This paper investigates the simultaneous control of a spacecraft with a rigid central hub and two flexible appendages. Taking into account the coupling between the vibration of flexible appendages and the motion of the hub, the rigid–flexible spacecraft subjected to external disturbance is modeled as a hybrid lumped–distributed parameter system. To attenuate the vibrations of the hub and flexible appendages and simultaneously track the given attitude angle, two boundary control laws are developed based on the original dynamic equation, where all system modes are controlled and spillover instability can be avoided. Using the active disturbance rejection control technique, two extended state observers are designed to obtain the estimation of external disturbances, which can be canceled in the negative feedback loop. The radial basis function neural network with adaptive weight law is employed to deal with the impact of input saturation. The well-posedness of the closed-loop system is proved by applying the semigroup theory. Under the rigorous Lyapunov analysis, the proposed control strategy ensures the practical stability of the rigid–flexible spacecraft system. Simulation verifies the performance of the designed control scheme.

This paper addresses the problems of vibration reduction and attitude tracking for a flexible spacecraft subject to external disturbances and uncertainties. Based on Hamilton’s principle, flexible spacecraft is modelled by a coupled nonlinear partial differential equation with ordinary differential equations. Adaptive boundary control scheme is adopted to stabilize the vibration displacement of flexible appendage into a small neighbourhood of original position and simultaneously maintain attitude angle within the desired angle region. Two disturbance adaptive laws are constructed to attenuate the effect of unknown external disturbances. The well posedness of the controlled system is proven by using the semigroup theory. The proposed adaptive boundary control scheme can guarantee the uniform boundedness of the closed-loop system. Numerical simulation results illustrate the effectiveness of the proposed control scheme.

This paper studies the control problem of an uncertain nuclear refueling machine (RM) system in the presence of uncertainty, external disturbance, input backlash and asymmetric output constraint. Taking into account the effects of external disturbance and input backlash, the RM system with fuel rod is modeled as a copling partial differential equation-ordinary differential equation (PDE-ODE). Using the backstepping method, an adaptive neural network control scheme is designed to drive the RM and bridge to the desired positions and simultaneously reduce the vibration of fuel rod. A novel asymmetric tangent-type barrier Lyapunov function (Tan-BLF) is constructed to restrict the position tracking error into the given range. The formulation of backlash nonlinearity is transformed into the expected input and nonlinear error. Then the combination of input backlash error and boundary disturbance is defined as a disturbance-like item. Applying the robust control strategy and adaptive technique, two auxiliary input signals are proposed to offset the impact of the disturbance-like item. The adaptive neural network (NN) is employed to compensate for the system uncertainty. The practical stability of the RM system with the proposed control is demonstrated via the theoretical Lyapunov analysis. Simulation verifies the performance of the designed control scheme.

This article focuses on the vibration suppression and attitude tracking consensus control of multiple flapping wing unmanned aerial vehicles (UAVs) in the presence of external disturbances and time varying actuator faults. Each flapping wing UAV equipped with a rigid-flexible coupled wing is modeled as partial differential equations (PDEs) with spatially varying coefficients. The hyperbolic tangent function is introduced to deal with the effect of external disturbances. The proposed disturbance rejection approach does not require prior knowledge of external disturbances. Adaptive tuning techniques are adopted to compensate for the system uncertainties caused by time varying actuator faults and external disturbances. A novel distributed fault tolerant boundary control is developed based on the connected and undirected graph to maintain the attitude consensus of multiple flapping wing UAVs and synchronously offset the vibrations of each flapping wing UAV. The uniformly bounded stability of multiple flapping wing UAVs with the designed control protocol is demonstrated by rigorous Lyapunov stability analysis. The control performance of the proposed approach is validated by simulations.