No abstract

Flow simulation subsystem of ground simulation test for aircraft fuel system aims to simulate fuel flow of engine. In a certain airplane fuel system, the flow scope is very broad. In order to ensure the control precision in the whole range, the method of subsection control and measuring has been put forward. A control algorithm based on fuzzy adaptive PID with two-degree of freedom has been adopted, since subsection control will bring out the switchover fluctuation phenomenon. The results of simulation show that this algorithm can realize the curve tracking of the wide-range flow and reduce the fluctuation in the flow switchover process. That is to say, this algorithm has a preferable control effect.

For a class of non-matching uncertain nonlinear system such as stratospheric balloon-borne gondola azimuth control system, a new robust adaptive multiple sliding mode controller is proposed. In this control method, the virtual and the practical control variables are obtained by designing the multiple sliding modes step-by-step. For avoiding the chattering problem generated by discontinuous input, the traditional sign function is replaced by hyperbolic tangent function. Meanwhile, the CMAC neural network is used to approximate the system uncertainties and the derivative of virtual control input online, which can reduce the conservation of controller parameters design. The system stability analyses show that the control method can guarantee that the output tracking error and slide modes asymptotically convergent to boundary layer. The simulation results show that the controller has higher tracking accuracy, and stronger robust to nonlinear and uncertainty of system, and it also can be applied to other similar non-matching uncertain nonlinear systems.