An application of adaptive fault-tolerant control to nano-spacecraft

Since nano-spacecraft are small, low cost and do not undergo the same rigor of testing as conventional spacecraft, they have a greater risk of failure. In this paper we address the problem of attitude control of a nano-spacecraft that experiences different types of faults. Based on the traditional quaternion feedback control method, an adaptive fault-tolerant control method is developed, which can ensure that the control system still operates when the actuator fault happens. This paper derives the fault-tolerant control logic under both actuator gain fault mode and actuator deviation fault mode. Taking the parameters of the UKube-1 in the simulation model, a comparison between a traditional spacecraft control method and the adaptive fault-tolerant control method in the presence of a fault is undertaken. It is shown that the proposed controller copes with faults and is able to complete an effective attitude control manoeuver in the presence of a fault

Neural Network-Based Adaptive Control for Spacecraft Under Actuator Failures and Input Saturations

In this article, we develop attitude tracking control methods for spacecraft as rigid bodies against model uncertainties, external disturbances, subsystem faults/failures, and limited resources. A new intelligent control algorithm is proposed using approximations based on radial basis function neural networks (RBFNNs) and adopting the tunable parameter-based variable structure (TPVS) control techniques. By choosing different adaptation parameters elaborately, a series of control strategies are constructed to handle the challenging effects due to actuator faults/failures and input saturations. With the help of the Lyapunov theory, we show that our proposed methods guarantee both finite-time convergence and fault-tolerance capability of the closed-loop systems. Finally, benefits of the proposed control methods are illustrated through five numerical examples

Dual-Quaternion-Based Fault-Tolerant Control for Spacecraft Tracking With Finite-Time Convergence

Results are presented for a study of dual-quaternion-based fault-tolerant control for spacecraft tracking. First, a six-degrees-of-freedom dynamic model under a dual-quaternion-based description is employed to describe the relative coupled motion of a target-pursuer spacecraft tracking system. Then, a novel fault-tolerant control method is proposed to enable the pursuer to track the attitude and the position of the target even though its actuators have multiple faults. Furthermore, based on a novel time-varying sliding manifold, finite-time stability of the closed-loop system is theoretically guaranteed, and the convergence time of the system can be given explicitly. Multiple-task capability of the proposed control law is further demonstrated in the presence of disturbances and parametric uncertainties. Finally, numerical simulations are presented to demonstrate the effectiveness and advantages of the proposed control method

Indirect neural-enhanced integral sliding mode control for finite-time fault-tolerant attitude tracking of spacecraft

In this article, a neural integral sliding mode control strategy is presented for the finite-time fault-tolerant attitude tracking of rigid spacecraft subject to unknown inertia and disturbances. First, an integral sliding mode controller was developed by originally constructing a novel integral sliding mode surface to avoid the singularity problem. Then, the neural network (NN) was embedded into the integral sliding mode controller to compensate the lumped uncertainty and replace the robust switching term. In this way, the chattering phenomenon was significantly suppressed. Particularly, the mechanism of indirect neural approximation was introduced through inequality relaxation. Benefiting from this design, only a single learning parameter was required to be adjusted online, and the computation burden of the proposed controller was extremely reduced. The stability argument showed that the proposed controller could guarantee that the attitude and angular velocity tracking errors were regulated to the minor residual sets around zero in a finite time. It was noteworthy that the proposed controller was not only strongly robust against unknown inertia and disturbances, but also highly insensitive to actuator faults. Finally, the effectiveness and advantages of the proposed control strategy were validated using simulations and comparisons

PID controller for microsatellite yaw-axis attitude control system using ITAE method

The need for effective design of satellite attitude control (SAC) subsystem for a microsatellite is imperative in order to guarantee both the quality and reliability of the data acquisition. A proportional-integral-derivative (PID) controller was proposed in this study because of its numerous advantages. The performance of PID controller can be greatly improved by adopting an integral time absolute error (ITAE) robust controller design approach. Since the system to be controlled is of the 4th order, it was approximated by its 2nd order version and then used for the controller design. Both the reduced and higher-order pre-filter transfer functions were designed and tested, in order to improve the system performance. As revealed by the results, three out of the four designed systems satisfy the design specifications; and the PD-controlled system without pre-filter transfer function was recommended out of the three systems due to its structural simplicity, which eventually enhances its digital implementation

Increasing performance of spacecraft active fault-tolerant control using neural networks

Actuator fault poses a challenge to the attitude control of spacecraft. Fault-tolerant control (active or passive) is often used to overcome this challenge. Active methods have better performance than passive methods and can manage a broader range of faults. However, their implementation is more difficult. One reason for this difficulty is the critical reaction time. The system may become unrecoverable if the actual reaction time becomes larger than the critical reaction time. This paper proposes using a feedforward neural network to reduce the actual reaction time in the active fault-tolerant control of spacecraft. Besides this improvement, using a feedforward neural network can increase the success percentage. Success percentage is the ratio of successful simulations to the total number of simulations. Simulation results show that for 200 simulations with random faults and initial conditions, the actual reaction time decreases by 73%, and the success percentage increases by 25%. Based on these results, the proposed controller is a good candidate for practical applications

Observer-based adaptive sliding mode fault-tolerant control for the underactuated space robot with joint actuator gain faults

summary:An adaptive sliding mode fault-tolerant controller based on fault observer is proposed for the space robots with joint actuator gain faults. Firstly, the dynamic model of the underactuated space robot is deduced combining conservation law of linear momentum with Lagrange method. Then, the dynamic model of the manipulator joints is obtained by using the mathematical operation of the block matrices, hence the measurement of the angular acceleration of the base attitude can be omitted. Subsequently, a fault observer which can accurately estimate the gain faults is designed, and the estimated results are fed back to the adaptive sliding mode fault-tolerant controller. It is proved that the proposed control algorithm can guarantee the global asymptotic stability of the closed-loop system through the Lyapunov theorem. The simulation results authenticate the effectiveness and feasibility of the control strategy and observation scheme

Fault tolerant control design of floating offshore wind turbines

This work is concerned with active vibration mitigation in wind turbines (WT) but not through the use of specifically tailored devices. Instead, a general control scheme is designed for torque and pitch controllers based on a super-twisting algorithm, which uses additional feedback of the fore-aft and side-to-side acceleration signals at the top of the WT tower to mitigate the vibrational behavior. In general, proposed methods to improve damping through pitch and torque control suffer from increased blade pitch actuator usage. However, in this work the blade pitch angle is smoothed leading to a decrease of the pitch actuator effort, among other benefits evidenced through numerical experiments. The most frequent faults induce vibrations in the corresponding WT subsystems. In fact, vibration monitoring has been recently used for fault diagnosis Thus, by means of vibration mitigation, different faulty conditions can be alleviated leading to a passive fault tolerant control. In this work, coupled non-linear aero-hydro- servo-elastic simulations of a floating offshore wind turbine are carried out for one of the most common pitch actuator faults.Postprint (published version