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.     

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.     

A Study on Human Simulation Intelligent Control Algorithm to a Category of Objects

Based on the model of Human Simulation Intelligent Controller (HSIC) presented briefly, a detailed algorithm was described for the servo system control by using the method of HSIC. Simulation results obtained proves the good performance of the control algorithm.     

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.     

Throttle dynamic coordinated control strategy of ISG type medium-HEV

The system efficiency of ISG (integrated starter/generator)type medium hybrid electric vehicle (HEV)is optimized by combining transient and global optimization method under given driving mode,and energy management strategy of the hybrid system is optimized to reach the highest hybrid system efficiency. In order to avoid dynamic fuel increasing caused by engine throttle mutation during driving mode shifting or acceleration,closed-loop control of inertia moment of engine and compensation control of motor torque are adopted to coordinate the medium hybrid system to suppress over fuel injection of the ICE caused by engine throttle mutation. Model of medium hybrid electric vehicle is built and simulation is carried out. The results show that the throttle coordinated control can improve fuel economy,under the condition of guaranteed dynamic performance.     

The main loop and servo loop structure control strategy of ESC

Aiming at the control of electronic stability control system(ESC)which can enhance the handling stability in limited condition,the hierarchical control structure control strategy of ESC including main loop and servo loop is proposed. The first order sliding mode control is used in the main loop and the sliding mode plane and control law are designed. The output of main loop is the accessional yaw moment. The nine points with five states control which can approximately simulate human thinking is used in the servo loop. The brake pressure is controlled by the servo loop aiming at the desired slip rate and the accessional yaw moment is generated by brake force. The driver in the loop simulation bench is designed and the online test of the control strategy is carried on. The test results indicate that the handling stability and active safety are enhanced remarkably by the ESC control strategy in the drive condition of low adhesion road and driver handling vehicles immoderately,and the testing facticity and the pertinency of developed control strategy are improved by the driver in the loop simulation.     

Analysis on Control Strategy for a Kind of Uncertain Complexity System

In practical industrial fields, it is very difficult to control uncertain complexity object effectively, because there are various uncertainties from internal dynamic characteristic and external, surroundings disturbance for controlled object. Its complexity is not only shown in structure, but also in information relation, so it is uneasy to implement it on technology. Aimed at selecting puzzle of control strategy for uncertain complexity system control, the authors describe cybernetics model based on analysis on some kinds of control strategy and contrastive research, and the model is applied in physical engineering system successfully. Finally, the authors point out that intelligent control strategy should be selected for uncertain complexity system control, and that Human Simulation Intelligent Control is a wise choice.     

Sliding mode control of robot with dynamic friction and dead zone compensation using fuzzy logic and neural network

Aiming to solve the problem of nonlinear uncertainties LuGre dynamic friction and non-symmetric dead zone in the robot,this paper presents a sliding mode robust robot control algorithm,compensates for the uncertainties of robot manipulator respectively LuGre dynamic friction with fuzzy radial base function (RBF)neural network and asymmetrical dead zone with fuzzy logic,trains parameters of nonlinear dynamic friction and asymmetrical dead zone real-timely and adaptively,to achieve an accurate reproduction of the actual robot system,and proves the Lyapunov stability of the algorithm. The simulation of a two-degree-of-freedom robot manipulator proves that the algorithm improves the trajectory tracking accuracy,the control torque stability and friction torque stability of the robot. Meanwhile,it is found that control moment pulse compensation error,rhombus attractor in the kinetic properties of the friction model of robot manipulator,and lacking of dead zone compensation cause nonlinear kinetic phenomena,such as limit cycle oscillation of control system. And the estimation of ε in the dead zone inverse model plays a decisive role in the accuracy of the system.     

Application of multi-dimension parallel genetic algorithm to energy-saving optimum control of trains in following operation

In order to study the energy-saving optimum control strategy of a leading train and a tracing train in following operation under a moving block system,an energy-saving control model of trains is created. The aims of the model are energy consumption and trip time error. The control variables of this model are the operating handle level and the train’s position when the operating handle level is changed. Based on the model,the static and dynamic speed restraints are put forward. The static speed restraints are defined by the line conditions and the dynamic speed restraints of the tracing train caused by the leading train for the sake of safety. This problem is solved with the help of multi-dimension parallel genetic algorithm (GA) and external punishment function. During the solving process,the crossover probability and the mutation probability are adjusted dynamically according to the GA generation to improve the efficiency of the coarse grain search and the fine grain search. Ramps divided into three parts and the real number coding are adopted to shorten the length of chromosomes and improve the speed of convergence. Its correctness and effectiveness are validated at a simulation platform of train operation.     

Growing and pruning dynamic recurrent fuzzy neural network optimal control on firing rate to feed water ratio for supercritical unit

By analyzing a certain once through boiler’s FR/FW control system,a new control scheme based on growing and pruning dynamic recurrent fuzzy neural network (GAP-DRFNN)is proposed. This GAP-DRFNN can synthetically study main relative state parameters about FR/FW control,so as to calculate the optimal FR/FW by using least temperature deviation value of outlet of moisture separator as its training signal. As the data of current main relative state parameters input,GAP-DRFNN through structure learning can automatically increase and pruning neurons,and adjust the parameters and the recurrent weight of neural network dynamically based on stochastic gradient descent algorithm. The experimental results show the good performance for the system in variable conditions and this scheme’s celerity and precise on FR/FW control,it has better quality than traditional PID control method.     

A kind of Expert Control Combined with the Supervisory Theory for Discrete Event Dynamic Systems

To overcome the shortages of the supervisory theory for Discrete Event Dynamic Systems,a kind of expert control combined with the supervisory theory is proposed,also a practical example is given to illustrate its effectiveness.     

A control system for vehicle applications of high-blend methanol gasoline

The ordinary gasoline engines could not be fueled by high-blend methanol directly. A MCU-based high-blend methanol gasoline control system is designed to extend the injection pulse width. PROTEUS simulation and test bench are validated. Flyer M-TCE engines burning M85 go smoothly. The results indicate that the high-blend methanol gasoline control system caneffectively control the engine injection mass without changing the original Electronic Control Unit , and make it feasible to apply high-blend methanol gasoline to the ordinary gasoline engines.