文献翻译英文AMR[1][1].418-420.1756.pdf

Design of Temperature Control System Based on Fuzzy PID Jianwei Li1,a, Cunfu Yan2,b , Jun Liu1,c 1Mechanical fuzzy PID; intelligent control; system design Abstract. To adjust temperature as the requirement of process curve, an intelligent control system of temperature was designed. In the system, the fuzzy rule was used to adjust parameters of PID controller. Adjusted PID controller was used to control the change of temperature. The system can avoid the disadvantages of common PID, such as, long setting time, wide overshoot, and acquire better control characteristic. It were expatiated that principle and method of control. The hardware structure and the software flow chart were also introduced. Introduction Temperature is one of the most important parameters to be controlled, in the metallurgical industry and mechanical engineering. In different applications, the demand of the precision and speed of temperature control is also different. In some applications, the requirement of control is very simple, only need control Boolean variable. But, in more applications, the temperature should be adjusted as the requirement of process curve. In the latter, it is necessary to real time measure and control the temperature. Computer control is popular used in the temperature real-time control, in which, for the outstanding advantage of low cost, single chip processor is used more widely 1,2. The method of PID is used widely in the temperature control system. But in practice, many engineering system have characteristics, such as great delay lag, strong coupling and time varying, PID control cant achieve famous result. If fuzzy control was used with PID, the control system should work well. An intelligent temperature control system based on fuzzy PID controller was designed in this paper. Principle of Fuzzy PID Temperature Controller The method of PID is used widely in the temperature control system, for its outstanding advantages. There are three basic control laws in PID control, proportional control, integral control and derivative control. The function of each control law is different. Every basic control law not only can be used solely, but also can be used combined. In PID control, three control laws are used combined. So PID control has advantages of three basic control laws. The characteristic of control system could be improved with PID, such as steady-state behavior, dynamic performance and stability. In digital system, PID algorithm has two expressions: P(k) = P(k-1) + KPE(k) - E(k-1) + KIE(k) + KDE(k) 2E(k-1)+E(k-2) . (1) P(k) = P(k) - P(k-1) = KPE(k) - E(k-1) + KIE(k) + KDE(k) 2E(k-1)+E(k-2) . (2) In above equations, E(k) is the deviation of the kth sample, P(k) is the output of PID at the kth sample, KP is the proportionality coefficient, KI is the integration coefficient, KD is the differential coefficient. Equation (1) obtains the absolute value, named as PID position control algorithm. Equation (2) named as incremental algorithm. Because large abrupt change is not allowed in manufacture process, equation (2) is widely used in digital PID algorithm. Advanced Materials Research Vols. 418-420 (2012) pp 1756-1759 Online available since 2011/Dec/06 at (2012) Trans Tech Publications, Switzerland doi:10.4028/ All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of TTP, . (ID: 218.29.136.11-07/12/11,11:23:41) But in practice, many engineering system have such characteristic as great delay lag, strong coupling and time varying. There are several disadvantages, such as long setting time, wide overshoot, and not easy to confirm coefficients of PID, if only common PID control is used. To acquire better control characteristic, fuzzy theory was used to adjust the coefficient of PID real time in our work. The adjust method is as shown with equation (3). In which, is the adjust coefficient of proportionality coefficient, is the adjust coefficient of integration coefficient, is the adjust coefficient of differential coefficient, KP is the adjusted proportionality coefficient, KI is the adjusted integration coefficient, KD is the adjusted differential coefficient. KP is the adjusted proportionality coefficient, KI is the adjusted integration coefficient, KD is the adjusted differential coefficient. KP = KP + E; KI = KI +E; KP = KP +E. (3) To adjust three coefficients real time, it is necessary to build three one-to-one fuzzy systems. We only depict the foundation process of one fuzzy system below 3,4. Deviation (E) and difference deviation (DE) were selected as input value of fuzzy system. According to every input value, PB, PM, PS, ZO, NS, NM, and NB were included in fuzzy set. shape curve was selected as membership function, which associated with given fuzzy set mapped an input value to its appropriate membership value. Adjust coefficient of one PID coefficient was selected as the output value. Fuzzy set of which also contained seven variable, such as PB, PM, PS, ZO, NS, NM, and NB. The output membership function was Gaussian. Centre of gravity method was used as inverse fuzzy method. As the core of fuzzy system, fuzzy rules were used to formulate the conditional statements that comprise fuzzy logic. Each rule was designed with experts knowledge. The design principle of rules is that: If the absolute value of E is big, adjust coefficient should aims