Adaptive Finite‐Time Command Filtered Fault‐Tolerant Control for Uncertain Spacecraft with Prescribed Performance

Abstract

In this paper, an adaptive finite-time fault-tolerant control scheme is proposed for the attitude stabilization of rigid spacecrafts. A first-order command filter is presented at the second step of the backstepping design to approximate the derivative of the virtual control, such that the singularity problem caused by the differentiation of the virtual control is avoided. Then, an adaptive fuzzy finite-time backstepping controller is developed to achieve the finite-time attitude stabilization subject to inertia uncertainty, external disturbance, actuator saturation, and faults. Through using an error transformation, the prescribed performance boundary is incorporated into the controller design to guarantee the prescribed performance of the system output. Numerical simulations demonstrate the effectiveness of the proposed scheme.

Finite‐time adaptive fault‐tolerant control for rigid spacecraft attitude tracking

“…Among various finite‐time control schemes (e. g. homogeneous method [21], H ∞ fuzzy control [22], adding power integrators [23]), sliding mode control (SMC) is the most widely used due to its strong robustness against external disturbances and internal uncertainties. Related SMC techniques include but are not limited to terminal sliding mode (TSM) [24,25], non‐singular TSM (NTSM) [26,27], full‐order recursive sliding mode [28], and super‐twisting sliding mode [29] some of which have been applied to achieve finite‐time ATC for spacecraft systems [30‐47]. In [35] an adaptive sliding mode controller was designed for the attitude‐tracking maneuver of a rigid satellite.…”

Robust Finite-Time Tracking for Uncertain Linear Systems with Actuator Faults

“…In a practical system, e.g., networked control system and ight control system, the actuator component usually su ers from a partial loss of e ectiveness (LOE) or even a total loss of control (LOC) due to the increasing complexity of system itself and operating environment [1][2][3][4][5]. See for example, the rudder of an aircraft may experience a loss of gain in the control channel or be stuck in a xed position.…”

Data-Driven Learning-Based Fault Tolerant Stability Analysis

“…Plenty of stability controllers are proposed, for example, variable structure control [1], fuzzy control [2], sliding mode control [3], and adaptive neural control [4]. Various undesirable effects are always existed in many engineering applications, such as time-delay [4], fault [5,6], and uncertainty [7]. In most cases, plenty of these effects can be observed by available measurement data; however in some cases, they are not easily described by existing mathematical models.…”

“…Learning result (this figure shows the learning result in(6) which is based on the optimization problem in (3). b ij g j , i � 1g j , i � 1, 2, 3, 4 { }, see (10) for the detail calculation).…”