Hypersonic vehicle, which reveals significant values in space accessing and prompt global striking, has achieved more and more attention in the past decades. To realize a high-speed and high-quality flight performance, hypersonic vehicle takes a specific airframe-engine-integrated structure, with which strong couplings and structural flexibility disturbances will appear. Furthermore, due to the high-speed operation as well as large flight envelope, the varying atmospheric conditions and various random disturbances may significantly deteriorate the flight performance. All of the above factors make the cruise flight control design difficult and challenging.
As an extension of conventional type-1 fuzzy logic system, interval type-2 fuzzy logic system (IT2-FLS) shows a stronger capability of modeling uncertain information. Based on the universal approximation property for real continuous function, IT2-FLS has been widely applied in complex nonlinear control design.
Focusing on the control problems of the hypersonic vehicle in the cruise flight stage and taking various uncertainties into consideration, some novel adaptive control methods for hypersonic vehicle based on IT2-FLSs are investigated in this dissertation. The main contributions and highlights of this dissertation are summarized as follows:
(1) Considering the measurement noises in the output channels of the hypersonic vehicle, which is seldom investigated in the existing literature, a novel state-estimator-integrated robust adaptive control system based on IT2-FLSs is proposed. A continuous-model-based state estimator is applied to reconstruct the exact states of the velocity and altitude which are contaminated by the measurement noises, while a robust adaptive controller based on IT2-FLSs is designed to fulfil the tracking mission using the ideal state measurements. By combining the state estimator and the robust adaptive controller, the control system is finally developed. Comparative simulation results verify the effectivenss and superiority of the proposed control system on measurement noises suppression.
(2) Simultaneously taking the measurement noises in the output channels and the uncertain strong aerodynamic disturbances into consideration, a novel interval type-2 fuzzy gain adaptive state estimator together with a novel robust adaptive control system for hypersonic vehicle is further proposed. After analyzing the stability of the static gain state estimator, the contradiction between accurate and fast state reconstruction versus high-frequency measurement noise suppression is stated, and the prior control knowledge is summarized. Then, two knowledge-based IT2-FLSs are formulated to adapt the gains online, which can realize accurate and fast state reconstruction in the transition process as well as high-frequency noise suppression in the steady-state process. Comparative simulation results demonstrate the improvements of the cruise flight performances with this novel state estimator.
(3) To deal with the issue of the computation and storage costs in IT2-FLSs brought by high-quality flight objective, a novel robust adaptive control system for hypersonic vehicle based on IT2-FLSs and small gain theorem is proposed. For each uncertain subsystem in the vehicle, an IT2-TSK-FLS is adopted to approximate the unknown model information online. Moreover, a new adaptive parameter is developed to replace the original learning parameter vector, which can alleviate the computation and storage burden of the system. By applying the small gain theorem, the final control law is developed. Rigorous stability analysis shows that all the states in the closed-loop system are uniformly ultimately bounded. Comparative simulation results illustrate the robustness and superiority of this control system.
To sum up, this dissertation focuses on the real problems of hypersonic vehicle in the cruise flight stage, and aims to achieve a high-quality flight performance. Several novel adaptive control methods based on IT2-FLSs are brought out, and the results reveal great values in real engineering.