Cheng Qiming

The study of single-phase PWM rectifier based on PR control strategy

Synchronous PI controller is usually used to track current in three-phase PWM rectifier with zero steady-state error which is difficult to achieve in the single-phase system. A novel proportional-resonant (PR) control scheme for single-phase PWM rectifier is proposed in the paper. Compared with traditional PI control and current hystereis control (CHC) methods, the PR control structure is simple and can reduce control time delay significantly. The simulation results verify the feasibility of the proposed control scheme in the disturbance rejection. In addition, sinusoidal current zero static error control can be achieved without a coordinate transformation and the DC voltage can automatically adjust to changes of grid voltage, load value and frequency which contributes to energy conversion and bidirectional flow of electricity.

Application of UPFC Based on Improved Double-loop Decoupling PI Control in Photovoltaic Systems

The mutation of solar irradiance can cause the output power of photovoltaic power plant to mutate, and it takes great changes to active power and reactive power which feed into the power grid. When the system security constraint is exceeded, the photovoltaic power plant will stop running. In this paper, the structure and the mathematical model of large grid-connected photovoltaic power plant are introduced, then an improved double loop PI decoupling control system is proposed based on the d-q model of UPFC parallel converter. On the basis of traditional PI control, DC load current is directly used as feed-forward control in the control system of capacitor voltage. It is not only easy to get feedback, but also conducive to design and operate the series controller and the parallel controller independently. Finally, this paper sets up a Simulink model of UPFC in the environment of Matlab/Simulink after analyzing its principle. And then, this model was applied into a three-phase system to observe its influences to power quality. The simulation results show that this control system based on the UPFC can effectively control the voltage and the power flow, maintain bus voltage and reduce reactive exchange. It can also improve the active photovoltaic power transmission, as well as maintaining the stability of the system.

The Forward NN-PID Controllers Based on Chaos PSO-BP Hybrid Optimization Algorithms for Decoupling Control System of Ball Mill

As to the multi-variable, close coupling, nonlinear and time-varying characteristics of the ball mill pulverizing system, the forward NN-PID controller based on chaos PSO-BP hybrid optimization algorithms for decoupling control system of ball mill was proposed. In this controller, the control parameters of PID controller are adaptively adjusted by forward NN, the weights of NN are optimized by the mixed learning methods integrating the offline PSO algorithm combined with chaos strategies of global searching ability, with the online BP algorithm of local searching ability. The results of simulation of Matlab/Simulink show that the hybrid optimization algorithms could solve some problems effectively, such as BP algorithm or PSO algorithm with slow convergence rate and falling to partial minimum easily, and the new control method has better quality than the traditional PID decoupling control method, it has fast tracking ability, strong robustness, good decoupling ability, and it can solve the time-varying problem and the coupling problem of ball mill effectively.

Model-Free Adaptive Control Method for Nuclear Steam Generator Water Level

Nuclear steam generator is a highly complex, nonlinear, non-minimum phase and time-varying system, which is caused by the swell and shrink effects. So the control of the steam generator water level is very difficult. Conventional double PI control method can not reach a good performance. There are many methodologies applied to water level controller design. But many methodologies are model based, as we all known, model-based methods cannot offer a satisfactory control for steam generator water level since the system is very complex. In this paper, Model-Free Adaptive Control (MFAC) is applied for the steam generator water level control. The MFAC has received much attention as a powerful tool for the control of industrial process systems. Simulation results show the effectiveness and the good performance of the method.

The hierarchical fuzzy-PID control for ball mill pulverizing system

As to the multi-variable, strong coupling, nonlinear, time-varying characteristics of the ball mill pulverizing system of power plant, a hierarchical fuzzy-PID control system is introduced in this paper based on the fuzzy control theory and the analysis of its dynamic characteristic, and the simulation results are also presented in this article. The simulation results show that the control method of this paper has better quality than the traditional control method, it has fast tracking ability, strong robustness, good decoupling ability, and it can effectively solve the time-varying problem, coupling problem etc.

Design and Implement of Responder Based on Freescale HCS12 Single Chip Microcomputer

An 8-channel responder based on Freescale HCS12 single chip microcomputer is designed. The responder can display the number of the first player correctly. It also can count the scores and show the player with the highest score. The system includes four modules: CPU12, the SCI serial communication, digital display tube and timer. When competition signal input, it is been caught and then cause interruption, the timer is used to time accurately, the serial port is used to send and receive the start answer signal, judgment signal and other signals, the digital display tube is used to show the scores of the current player. LCD display tube shows subjects and answers. So the basic functions of the responder are achieved.

Simulation Study on Model Free Adaptive Control Based on Grey Prediction in Ball Mill Load System

The load object of ball mill in thermal power plant has complex traits that are large time-delay, slow time-varying, strongly nonlinear, etc. It is difficult to obtain satisfactory control performance using conventional control methods. The model-free adaptive control method based on grey prediction was introduced to control ball mill load in this paper. This method combined the adaptive, anti-interference features of model-free control with the time-delay prediction, overshoot suppression, rapid stability of grey prediction model, the measured output value of load object was replaced by the predicted result of grey model, then, the model free adaptive control was used for close-loop control. The simulation results show that the control method has fast response, small overshoot, good robustness, strong anti-interference ability, it can effectively solve the large time-delay, nonlinear and adaptive problems.

The control system of GA-BP fuzzy neural network controller and Elman network identifier

The fuzzy controller with neural network is proposed in this paper, this system consists of a fuzzy neural network controller and a model identification network, the fuzzy neural network controller is optimized by the offline genetic algorithm of global searching ability, and the online BP algorithm ability of local searching. The detailed control algorithm is given, the algorithm of system identification based on modified Elman network is ratiocinated. The simulation result shows the feasibility and validity of the proposed method.