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This study investigates the problem of reconstructing actuator faults for descriptor systems via a PD‐type learning observer. By synthesising the derivatives of the output estimation error into the P‐type learning law, a novel PD‐type learning observer is established to simultaneously reconstruct original system states and actuator faults. Stability analysis of the PD‐type learning observer is explicitly provided. A systematic design method is also suggested based on a linear matrix inequality technique. Further, a robust PD‐type learning observer is designed against process disturbances and measurement noises. At last, a simulation example is used to demonstrate the effectiveness of the proposed fault‐reconstructing method. [ABSTRACT FROM AUTHOR]

In this study, the problem of robust fault reconstruction in polytopic linear parameter‐varying systems, subject to loss of actuator effectiveness and external disturbances, is investigated using a learning observer (LO). A polytopic LO is proposed to achieve system state estimation and actuator fault reconstruction at the same time. The proposed LO is sensitive to incipient faults because no chattering is induced. Both constant and time‐varying faults can be accurately reconstructed and detected. Moreover, simultaneous fault reconstruction and detection can be performed using a single LO because the reconstructed fault signal can be employed as a fault alarm. The stability and convergence of polytopic LO and the uniformly ultimately boundedness of the dynamic error system is proved using Lyapunov stability theory and H∞ techniques. A systematic design of the LO is effectively solved using standard linear‐matrix‐inequality techniques. At last, simulation results on a satellite system for attitude control verify the effectiveness of the proposed fault‐reconstruction approach. [ABSTRACT FROM AUTHOR]

This paper addresses the control problems of distributed attitude coordination for multiple flexible spacecraft based on the feedback of inertial vector measurements. It is assumed that the angular velocity information is not available, and the modal variable cannot be measured. The orientation error model with vector measurements is introduced. And then the distributed attitude synchronization control scheme is presented without actuator faults or disturbances. It is guaranteed that the desired equilibrium is locally asymptotically stable and the undesired equilibrium is unstable. Meanwhile, the domain of attraction is given by inequality constraints. In the case that there exist actuator faults and external disturbances, a robust fault-tolerant control strategy is developed to realize attitude synchronization. The hyperbolic tangent function in place of sign function is adopted to eliminate external disturbances. Meanwhile, the adaptive laws are proposed to estimate actuator faults. The salient feature of these control approaches is that no modal variable observers are utilized and the control schemes are robust to the inertia uncertainty of spacecraft. Finally, numerical simulations are implemented to manifest the validity of the presented control schemes. [ABSTRACT FROM AUTHOR]

This paper investigates an optimal small satellite orbit design problem subject to the atmospheric drag uncertainty, and the small satellite is assumed to have no orbital control systems due to volume and mass constraints. The optimization objective of maximum target observation time is considered, which is constrained by the priority and minimum observation duration of each target site. Given the adverse impacts of atmospheric drag uncertainty on the designed orbit, the optimal solution is expected to maximize observation duration for given target sites while being less sensitive to substantial variations of atmospheric coefficients involved in atmospheric drag modeling. As a result, a robust orbit design approach is proposed by combining the robust optimization model with multi-objective optimization algorithm. Finally, the Monte Carlo simulation results are provided to demonstrate that the robust orbit solutions are more reliable compared to the nominal orbit solution designed from the traditional single-objective stochastic optimization algorithm. [ABSTRACT FROM AUTHOR]