at decrease the deviation as soon as possible. To accelerate response speed, KP should be biggish; to avoid differential supersaturation, KD should be lesser; to avoid biggish overshoot and integral supersaturation, KI should be zero in usual. If the absolute value of E is middle, it is necessary to comprehensive use E and DE to change adjust coefficient, to increase or decrease the intension of PID control accordingly, avoid or decrease the overshoot and oscillation. If the absolute value of E is small, the coefficient of PID should be steady. Fuzzy rules as shown in table 1. Table 1 Fuzzy rules Difference deviation (DE) NB NM NS ZO PS PM PB Deviation (E) NB NB NB NB NB NM NS ZO NM NB NB NM NM NS ZO ZO NS NB NM NM NS ZO ZO PS ZO NM NS NS ZO PS PS PM PS NS ZO ZO PS PM PM PB PM ZO ZO PS PM PM PB PB PB ZO PS PM PB PB PB PB System hardware structure Fuzzy PID controller can be realized in many ways. Special fuzzy logical chip and develop tools can be used as the platform, advantage of which is high precision and fast speed, disadvantage of which is high cost and less mobility. The other method used widely is use single chip processor as hardware platform, the outstanding advantage of which is low cost. For the reason of cost, single chip processor was used as hardware platform of the system. Advanced Materials Research Vols. 418-4201757 C8051F series single chip processors have compatible micro processor with core and instruction set of MCS-51 5. They not only has standard external device of 8051, but also integrated more device. Analog module device, which is often used in data acquisition and control system, and other digital external device are included. C8051F series is SoC with true capability of work independently. Analog and digital external device can be managed effectively. To save energy, one or more external device can be closed. The flash memory has the ability of afresh program, it not only can be used as program memory, but also can be used as date memory. Compared with traditional MCS-51, the performance of C8051F has been enhanced greatly, and the operation speed of C8051F also has been quickened greatly. Considering actual demand of fuzzy PID controller, C8051F020 single chip processor was selected as the core of controller. The hardware structure of system is as shown in figure 1. Being A/D converter and D/A converter have been integrated in single chip, and they can satisfy the actual demand, no external A/D and D/A converter were used. Front end circuit including preamplifier and filter, was used to amplify the signal of temperature sensor, and filter the noise in signal. Output control circuit functioned as amplify, isolate and matching with action element. Action element realized the function of energy conversion, convert electrical energy to mechanical energy, and then drive the control device. PDIUSBD11 is interface chip of USB, which cooperated with SMBus in C8051F020, realized the function of USB interface. By PDIUSBD11, controller system can exchange data and information with portable memory. Then functions of saving data of temperature, exporting data of temperature, and adjusting parameters of control can be realized. Fig. 1 The hardware structure of the system To obtain friendly man-machine interaction, keyboard, liquid crystal display device, micro-printer, buzzer and indicator light were used in the system. Six function keys, number keys (0-9), negative sign and decimal point key were included in specially designed keyboard. Through the keyboard, user can modify data and set parameters. Liquid crystal display device function as real time monitor. By monitor and keyboard, the function of man-machine interaction was realized. Micro-printer was used to print the temperature curves and control records. Buzzer and indicator light would alarm when temperature exceeds the predeterminded range. System software design The design idea of modularization was used in system software design. Software system was divided into four modules by function. Temperature signal acquisition module. A/D converter of C8051F020 was used to convert analog to digital quantity. And the noise in signal was filtered with digital filter. Control module of output. According to sample data and setting value of user, fuzzy PID algorithms produce output values. These values were converted into analog by D/A converter in C8051F020. Data exchange module. Through interface chip PDIUSBD11, data could be exchanged between C8051F020 and portable memory. 1758Materials Processing Technology Man-machine interaction module. In this module, four sorts of program were included. That is, keyboard handle program, LCD driver program, printer driver program, buzzer and indicator light handle programs. There are close contact in four modules. They achieve functions demanded by system, through cooperation. Monitoring task was realized by watch dog in C8051F020. There are two algorithms on realizing fuzzy system by single chip processor. One named look-up table technique; another is compute value on line. In first method, a table was predeterminated and was saved in single chip, in which the parameters of fuzzy system were all included. When working, according to the instance, look up the table and select appropriate record value to use in control. In second method, computing input values and output v