Robust Adaptive Control Of Aerospace Vehicles Re-entry Based On Terminal Sliding Mode Control

Aerospace vehicle (ASV) is the reusable flying vehicle of next generation. The vehicle fills the blanks of spaceraft's activities in near space and has very important martial values. For the varieties of the aerosphere and the large disturbances, the design of attitude control system of ASV is a very difficult problem during the re-entry. In this dissertation, we focus on the high-precision, strong-stabilization, fast adaptive robust control of ASV re-entry.First of all, a simulation model of an ASV re-entry mode is presented based on the contributions of our lab. This model includes two kinds of actuators, the RCS and the control surface deflections, to satisfy different control tasks in the flight. Open-loop dynamics and stability characteristics demonstrate that this model is complex-nonlinear, coupling, fast time-varying, so it is able to be used in the following research works.Secondly, a discussion is devoted to the design of the control systems of ASV re-entry based on the terminal sliding mode control. Under the assumption to the totall disturbances, a terminal sliding mode control scheme with finite-time convergence is proposed. This scheme can promise that the tracking errors converge to zeros in finite time, and can improve the response speed of the closed-loop system rapidly. Then, in order to release the assumption above, an adaptive terminal sliding mode control based on neural networks is designed. The controller can compensate the totall disturbances online. After strict analysis to the stabilities, the simulation results are given to demonstrate the good performances of the controllers under the hypersonic conditions.In the following, an adaptive terminal sliding mode control method that based on the fuzzy disturbance observer (FDO) is designed, in order to eliminate the influences of the totall disturbances and be applicated easily. The stabilities of this method are proved strictly based on Lyapunov's direct method. Furthmore, by modifying the adaptive law of the FDO, a fast fuzzy disturbance observer (FFDO) is presented to improve the convergence speed of FDO. Then the FFDO is used in the design of the flight control system of ASV re-entry. The simulation results demonstrate the superiority of proposed methods.In Chapter 5, the reseach emphases are the finite-time convergence of closed-loop system and the efficiencies of the adaptive laws. The approximation errors of fuzzy systems are holded to get the explicit expression of the convergence time. Then the errors of closed-loop converge to certain arbitary small regions, not to zeroes. Another problem studied in this chapter is how to alleviate the computation burden of the computers on-vehicle. A novel adaptive law for the fuzzy systems, only two parameters are adjusted on-line, is proposed to enhance the efficiencies of the computation.In Chapter 6, after the analysis to the influences of the design parameters to the sliding mode regions and the reaching time, an adaptive time-varying terminal sliding mode control method based on T-S fuzzy model is designed. In this scheme, on one side the T-S fuzzy systems are adopted to approach the totall disturbances on-line, on the other side the time-varying sliding surfaces are benefit to enhance the sliding mode regions, improve the robusticity of closed-loop systems and abbreviate the reaching time.Finally, the design of observers is studied. After extended the system two times, a novel state-extended observer based on super-twisting is presented. It provides the observer errors can converge to zeroes in finite time under the consideration of the measured noises. Then the unkown states of ASV are estimated using the measured states and the exact differentiation. This method is simple, high-precision, and easy to be applicated.