Papers by Keyword: Temperature Control System

Abstract: Due to the complexity of the heat transfer for heating furnace, some characteristics are caused such as big inertia, great lag. In the temperature control system for heating furnace, the traditional PID controller can not get satisfactory effect, that dynamic is instability and control accuracy is bad, which is very detrimental to the system to achieve optimum efficiency. A fractional order PI^λD^μ controller based on particle swarm optimization method was designed, at the same time compared with PID control. Simulation results show that, fractional order PI^λD^μ control based on particle swarm optimization has better convergence stability, faster response times and higher accuracy value. Fractional order PI^λD^μ controller has better dynamic performance, compared with traditional PID controller, greatly improves the quality control system.

Abstract: According to the characteristics of temperature intelligent control, the automatic temperature control system is designed and analyzed based on PLC. Through the requirement of the control function, electric control circuit is researched, and hardware is selected. According to the programming language, the main program is designed to satisfy the intelligent control which can keep the temperature in specially appointed rang. The design process provides some guidance for the development of the intelligent control with PLC.

Abstract: The fuzzy PID controller is almost realized by single chip microcomputer software, its real-time and anti-jamming are poor. This artical uses FPGA as the core controller and adopts the idea of modules, a fuzzy PID temperature controller is designed and achieved. Actual operating result shows that this method can significantly improve the control effect, simplify the design, but also can improve the real-time and anti-jamming capability of the system.

Abstract: A rapid learning algorithm was put forward to realize complex system modeling and self-adaptive control with uncertainty, high nonlinear and lame time-delay. Merits of internal model control were combined, such as simple design, food regulation capacity, high robustness and the ability to eliminate the unknown disturbance to construct a internal model control system based on wavelets neural network, which was characterized by high robustness and quick response speed and then it can brim food control performance when controlled objects vary in a wide range. Finally, it was triumphantly used in simulation of the superheated steam temperature reduction control system of 500 MW unit and food performances are obtained.

Abstract: The system uses DS18B20 as a temperature sensor to collect temperature data on spot, uses ZigBee as wireless transmission module, and uses C8051F020, a single chip as a processor. The temperature control module issues instructions to achieve real-time control of the indoor temperature so as to control the temperature under established standard. The system can effectively reduce energy consumption.

Abstract: In order to study the nonlinear viscoelasticity of polymer melts at high shear rate, multi-function and all-electric rheometer (MAR) was designed by the authors. Development of temperature control system of MAR is important because rheological behavior of polymer melts is affected by temperature significantly. The design principle of the temperature control system of MAR was studied. According to the temperature upper limit the barrel need to reach, and the power the heating system can offer to maintain the temperature, the suitable type of heating system was determined. Considering the requirement of heater and the measurement error, the suitable type of temperature transducer was determined. The measured values of temperature were compared with the set values of them to evaluate the temperature control error of MAR. The results show that the temperature fluctuation is smaller than ±0.4°C in 3.5 minute. Therefore, the temperature control error of MAR is small enough for rheological test. And the temperature control stability of MAR is very well.

Abstract: s: Polymer mixing is the key process of rubber products manufacturing, and mixer is the core equipment in polymer mixing process. By analysis of the effective factors on mixer mixing temperature, this paper study realization method of temperature control system. A polymer temperature control system using tandem mixing technology is designed to improve the mixing efficiency and the quality.

Abstract: Using fuzzy neural network to tune PID parameters, and DSP as processor, it was designed that a set of electric boiler temperature control system based on PID parameters self-tuning, including the design of each hardware module and each software subroutine of the system. Experimental results show that compared with the traditional PID temperature control system, this temperature control system has the advantages such as good control effect, easy parameter adjustment, strong anti-jamming capability, better adaptability and robustness, has the feasibility and practical value.

Abstract: A temperature control system based on thermoelectric coolers is designed in this paper for infrared CCD camera used to monitor burden surface of blast-furnace. The thermoelectric cooling system consists of a microcontroller module, a temperature sensor, a CCD camera, a thermoelectric cooler, a power amplifier and isolation module. The CCD camera with a temperature sensor is tightly mounted on the TEC cold surface. The microcontroller changes duty ratio of PWM signals with changes of the camera temperature to make working temperature of the CCD camera constant. The experiments show that the cooling system works well in temperature controlling

Abstract: The technologic of PID control is very conventional. There is an extensive application in many fields at present. The PID controller is simple in structure, strong in robustness, and can be understood easily. Then neural networks have great capability in solving complex mathematical problems since they have been proven to approximate any continuous function as accurately as possible. Hence, it has received considerable attention in the field of process control. Due to the complication of modern industrial process and the increase of nonlinearity, time-varying and uncertainty of the practical production processes, the conventional PID controller can no longer meet our requirement. This paper introduces the theoretical foundation of the BP neural network and studying algorithm of the neural network briefly, and designs the PID temperature control system and simulation model based on BP neural network.