Self-adjusting Fuzzy Control Research Articles

Research on Pump Speed Control System Based on Fuzzy PID

In this paper, based on MATLAB/simulink, the PID vector frequency conversion control of permanent magnet synchronous motor has better drive control performance in the multi-stage centrifugal pump speed control system. The electric-hydraulic coupling system of centrifugal pump has a good evaluation and research function. In view of the low efficiency of the traditional PID control method and the poor adaptability to the change of working environment, a vector control method of permanent magnet synchronous motor based on adaptive and self-adjusting fuzzy control principle is proposed for the speed regulation system of water pump. The simulation results show that the PMSM system controlled by the fuzzy PID controller is superior to the traditional PID control, and has better disturbance resistance, dynamic and steady performance.

Design of Automatic Cable Path Detection System Using Electronic Marker

Power cable is more and more widely used. But once the cable breaks down, and the direction and location of the cable are not clear, path detection is the first step to eliminate the cable breakdown. After the information of underground cable jacking is detected by detection equipment, positioning and identification are carried out to form management files, and power pipe jacking is managed by information management mode, which can reduce the loss caused by cable jacking accident and the harm to operation and maintenance. In this paper, the cable path detection, cable short-circuit point positioning and electronic marker are integrated. The cable path automatic detection system is designed by using the single-chip fuzzy controller. The self-adjusting fuzzy control scheme is proposed and the hardware and software design of the system is given.

Application of the Self-Adjusting Fuzzy Control in Water System of Central Air-Conditioner for Saving Energy

Central air conditioning system with multi variable, nonlinear, time-varying, large time-delay characteristics using the traditional control strategy is difficult to control and good energy saving effect. For these features of central air conditioning system, self-adjustment fuzzy controller is studied based on the fuzzy controller. The simulation can be seen, the self-adjustment fuzzy controller has a faster response speed and smaller steady-state error, while there is a certain adaptive capacity. Its control performance is superior to conventional control strategies and conventional fuzzy controller. Central air-conditioning system uses the parameter self-adjusting fuzzy controller strategy combined with inverter technology. According to load changes, central air conditioning water system can automatically real-timely control the pumps to ensure that the comfort of central air-conditioning provided a significant reduction in energy consumption.

Research on the Application of Intelligent Decoupling Control Method in the Process Control System

There is a universal coupling in process control system, especially with the development of science and technology, industry system has became more and more big, the control process is more complicated, the variables which need to solve are also gradually increased. Therefore between the variables in the associated process produce coupling. In order to solve the coupling problems, we introduced PI self-adjusting fuzzy control model in the link of decoupling, and designed the model and the algorithm of decoupling with decoupling controller. The experiment showed that, after the introduction of PI algorithm, the time when the system reaches a steady is greatly reduced, saving time and cost. Also there is no coupling between the two signals, which shows that PI algorithm successfully reaches the decoupling in the process control.

High Precision Prediction of Rolling Force Based on Fuzzy and Nerve Method for Cold Tandem Mill

The rolling force model for cold tandem mill was put forward by using the Elman dynamic recursive network method, based on the actual measured data. Furthermore, a good assumption is put forward, which brings a full universe of discourse self-adjusting factor fuzzy control, closed-loop adjusting, based on error feedback and expertise into a rolling force prediction model, to modify prediction outputs and improve prediction precision and robustness. The simulated results indicate that the method is highly effective and the prediction precision is better than that of the traditional method. Predicted relative error is less than ±4%, so the prediction is high precise for the cold tandem mill.

Improvement in machining performance of die-sinking EDM by using self-adjusting fuzzy control

Recently, in order to increase the autonomy of machines, the knowledge engineering is being applied widely in the field of the electrical machining. The fuzzy control is known well as one of the most effective ways for the knowledge engineering to maintain the stability of the non-deterministic machining such as die-sinking EDM [Int. J. Mach. Tools Manuf. 43 (13) (2003) 1287; J. Mater. Process. Technol. 129 (1–3) (2002) 45; Modern Mach. Shop 70 (7) (1997) 262; IEEE Trans. Automatic Control 35 (2) (1990) 148; Modern Mach. Shop 66 (5) (1993) 130]. Even the fuzzy control is powerful, the ability of the machine would never grow as long as the fuzzy rules are fixed. This investigation was carried out to examine the validities of a self-adjusting fuzzy control on die-sinking EDM. The stability of machining could be calculated properly by using a simplified fuzzy inference with only two input signals such as a frequency of short circuit and a frequency of arcing. And by controlling the jump heights and the approaching movement of the tool electrode according to the calculated stability, a remarkable improvement in machining speed and the maximum depth of cut was achieved.

Improvement in machining performance of die-sinking EDM by using self-adjusting fuzzy control

Recently, in order to increase the autonomy of machines, the knowledge engineering is being applied widely in the field of the electrical machining. The fuzzy control is known well as one of the most effective ways for the knowledge engineering to maintain the stability of the non-deterministic machining such as die-sinking EDM [Int. J. Mach. Tools Manuf. 43 (13) (2003) 1287; J. Mater. Process. Technol. 129 (1–3) (2002) 45; Modern Mach. Shop 70 (7) (1997) 262; IEEE Trans. Automatic Control 35 (2) (1990) 148; Modern Mach. Shop 66 (5) (1993) 130]. Even the fuzzy control is powerful, the ability of the machine would never grow as long as the fuzzy rules are fixed. This investigation was carried out to examine the validities of a self-adjusting fuzzy control on die-sinking EDM. The stability of machining could be calculated properly by using a simplified fuzzy inference with only two input signals such as a frequency of short circuit and a frequency of arcing. And by controlling the jump heights and the approaching movement of the tool electrode according to the calculated stability, a remarkable improvement in machining speed and the maximum depth of cut was achieved.