Song Yongxian

A Fuzzy-PID Control System of PTFE Sintering Furnace Based on Lonworks

This note introduces an industrial control system which adopts fuzzy-PID and Lonworks. According to the character of a class of time-delay and great inertia first-order system, we chose a combined-control strategy that On-off control or Fuzzy-control or PID control strategy were selected automatically, so accurate control to the four PTFE (Polytetrafluoro-ethylene) molding furnace sintering process such as sintering temperature, sintering time, cooling speed etc were achieved. App effect shows, temperature control precision is 0.5%, initial tracking error, maximum exceed error and final error are 2.5, 2.0 and 2.0 Celsius respectively. It proves that the combined-control system is better than the singularity structural such as PID or Fuzzy in fleetness and robustness and steady-state precision.

A Control Method of Dual Buck Half Bridge Inverter Based on the Phase of Voltage Loop Output

In this paper, a novel hysteresis current control method based on the phase of the output of voltage loop by using a single LEM current sensor is proposed. Because of having two filter inductors, the Dual Buck Half Bridge Inverter has on bridge arm shoot-through problem. Each inductor current can be independently controlled, so the power switches and the free wheeling diodes can be optimally chosen, and the efficiency of the inverter will be increased. So the inverter can promise high practical value in the engineering application. Finally, the control method is verified by simulation and experimental results.

Design of Electric Power Parameter Monitoring System Based on DSP and CPLD

In this article, we introduce a set of online power quality monitor who is based on DSP (Digital Signal Processor). The monitor makes full use of DSP chips strong operation capability. It can monitor power quality online, display real-time measure data and save super scalar data, which can provide accurate data to power quality evaluation and improvement. On the hardware side, the system takes DSP and CPLD as core of power parameter detection circuit, and complex programmable logic device (CPLD) and phase-locked loop (PLL) as synchronous sampling circuit, TO the software, designed relative software arithmetic. At the same time, the main program of electric power parameter detection was introduced. Experiments show the proposed system is of fast response, high accuracy, and real-time processing.

Nonlinear System Control Based on Multi-step Predicted and Neural Network Inverse

A multi-layer forward neural network acted as the inverse controller, which was trained with predictive optimization algorithm to compensate for disturbances and uncertain plant nonlinearities, and reverse control based on neural network is implemented in complicated non-linear system. The weights of neural network inverse control were trained by multi-step predictive index function, thereby the system has the character of predictive control. The method has faster dynamic speed than general neural network inverse control, and has better performance of the response. The simulation results have shown the effectiveness of this method.

Inverse System Decoupling Control for Induction Motor Based on Neural Network On-Line Learning

The induction motor is a MIMO, nonlinear and high coupling system. The reversibility of the induction motor is testified. Consequently, a pseudo-linear system is completed by constructing a neural network inverse (NNI) system and combining it with the motor system. The inverse can transform the MIMO nonlinear system into two SISO linear subsystems (i.e., rotor speed and flux subsystems). In order to approach the inversion exactly in operation of the motor, the control method online learning based on NNI system is proposed, in which connection value can be amended continuously on-line to make the NN adapt to the changes of environment to strengthen its robustness. Experiment results have shown that NN can be adjusted in the control process. The good applicability of NN along with the strong stability and robustness of the system can be achieved by using the proposed method.