control for Multivariable System Based on Ameliorative RBF Neural Networks

Aiming at systems which are of characteristics of multi-input and multi-output, nonlinearity and time-variation in the industrial control fields, this paper presents a intelligent PID control method based on ameliorative RBF neural networks, which constructs RBF neural networks identifier on-line and identifies a controlled object on-line by means of adopting the nearest neighbor-clustering algorithm, and adjusts parameters of PID controller on-line and realizes decoupiing control of multivariable, nonlinear and time-variation system. The simulation result indicates that the controller can get parameters which are optimal under some control law, it makes the decoupled system, compared to the PID control method based on the conventional RBF neural networks, has perfect dynamic and static performances, possesses the advantages of high precision, quick response speed and is of great adaptability and robustness.