Abstract
Optimal performance is extremely important for hypersonic flight control. Different from most existing methodologies, which only consider basic control performance including stability, robustness, and transient performance, this article deals with the design of nearly optimal tracking controllers for hypersonic flight vehicles (HFVs). First, main controllers are developed for the velocity subsystem and the altitude subsystem of HFVs via concise fuzzy approximations. Then, optimal controllers are nearly implemented utilizing single-network adaptive critic design. Moreover, the stability of closed-loop systems and the convergence of optimal controllers are theoretically proved. Finally, compared simulation results are given to verify the superiority. The special contribution is the application of a low-complex control structure owing to the critic-only network and advanced learning laws developed for fuzzy approximations, which is expected to guarantee satisfied real-time performance.
Highlights
H YPERSONIC flight vehicles (HFVs) have potential to serve as long-range transports and carriers of rapid and accurate attack weapons [1]–[5]
For an arbitrarily unknown function, we can obtain a lowcomputational approximation by directly turning ||ζf ||2 instead of its elements. This is very significant for hypersonic flight vehicles (HFVs) to guarantee their control systems with excellent real-time performance
The control real-time performance cannot meet the requirement of hypersonic flight control if we use fuzzy formulation (8) to develop critic networks. We give another form of fuzzy approximations, called fuzzy Hyperbolic model (FHM) [37], to construct the critic network subsequently
Summary
H YPERSONIC flight vehicles (HFVs) have potential to serve as long-range transports and carriers of rapid and accurate attack weapons [1]–[5]. Most of the methodologies mentioned above, are aimed at guaranteeing steady-state performance and transient performance for hypersonic flight control systems under different actual conditions including uncertainties, disturbances, and actuator saturations/faults. Only such basic performance is not enough for hypersonic flight control, and instead we must further seek some optimal performance indexes [23]–[27]. This minimizes cost functions and enhances control performance Despite this advantage, a wellknown problem with the dual-network structure is that it results in high-computation burdens caused by the fact that both the critic network and the action network should be approximately estimated by neural or fuzzy approximations. Such restriction is released in this article and the control inputs are allowed to converge to nonzero constants
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