基于自适应模糊PID的飞机客舱温度控制（英文）
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摘要
飞机客舱温度控制系统具有高度非线性、不确定的特点,传统的PID控制很难取得良好的控制效果,因此设计了自适应模糊PID控制器。采用机理建模与实验相结合的方法,确定了系统的数学模型。针对自适应模糊PID控制器参数范围变动较大,不易调节的问题,提出了一种能够很方便确定模糊PID控制器比例、积分以及微分三个参数合理范围的方法。基于专家系统设计模糊规则。利用MATLAB/SIMULINK建立了仿真模型,仿真结果表明提出的自适应模糊PID控制器在抗系统参数摄动以及不确定方面具有更好的鲁棒性。
The temperature control system is a highly nonlinear and uncertainty system, and using a conventional PID controller makes it difficult to achieve a good control effect. In this paper, a self-adaptive fuzzy PID controller is described. The model of controlled object is established by combining mechanism modeling with experiment. Aiming at the problem that the parameter range of the self-adaptive fuzzy PID controller varies greatly and is difficult to adjust, a new method is proposed which can easily provide a more reasonable fuzzy controller output variable range. The fuzzy rules based on experts' experience and knowledge are adopted. The simulation model is established using MATLAB/SIMULINK. The simulation results show that the self-adaptive fuzzy PID controller has better robust performance against system parameter changes and uncertainties.
The temperature control system is a highly nonlinear and uncertainty system, and using a conventional PID controller makes it difficult to achieve a good control effect. In this paper, a self-adaptive fuzzy PID controller is described. The model of controlled object is established by combining mechanism modeling with experiment. Aiming at the problem that the parameter range of the self-adaptive fuzzy PID controller varies greatly and is difficult to adjust, a new method is proposed which can easily provide a more reasonable fuzzy controller output variable range. The fuzzy rules based on experts' experience and knowledge are adopted. The simulation model is established using MATLAB/SIMULINK. The simulation results show that the self-adaptive fuzzy PID controller has better robust performance against system parameter changes and uncertainties.
引文
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[2]?aban?etin,Akkaya A V.Simulation and hybrid fuzzy-PID control for positioning of a hydraulic system[J].Nonlinear Dynamics(S0924-090X),2010,61(3):465-476.
[3]Jia D,You B.Study on novel plasma arc cutting technology based on PIDNN-FUZZY controller[J].International Journal of Innovative Computing Information&Control Ijicic(S1349-4198),2011,7(7):4171-4182.
[4]Li Y,Tong S,Li T.Adaptive fuzzy backstepping control design for a class of pure-feedback switched nonlinear systems[J].Nonlinear Analysis:Hybrid Systems(S1751-570X),2015,16(2):72-80.
[5]Xu Q,Kan J,Chen S,et al.Fuzzy PID Based Trajectory Tracking Control of Mobile Robot and its Simulation in Simulink[J].International Journal of Control&Automation(S2207-6387),2014,7(8):233-244.
[6]Mamdani E H.Application of fuzzy algorithms for control of simple dynamic plant[J].Proceedings of the Institution of Electrical Engineers(S0020-3270),1974,121(121):1585-1588.
[7]Bachache N,Wen J.PSO and GA designed Pareto of Fuzzy Controller in AC Motor Drive[J].International Journal of Control&Automation(S2207-6387),2013,6(5):149-158.
[8]Mugisha J C,Munyazikwiye B,Karími H R.Design of temperature control system using conventional PID and Intelligent Fuzzy Logic controller[C].International Conference on Fuzzy Theory and ITS Applications.IEEE,2016:50-55.
[9]Baghli F Z,Bakkali L E.Design and Simulation of Robot Manipulator Position Control System Based on Adaptive Fuzzy PID Controller[M].Robotics and Mechatronics.Springer International Publishing,2016:243-250.
[10]Huang H C,Xu S D,Chiang C H.Optimal Fuzzy Controller Design Using an Evolutionary Strategy-Based Particle Swarm Optimization for Redundant Wheeled Robots[J].International Journal of Fuzzy Systems(S1562-2479),2015,17(3):390-398.
[11]Yi T U.Simulation of Large-scale Aircraft Cabin Temperature Control System[J].Acta Aeronautica Et Astronautica Sinica(S1000-6893),2011,32(1):49-57.
[12]Fang D,Na F.Application and simulation of fuzzy neural network PID controller in the Aircraft cabin temperature[J].Sensors&TransducersS(S2306-8515),2013,153(6):100-104.
[13]Tu Y,Lin G P.Dynamic Simulation of Aircraft Environmental Control System Based on Flowmaster[J].Journal of AircraftS(S0021-8669),2012,48(6):2031-2041.
[14]Xie X,Long Z.Fuzzy PID Temperature Control System Design Based on Single Chip Microcomputer[J].International Journal of Online Engineering(S1861-2121),2015,11(8):29.
[15]Chiang W Y.Establishment and application of fuzzy decision rules:an empirical case of the air passenger market in Taiwan[J].International Journal of Tourism Research(S1522-1970),2011,13(5):447-456.