Flight Environment Simulation Volume (FESV) is the most important part of Altitude Ground Test Facilities (AGTF). It’s temperature and pressure control precision determines the level of test ability of AGTF. Therefore, in order to study the temperature and pressure control problem of FESV and improve the modeling precision of FESV, the energy equation and gas state equation are used to deduce the temperature and pressure differential equations of FESV. Meanwhile, the heat transfer influence of FESV has been taken into account in this paper and the transient heat conduction of FESV is established by using a discretizing method. The temperature and pressure differential equations of FESV are linearized around a balance point and the uncertainty of actuators has been considered in multiplicative uncertainty. The augmented system of linear model of FESV and the actuators are obtained. For the sake of making the controller design and weighting function choice more easily, a normalization method is used to normalize the augmented system. For the purpose of achieving the temperature and pressure synchronic control of FESV, a two-degree-of-freedom integral type μ synthesis control design method is proposed. What’s more, for guaranteeing the designed μ synthesis controller has servo tracking and disturbance attenuation performance, the performance weighting functions are designed according to the frequency division weighting principle and the control weighting functions are designed by using the principle of low frequency free limit, medium frequency gradually increase the limit, and high frequency maximum limit. The MATLAB Robust Control Toolbox function dksyn is used to design the μ controller.
In order to verify the effectiveness of designed μ controller, we assume two types of engine test conditions. The simulation results show, for the engine test condition one, the biggest relative tracking error of temperature is less than 0.5% and the relative steady state error of pressure is less than 0.1% and the relative tracking error of pressure slope signal is less than 3%. For the engine test condition two, the relative steady state error of temperature is less than 0.1% and the relative tracking error of temperature slope signal is less than 1%. To verify the advantage of designed μ controller, we designed a PID controller and compared the simulation results with μ controller. The comparison results showed that the designed μ controller provided better performance than the PID controller.
Position Tracking of ML System using CSA Based PID Controller
