Quantized learning control for flexible air-breathing hypersonic vehicle with limited actuator bandwidth and prescribed performance

Abstract

This paper investigates the quantized learning control considering limited actuator bandwidth and guaranteed transient performance without requiring accurate initial state for flexible air-breathing hypersonic vehicle (FAHV) subject to the lumped disturbances including dynamic coupling, parameter uncertainties, external disturbances, and flexible dynamics. To effectively alleviate the digital communication load from control module to the actuators without sacrificing tracking accuracy, a hysteresis quantizer (HQ) is employed to produce piece-wise quantized control signals that can be executed with finite precision by the FAHV actuators, such that the undesirable chattering phenomena encountered in the traditional non-hysteresis quantizers can be addressed. Subsequently, to provide prescribed specifications on the transient and steady-state behavior of output tracking errors, modified preselected boundaries and error transformation function are constructed to convert the original constrained dynamics into an unconstrained one, such that the predetermined transient and steady-state performance for FAHV can be achieved without the need of priori information of immeasurable initial states. Furthermore, with the aid of the minimal learning parameter-neural network (MLP-NN), the unknown disturbances can be effectively identified online meanwhile the excessive occupation of the limited computational resource can be also avoided. The sigmoid function-based tracking differentiators are applied in the recursive controller design to circumvent the “complexity explosion” phenomena. Different from the existing results for FAHV, a robust control law based on the quantization decomposition is constructed to compensate for quantization error induced by HQ. The stability of resulting control law is analyzed via Lyapunov function and non-smooth analysis technique. The simulation results and comparisons validate the effectiveness of the proposed scheme.