Adaptive fuzzy tracking control for a constrained flexible air-breathing hypersonic vehicle based on actuator compensation

Abstract

The design of an adaptive fuzzy tracking control for a flexible air-breathing hypersonic vehicle with actuator constraints is discussed. Based on functional decomposition methodology, velocity and altitude controllers are designed. Fuzzy logic systems are applied to approximate the lumped uncertainty of each subsystem of air-breathing hypersonic vehicle model. Every controllers contain only one adaptive parameter that needs to be updated online with a minimal-learning-parameter scheme. The back-stepping design is not demanded by converting the altitude subsystem into the normal output-feedback formulation, which predigests the design of a controller. The special contribution is that novel auxiliary systems are developed to compensate both the tracking errors and desired control laws, based on which the explored controller can still provide effective tracking of velocity and altitude commands when the inputs are saturated. Finally, reference trajectory tracking simulation shows the effectiveness of the proposed method in its application to air-breathing hypersonic vehicle control.

Chebyshev Neural Network-Based Adaptive Nonsingular Terminal Sliding Mode Control for Hypersonic Vehicles

“…So far, many advanced control methods have been used to design control systems for hypersonic vehicles, such as dynamic inversion [3][4][5], backstepping control [6][7][8][9], and fuzzy control [10][11][12][13]. In particular, sliding mode control (SMC) is well known for its robustness against parameter uncertainties and external disturbances [14].…”

Adaptive neural tracking control for near-space vehicles with stochastic disturbances

“…The robust flight control of NSV becomes a challenging and valuable work, and some control approaches have been proposed in the literature. [5][6][7][8][9][10][11][12][13][14][15] Meanwhile, the control design as one of the most important research topics in NSV, the tracking control problem has been extensively studied. The novel global neural dynamic surface tracking control scheme is presented for hypersonic flight vehicle in the study by Xu et al 16 The guaranteed transient performance-based attitude control scheme was proposed for NSV with input saturation by Chen et al 17 In the study by Chen et al, 18 a robust sliding mode control strategy was presented for attitude dynamics of NSV.…”

Constrained Adaptive Neural Control for Air-Breathing Hypersonic Vehicles without Backstepping

“…Noticing that the robustness of the designed controllers is closely related to the NDO, an novel NDO based on hyperbolic sine function is investigated and the robustness is enhanced [12]. Moreover, much concern has been on the intelligent controls such as the fuzzy logical system (FLS) [13][14][15] and the neural network (NN) [16,17]. The minimal learning parameter (MLP) scheme [13,14,16] and the composite learning-based parameter adaptive law [15,17] are constructed to update the FLS/NN weights.…”

“…However, the expression of the final actual controller becomes complex with a large number of state variables and design parameters. Motivated by the above studies [13,14,16,17], the radial basis function neural networks (RBFNNs) with MLP algorithm are constructed to approximate the model uncertainty. Different from the previous studies, the control scheme without backstepping is proposed by introducing the high-order differentiator.…”

“…Moreover, much concern has been on the intelligent controls such as the fuzzy logical system (FLS) [13][14][15] and the neural network (NN) [16,17]. The minimal learning parameter (MLP) scheme [13,14,16] and the composite learning-based parameter adaptive law [15,17] are constructed to update the FLS/NN weights. By estimating the model uncertainty accurately and compensating for the controllers, the robustness of the proposed control scheme is ensured.…”