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This article presents a finite-time prescribed performance (FTPP) control approach based on a learning Chebyshev neural network (LCNN) for spacecraft attitude tracking with modeling uncertainties, actuator faults, and external disturbances. An FTPP function is designed to specify the desired accuracy boundary and finite-time convergence. Further, an FTPP-based learning sliding mode controller (LSMC) is constructed, where the lumped disturbance is approximated and compensated via a novel LCNN model. Unlike conventional adaptive CNN models, the LCNN model employs an iterative learning mechanism for adjusting the weights of the CNN model, reducing computing costs. The FTPP-based LSMC approach is presented with a detailed stability analysis. The proposed method offers a broad range of applications with the FTPP criteria satisfied. A series of simulations are performed to verify the validity and applicability of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper addresses the robust attitude synchronization issue in a multi-spacecraft formation system subjected to limited communication, space disturbances, modeling uncertainties, and actuator faults. To accommodate limited inter-spacecraft communication, a dynamic event-triggered mechanism is designed to reduce the communication trigger frequency by dynamically adjusting the trigger threshold. Moreover, an event-based distributed self-learning neural-network control (SLN2C) law is developed to guarantee robust attitude synchronization during multi-spacecraft formation. In the SLN2C scheme, a learning radial basis function neural network (RBFNN) model is proposed to online approximate and compensate for lumped disturbances, in which an iterative learning algorithm with a variable learning intensity is adopted to update the weight matrix of the RBFNN model. Compared with the traditional fixed learning intensity, a variable one can reduce initial oscillation and weaken the saturation response. Numerical simulations and comparisons are performed to illustrate the effectiveness and superiority of the proposed event-based spacecraft attitude synchronization control method. [ABSTRACT FROM AUTHOR]

This paper addresses the robust attitude synchronization issue in a multi-spacecraft formation system subjected to limited communication, space disturbances, modeling uncertainties, and actuator faults. To accommodate limited inter-spacecraft communication, a dynamic event-triggered mechanism is designed to reduce the communication trigger frequency by dynamically adjusting the trigger threshold. Moreover, an event-based distributed self-learning neural-network control (SLN2C) law is developed to guarantee robust attitude synchronization during multi-spacecraft formation. In the SLN2C scheme, a learning radial basis function neural network (RBFNN) model is proposed to online approximate and compensate for lumped disturbances, in which an iterative learning algorithm with a variable learning intensity is adopted to update the weight matrix of the RBFNN model. Compared with the traditional fixed learning intensity, a variable one can reduce initial oscillation and weaken the saturation response. Numerical simulations and comparisons are performed to illustrate the effectiveness and superiority of the proposed event-based spacecraft attitude synchronization control method. [ABSTRACT FROM AUTHOR]

This paper presents an adaptive non-affine control scheme for the longitudinal short-period model of a generic hypersonic flight vehicle (HFV). Firstly, the non-affine nonlinear characteristics of the aerodynamic coefficients are analyzed, which have great influence on the flight dynamical behaviors. Secondly, without ignoring the non-affine nonlinear aerodynamics, a fuzzy sliding mode adaptive non-affine controller is designed. Under the existence of external disturbances and unmodeled dynamics, the controller can still ensure that the angle of attack tracks the desired signal robustly and asymptotically. Furthermore, the proposed controller does not require the exact bound values of the external disturbances and unmodeled dynamics, which is very important for hypersonic vehicles because the values usually cannot be obtained at hypersonic flight conditions. Finally, the simulation results are provided to illustrate the feasibility and effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this study, the issue of the performance guaranteed fault-tolerant control for formation reconfiguration with collision avoidance in the multi-spacecraft system subjects to space perturbations and thruster faults is investigated. A new nonlinear iterative learning disturbance observer is constructed to accurately reconstruct the synthesized disturbance no matter it is time-varying or not. Then, an exponential artificial potential function with a simple structure and low computation requirement is designed to avoid collision between spacecrafts. A nonsingular terminal sliding mode fault-tolerant control method is explored to accomplish fault-tolerant formation reconfiguration with collision avoidance ability and prescribed robust performance. Finally, numerical simulations and comparisons are performed to validate the effectiveness and superiority of the proposed approaches. [ABSTRACT FROM AUTHOR]

Abstract A fuzzy adaptive non-affine attitude tracking control method is proposed for a generic hypersonic flight vehicle (HFV). Due to the complexities of the hypersonic flows and nonlinear dynamics, the aerodynamic coefficients of the HFV are dependent not only on the attack of angle, sideslip angle, angular rates, and Mach number, but also on the deflection angles of the control surfaces. This cause the attitude tracking control problem becomes a non-affine multi-input–multi-output (MIMO) one. By analyzing the characteristics of the aerodynamic coefficients, it can be found that the non-affine terms have a great influence on the attitude dynamics and should not be ignored. Then, a non-affine MIMO attitude tracking controller is designed using fuzzy sliding mode adaptive techniques with consideration of the non-affine nonlinear aerodynamic coefficients. The proposed controller has good practicability because it does not need to know the exact bound values of the uncertainties, unmodeled dynamics, and external disturbances. Finally, simulation results show that the attitude angles can track the desired signals robustly and asymptotically under the control. [ABSTRACT FROM AUTHOR]

The trajectory planning and tracking control problem is studied in this paper based on prescribed performance method (PPM) for the small-scale unmanned autonomous helicopter (UAH) with wind-gust disturbances (WGDs) and unmeasurable states. For the purpose, the nonlinear model with flapping dynamics is established, and the transformation performance function is used to ensure that the errors of trajectory tracking satisfy the corresponding performance. A fractional-order observer is designed for unmeasurable states to estimate the flapping angles in actual flight, and the fractional-order extended state observer (ESO) is constructed to estimate the WGDs, respectively. On the basis of PPM and the designed observers, the fractional-order theory-based backstepping trajectory tracking control scheme is developed for the UAH system, and the three-dimensional trajectory is planned by the improved wolf pack algorithm. Then the stability of the entire system is proven through strict theoretical analysis. Finally, the simulation analysis on the UAH is presented to demonstrate the efficiency of the designed method. [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]