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Aiming at the problem that it is difficult to confirm the parameters of the PID controller and the parameters can not be changed once identified, an intelligent PID control method is proposed. According to the size of the system error, this algorithm controls the system with different subsections of different parameters, by using the particle swarm optimization (PSO) to optimize the parameters of...
The heat exchange of distilled water unit is a very complex process.The main steam pressure and temperature are tightly coupled with the pressure of raw water, temperature and flow in the circuit, and show non-linear relationship. There are two important parameters need to be controlled in water production process: conductivity and temperature of distilled water at the exit. This is a typical double...
Temperature is a very important parameter in industrial production. Based on Fuzzy PID controller structure and study algorithm, fuzzy PID controller can be used in actual industrial processes on Kingview movement platform by using PLC technology. The results show that PID parameters can be adjusted on line by control strategy configuration, and the effect meets the need in temperature control experiments.
In order to improve tracking accuracy of the servo system, an adaptive inverse controller with PID feedforward is designed. It is based on the time-delay characteristic of the adaptive inverse control when training. The controller can realize accurately tracking of the servo, so as to meet the working need of the system. Finally, the tracking simulation is carried out on the digital servo experimental...
Neutralizing pH value of sugar cane juice is the important craft in the control process in the clarifying process of sugar cane juice, which is the important factor to influence output and the quality of white sugar. On the one hand, it is an important content to control the neutralized pH value within a required range, which has the vital significance for acquiring high quality purified juice, reducing...
The paper presents a neural network based predictive control (NPC) strategy to control nonlinear chemical process or system. Multilayer perceptron neural network (MLP) is chosen to represent a Nonlinear autoregressive with exogenous signal (NARX) model of a nonlinear process. Based on the identified neural model, a generalized predictive control (GPC) algorithm is implemented to control the composition...
In this paper, we present a machining time estimation algorithm for five-axis high-speed machining. and propose an algorithm based on five-axis machine behavior in order to predict machining time more exactly. first, it is needed to investigate the operational characteristics of five-axis machines. Then, we defined some dominant factors, including feed angle that is an independent variable for machining...
In this work we present an approach that uses a neural net for an online control of the cooling process in light metal die casting industry. Normally the die casting process is controlled manually or semi-manually, and quality control is done well after the cooling process. In our approach we increase the product quality during the production process by monitoring the cooling process with an infra...
In this paper, data mining technology is adopted to find correlations from massive production data to predict burning through point (BTP) of sintering process. A hybrid BTP prediction model is presented which is based on artificial neural network and multi-linear regression error compensation algorithm. In this model, the final prediction result is calculated based on both the prediction value from...
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