Nonlinear robust adaptive control of an airplane with structural damage

Abstract

This article investigates the design of a novel nonlinear robust adaptive control architecture to stabilize and control an airplane in the presence of left-wing damage. Damage effect is modeled by considering the sudden mass and inertia changes, center of gravity, and aerodynamic variations. The novel nonlinear control algorithm applies a state predictor as well as the error between the real damaged dynamics and a virtual model based on the nominal aircraft dynamics in the control loop of the adaptive strategy. The projection operator is used for the purpose of robustness of the adaptive control algorithm. The stability of the proposed nonlinear robust adaptive controller is demonstrated applying the Lyapunov stability theory. The performance of the proposed controller is compared with two previous successful algorithms, which are implemented on the Generic Transport Model airplane to accommodate wing damage. Numerical simulations demonstrate the effectiveness and advantages of the proposed robust adaptive algorithm regarding two other algorithms of adaptive sliding mode and L 1 adaptive control.

L1 adaptive output-feedback fault-tolerant control for uncertain nonlinear systems subject to unmodeled actuator dynamics and faults

“…So the proposed fault-tolerant controller has a simple structure and easy to implement. Unlike the results in Ahmadi et al (2019), the proposed controller abolishes the constraint that the state variables are measurable and enhances practicability. 2.…”

“…For the past few years, scholars have gradually paid attention to the research of L1 adaptive fault-tolerant control. Ahmadi et al (2019) design a L1 adaptive controller combined with nonlinear dynamic inversion to stabilize and control airplane subject to unmodeled actuator dynamics, wing and vertical tail damage. Meanwhile, through comparative experiments with a model reference adaptive controller, a robust model reference adaptive controller, and an adaptive sliding mode controller, the performance of the proposed controller has been verified to be superior.…”

“…Compared with the projection operator-based adaptive law in most L1 adaptive controllers (Ahmadi et al, 2019; Alyazidi and Mahmoud, 2018; Li et al, 2017b; Nguyen and Dankowicz, 2019), the piecewise-constant adaptive law is adopted in this paper. The former reduces the estimation error by choosing a high adaptive gain, but the high adaptive gain will bring undesirable high-frequency oscillations and the choice of gain is restricted by hardware conditions, which needs a trade-off scheme.…”

Performance-based emergency landing trajectory planning applying meta-heuristic and Dubins paths

“…Finally, the conclusion section presents the key results of our research. leads to loss of control (LoC) [6][7][8]. It is essential to maintain stable flight in all flight conditions including the degraded performance conditions in presence of in-flight fault or failure.…”

Trajectory tracking of under-actuated quadcopter using Lyapunov-based optimum adaptive controller

“…To this date, a number of efficient control approaches have been successfully applied on aerospace systems. [2][3][4][5][6][7][8][9] For example, linear controllers such as proportionalintegral-derivative (PID) 10,11 and linear quadratic regulator [12][13][14] and nonlinear control approaches such as fuzzy-adaptive extended Kalman filter, 15 model predictive, 16 θ-D-based nonlinear tracking, 17 immersion and invariance-based adaptive theory, 18 nonlinear L 1 adaptive control, 19 sliding mode controller, 20,21 feedback linearization, 22,23 and backstepping [24][25][26] have been investigated for aerospace systems with fully known dynamics. What is more, several control methods have been developed to tackle the uncertain dynamic model of a dynamic system.…”