Intelligent Control Method for Aircraft Deicing Fluidtemperature Based on a New Adaptive Smith Predictor

Abstract

During the course of industry control, pure hysteresis, time-varying，non- linear complex systems often occur. It is ineffective to solve the issues above with the traditional fuzzy control and PID control methods. Against the pure hysteresis, time-varying, non- linear characteristics of Aircraft Deicing Fluid rapid heating system, on the basis of Smith Predictor and traditional PID, a Fuzzy-PID control method is proposed based on an adaptive Smith predictor. In this way, pure hysteresis of the system will be compensated, to reduce the overshoot and enhance the stability of the system. By establishing the mathematical model of Aircraft Deicing Fluid rapid heating system and simulating for the model obtain the simulation results, which have shown that the method is effective, can improve the qualities of control and enhance the stability of temperature control system significantly

Decoupling Adaptive Smith Prediction Model of Flatness Closed-Loop Control and Its Application

“…Ignoring the slight influence of RT on the quadratic and quartic flatness, and the cascade controllers adopt proportional control, the quadratic and quartic flatness decoupling PI-adaptive Smith predictive control system shown in Figure 6 2 and ∆a * 4 are the quadratic and quartic flatness changes of the Smith predictors, and e y2 and e y4 are the deviation between the actual and predicted outputs of the quadratic and quartic flatness control loops respectively. Referring to the adaptive algorithm of primary flatness control, the adaptive algorithm of quadratic and quartic flatness control loops is obtained as shown in Equation (17) and Equation (18), respectively, in which K 2 (0) and K 4 (0) are the initial values of K 2 (t) and K 4 (t), respectively, and λ 2 , λ * 2 , λ 4 and λ * 4 are four constants greater than zero. 17) and Equation (18), respectively, in which K2(0) and K4(0) are the initial values of K2(t) and K4(t), respectively, and λ2, λ…”

“…Initially, a multivariable coupled pure time-delay system is decoupled into several generalized single variable pure time-delay systems by using the dynamic decoupling matrix. Then, for the generalized single-loop pure time-delay system, an adaptive Smith predictor is designed to solve the problem of pure time-delay, and improve the control performance when the model is mismatched [17]. In this control system, the transverse multi-point flatness is recognized as several characteristic components by pattern recognition [18], and the overall flatness is controlled by controlling the characteristic components.…”