In rolling mill, the accuracy and quality of the strip exit thickness are very important factors. To realize high accuracy in the strip exit thickness, the Automatic Gauge Control (AGC) system is used. Because of roll...In rolling mill, the accuracy and quality of the strip exit thickness are very important factors. To realize high accuracy in the strip exit thickness, the Automatic Gauge Control (AGC) system is used. Because of roll eccentricity in backup rolls, the exit thickness deviates periodically. In this paper, we design PI controller in outer loop for the strip exit thickness while PD controller is used in inner loop for the work roll actuator position. Also, in order to reduce the periodic thickness deviation, we propose roll eccentricity compensation by using Fuzzy Neural Network with online tuning. Simulink model for the overall system has been implemented using MATLAB/SIMULINK software. The simulation results show the effectiveness of the proposed control.展开更多
In recent day’s power distribution system is distress from acute power quality issues.In this work,for compensating Power Quality(PQ)disturbances a seven level cascaded H-bridge inverter is implemented in distributio...In recent day’s power distribution system is distress from acute power quality issues.In this work,for compensating Power Quality(PQ)disturbances a seven level cascaded H-bridge inverter is implemented in distribution static com-pensator which protects power quality problems in currents.Distribution Static Compensator(DSTATCOM)aid to enhances power factor and removes total har-monic distortion which is drawn from non-linear load.The D–Q reference theory based hysteresis current controller is employed to generate reference current for compensation of harmonics and reactive power,additionally Probabilistic Neural Network(PNN)classifier is used which easily separates exact harmonics.In the meantime fuzzy logic controller is also used to maintain capacitor DC-link poten-tial.When comparing to PI controller it decreases steady state time and reduces maximum peak overshoot.Cascaded H-bridge multilevel inverter converts direct current to Alternating current,through inductor opposite harmonics are injected in Power Control Centre reduces source current harmonics and reactive power.The implementation of CHBMLI in distribution STATic COMpensator simulation model is simulated by means of MATLAB.展开更多
Based on detailed study on several kinds of fuzzy neural networks, we propose a novel compensationbased recurrent fuzzy neural network （CRFNN） by adding recurrent element and compensatory element to the conventional...Based on detailed study on several kinds of fuzzy neural networks, we propose a novel compensationbased recurrent fuzzy neural network （CRFNN） by adding recurrent element and compensatory element to the conventional fuzzy neural network. Then, we propose a sequential learning method for the structure identification of the CRFNN in order to confirm the fuzzy rules and their correlative parameters effectively. Furthermore, we improve the BP algorithm based on the characteristics of the proposed CRFNN to train the network. By modeling the typical nonlinear systems, we draw the conclusion that the proposed CRFNN has excellent dynamic response and strong learning ability.展开更多
文摘In rolling mill, the accuracy and quality of the strip exit thickness are very important factors. To realize high accuracy in the strip exit thickness, the Automatic Gauge Control (AGC) system is used. Because of roll eccentricity in backup rolls, the exit thickness deviates periodically. In this paper, we design PI controller in outer loop for the strip exit thickness while PD controller is used in inner loop for the work roll actuator position. Also, in order to reduce the periodic thickness deviation, we propose roll eccentricity compensation by using Fuzzy Neural Network with online tuning. Simulink model for the overall system has been implemented using MATLAB/SIMULINK software. The simulation results show the effectiveness of the proposed control.
文摘In recent day’s power distribution system is distress from acute power quality issues.In this work,for compensating Power Quality(PQ)disturbances a seven level cascaded H-bridge inverter is implemented in distribution static com-pensator which protects power quality problems in currents.Distribution Static Compensator(DSTATCOM)aid to enhances power factor and removes total har-monic distortion which is drawn from non-linear load.The D–Q reference theory based hysteresis current controller is employed to generate reference current for compensation of harmonics and reactive power,additionally Probabilistic Neural Network(PNN)classifier is used which easily separates exact harmonics.In the meantime fuzzy logic controller is also used to maintain capacitor DC-link poten-tial.When comparing to PI controller it decreases steady state time and reduces maximum peak overshoot.Cascaded H-bridge multilevel inverter converts direct current to Alternating current,through inductor opposite harmonics are injected in Power Control Centre reduces source current harmonics and reactive power.The implementation of CHBMLI in distribution STATic COMpensator simulation model is simulated by means of MATLAB.
基金Supported by the National High-Tech Research and Development Program of China (Grant No. 2006AA05A107)Special Fund of JiangsuProvince for Technology Transfer (Grant No. BA2007008)
文摘Based on detailed study on several kinds of fuzzy neural networks, we propose a novel compensationbased recurrent fuzzy neural network （CRFNN） by adding recurrent element and compensatory element to the conventional fuzzy neural network. Then, we propose a sequential learning method for the structure identification of the CRFNN in order to confirm the fuzzy rules and their correlative parameters effectively. Furthermore, we improve the BP algorithm based on the characteristics of the proposed CRFNN to train the network. By modeling the typical nonlinear systems, we draw the conclusion that the proposed CRFNN has excellent dynamic response and strong learning ability.
