Improved adaptive fault‐tolerant control design for hypersonic vehicle based on interval type‐2 T‐S model

Abstract

Summary This study proposes an improved adaptive fault estimation and accommodation algorithm for a hypersonic flight vehicle that uses an interval type‐2 Takagi‐Sugeno fuzzy model and a quantum switching module. First, an interval type‐2 Takagi‐Sugeno fuzzy model for the hypersonic flight vehicle system with elevator faults is developed to process the nonlinearity and parameter uncertainties. An improved adaptive fault estimation algorithm is then constructed by adding an adjustable parameter. The quantum switching module is also applied to the estimation part to select an appropriate algorithm in different fault cases. The estimation results from the given fuzzy observer are used to design a type‐2 fuzzy fault accommodation controller to stabilize the fuzzy system. The stability of the proposed scheme is analyzed using the Lyapunov stability theory. Finally, the validity and availability of the method are verified by a series of comparisons on numerical simulation results.

Adaptive neural network disturbance observer based nonsingular fast terminal sliding mode control for a constrained flexible air-breathing hypersonic vehicle

“…To verify the effectiveness of the previously proposed scheme, we carry out numerical simulations for FAHV model (1)- (8) in the MATLAB environment where a fourth-order Runge-Kutta algorithm is employed with the fixed-step 0.01 s. The detailed parameters of simulation model could refer to Fiorentini. 17 The vehicle starts at initial trim conditions listed in Table 2, and tracks the reference trajectories of velocity and altitude generated by the following second-order filters with natural frequency !…”

“…4 Considering that there exist instability and nonminimum phase in the longitudinal dynamics of AHV, so domestic and foreign scholars have lucubrated the flight control design for the longitudinal dynamics of AHV where the yaw and roll channels are assumed to be omitted during the cruise phase of supersonic flight. 5 For the purpose of tractable control synthesis and stability analysis, a rigid-body theoretical model, which only describes the longitudinal rigid-body dynamics of AHV, was developed by NASA Langley Research Center in the earliest studies, and then numerous control methods, such as robust control, 6 adaptive backstepping control, 7 fault-tolerant control, 8 sliding mode tracking control, [9][10][11] predictive control, [12][13][14] have been investigated for AHV control system. However, the aerothermoelasticity is induced potentially by the significant flexible effects related to the slender geometry and could destabilize AHV control system, so the flexible dynamics, which were eliminated in the rigid-body theoretical model, cannot be ignored in hypersonic flight.…”

Asymmetric integral BLF based state‐constrained flight control using NN and DOB

“…To address the model uncertainties, robust control strategies including the sliding mode control 5‐7 and H control 8 are investigated on HFVs. Moreover, adaptive laws and intelligent learning are applied in References 9‐15 to achieve online identification. In References 16‐19, the learning performance is improved by mining the internal information of the HFV dynamics.…”

Secure sliding mode control of interval type‐2 fuzzy systems against intermittent denial‐of‐service attacks

“…Especially, the interval type‐2 (IT2) fuzzy set has gained more attention due to its capacity of reducing the computational burden of the type‐2 fuzzy set, which was supported by a large amount of research 22‐26 . Benefit from the IT2 fuzzy set, the IT2 fuzzy system has been extensively applied to represent nonlinearities and uncertainties 27,28 . In Reference 29, an analysis and synthesis framework of IT2 fuzzy systems was established.…”