Automatic Equipment Design of Intelligent Manufacturing Flexible Production Line Based on Industrial Motorized Spindle

Based on the previous research on the production line automation, this paper carries out further research and further design and development on the basis of the original production line automation equipment. In this paper, the overall design of the automatic production line is carried out, and the various systems in the automatic production line are optimized, and the backward instruments are eliminated, and then some more advanced and convenient instruments are applied. Then, the hardware and software of the automatic production line are studied respectively, and the human-computer interaction module and real-time main control circuit module are re developed, and the electric shaft is applied to the automatic production line. Finally, the fuzzy PID controller of the stepping motor is designed. The experiment shows that the fuzzy PID control scheme is better than the traditional PID control scheme. After the rationalization of the system, the quality robustness of proactive planning is improved obviously. Then, the temperature of motorized spindle was tested.

Design and robustness analysis of fuzzy PID controller for automatic voltage regulator system using genetic algorithm

In this paper, a Fuzzy proportional–integral–derivative (Fuzzy PID) controller design is presented to improve the automatic voltage regulator (AVR) transient characteristics and increase the robustness of the AVR. Fuzzy PID controller parameters are determined by a genetic algorithm (GA)-based optimization method using a novel multi-objective function. The multi-objective function, which is important for tuning the controller parameters, obtains the optimal solution using the Integrated Time multiplied Absolute Error (ITAE) criterion and the peak value of the output response. The proposed method is tested on two AVR models with different parameters and compared with studies in the literature. It is observed that the proposed method improves the AVR transient response properties and is also robust to parameter changes.

Pipeline Leak Detection and Estimation Using Fuzzy PID Observer

A pipe is a ubiquitous product in the industries that is used to convey liquids, gases, or solids suspended in a liquid, e.g., a slurry, from one location to another. Both internal and external cracking can result in structural failure of the industrial piping system and possibly decrease the service life of the equipment. The chaos and complexity associated with the uncertain behaviour inherent in pipeline systems lead to difficulty in detection and localisation of leaks in real time. The timely detection of leakage is important in order to reduce the loss rate and serious environmental consequences. The objective of this paper is to propose a new leak detection method based on an autoregressive with exogenous input (ARX) Laguerre fuzzy proportional-integral-derivative (PID) observation system. The objective of this paper is to propose a new leak detection method based on an autoregressive with exogenous input (ARX) Laguerre fuzzy proportional-integral-derivative (PID) observation system. In this work, the ARX–Laguerre model has been used to generate better performance in the presence of uncertainty. According to the results, the proposed technique can detect leaks accurately and effectively.

Adaptive Fuzzy Neural Network PID Algorithm for BLDCM Speed Control System

Because of its simple structure, high efficiency, low noise, and high reliability, the brushless direct current motor (BLDCM) has an irreplaceable role compared with other types of motors in many aspects. The traditional proportional integral derivative (PID) control algorithm has been widely used in practical engineering because of its simple structure and convenient adjustment, but it has many shortcomings in control accuracy and other aspects. Therefore, in this paper, a fuzzy single neuron neural network (FSNNN) PID algorithm based on an automatic speed regulator (ASR) is designed and applied to a BLDCM control system. This paper introduces a BLDCM mathematical model and its control system and designs an FSNNN PID algorithm that takes speed deviation e at different sampling times as inputs of a neural network to adjust the PID parameters, and then it uses a fuzzy system to adjust gain K of the neural network. In addition, the frequency domain stability of a double closed loop PID control system is analyzed, and the control effect of traditional PID, fuzzy PID, and FSNNN PID algorithms are compared by setting different reference speeds, as well as the change rules of three-phase current, back electromotive force (EMF), electromagnetic torque, and rotor angle position. Finally, results show that a motor controlled by the FSNNN PID algorithm has certain superiority compared with traditional PID and fuzzy PID algorithms and also has better control effects.

Research and Application of Precision Fertilizer Application Algorithm Based on PSO Optimized Fuzzy PID Control

In irrigation’s process and fertilizer application in production of agriculture, the accuracy of fertilizer application and water maintains at a relatively low level, which results in waste of soil slabbing and resources. In this research, a fuzzy PID algorithm based on PSO optimization is designed to control the fertilizer application process and irrigation of the fertilizer applicator. Firstly, a mathematical model of the fertilizer applicator is established according to the relevant modules and corresponding parameters. Based on the MATLAB/Simulink platform, the PID controller, the fuzzy PID controller and the controller proposed in this article are constructed respectively, which can be applied to the established transfer functions. The simulation outcomes demonstrate that the response time of the control algorithm proposed in this research is shortened to 30s, compared to fuzzy PID and PID, which is 62.5% and 50% shorter respectively, and the overshoot of the control algorithm in this article is nearly 0 of apart from the early oscillation. In order to verify the algorithm’s reliability in practical application, this research designs groups of different pressure for the accuracy control test, the test consequences illustrate that the fuzzy PID control based on PSO optimization has excellent control effect under each pressure. The control accuracy is concentrated at around 2%, while PID control maintains around 20% and fuzzy PID control distributed at 10%.The results show that the control algorithm proposed in this research enhances the irrigation accuracy in the practical application process.