The Study On Intelligent Control Strategy In The Applications Of Two Industrial Systems

At present, in the industrial process control, most of the controlled objects become more and more maximization, continuous, non-linearization, complication in order to meet the growing technological requirements. Most of these complicated processes can be approximated as a first-order model with dead time. To find a precise and efficient control strategy is a hot research content of domestic and foreign experts. This thesis is based on the existing science and technology projects, and does some researches on time delay inertial system.Temperature control is an important part of printing and dyeing industry.According to the transition curve acquisition and processing of dye vat, we know that temperature control process of dyeing is a big inertia and small time delay object; also it is a multi-disturbances, uncertain and time-varying complex process. The main difficult problem of temperature control of dyeing is the contradiction between rapid response and overshoot. In order to develop a temperature control algorithm with high adaptability and strong robustness, in this article, we adopt some updated PID control strategy, included integral separation PID control, improved differential PID control, nonlinear PID and Human-simulating Intelligent PID Control. And then the simulation study and analysis of these control methods are taken. The results showed that intelligent PID control strategy has great research value and application prospect.The coagulant dosing system of Water Works is a typical time-delay process. According to our observations and experimentally study in the water plant,we know that, the coagulant dosage dosing system of water factory is a non-linear and time-variant process with a large time constant and large dead time, it is always difficult to control.And many advanced control method at present can't be true for the actual control. Then, PID controller which based on internal model control can set the system using only one adjustable parameter. And the parameter direct related to the response speed of closed loop and the robustness of loop. The MIC-PID controller is better to conventional PID controller in noise immunity and complexity.It controller can greatly improve the control results and be easy to be controled by the engineers and technicians. When adding the MIC-PID controller to the coagulant dosage dosing system of water factory can obtain a better control effect. Also, this paper brings forward a new technique which bases on MFA, and applies it to water supply works in the pilot-plant test to control water turbidity. It compares the 3 methods control effect: pure feedback control technology, feed forward and feedback control technology in the experiment. The result is that the third one can obtain a better control effect and it can make a steady turbidity of effluent (control accuracy of±0.35).this can completely meet to the process requirement.The study on the Intelligent Control of Coagulant Dosing water plants can save the manpower, the dosage of drugs in the water treatment process, reduce production costs and increase productivity. So, in order to decrease the production cost more comprehensive, we do some optimal control on the whole system of water plant. The study on optimal control strategy of the large inertia and large time delay system is based on water treatment processes of water plant. Taken together every techniques for water treatment, mathematics pattern and constraint condition are established. The resources should be allocated rationally and a higher production efficiency should be achieved after using particle swarm optimization (PSO).So, An improved Particle Swarm Optimization (IPSO) is proposed in this paper, according to the problem of the standard Particle Swarm Optimization (SPSO) algorithm, in which the inertia factor w decreases with time increases, resulting in the reduction of the convergence rate in the search later and thus a lower convergence performance of the algorithm. In the new algorithm, the linear function of the inertia factor w is changed to an exponential function which base on'e'. The optimization results show a faster convergence and higher efficiency in IPSO. The study on the algorithm provided a good reference value for the follow-up work of this project.