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In this paper, the problem of data-driven quadratic optimal control is investigated for discrete-time linear systems without the exact knowledge of system dynamics. A value iteration-based algorithm is proposed to obtain the optimal feedback gain. The main idea of the proposed approach is to obtain two sequences for the approximation of the unique positive definite solution of the corresponding algebraic Riccati matrix equation and the optimal feedback gain by using the collected data of the system states and control inputs. The proposed algorithm could be activated by an arbitrary bounded control input and a simple initial value of the Lyapunov matrix. An important feature of this algorithm is that an original stabilising feedback gain is not required. Finally, the effectiveness of the proposed approach is verified by two examples. [ABSTRACT FROM AUTHOR]

In this article, anti‐unwinding sliding mode attitude maneuver control with predefined time is investigated for rigid spacecraft with input saturation. First, a nonsingular sliding function containing two equilibrium points is designed to ensure the predefined‐time convergence of system states and unwinding‐free performance of the closed‐loop system on the sliding phase. Then, an auxiliary system with a dynamic parameter is presented to compensate the impact of input saturation. With this parameter, the auxiliary system can handle input saturation that occurs. Based on the sliding function and the auxiliary system, an attitude maneuver controller is developed to guarantee the robustness of the closed‐loop system to bounded external disturbance. Under the designed controller, the states of the closed‐loop system are driven into a neighborhood of the sliding surface within a predefined time. Moreover, the unwinding phenomenon is also avoided on the reaching phase. Numerical simulation results illustrate the unwinding‐free performance and predefined‐time convergence of the closed‐loop system under the proposed control strategy. [ABSTRACT FROM AUTHOR]

In this article, the fault‐tolerant tracking control is addressed for uncertain strict‐feedback nonlinear systems with actuator faults. Neural networks are utilized to identify unknown dynamics in strict‐feedback nonlinear systems, and the adaptive technique is employed to estimate the parameter of actuator effectiveness. More importantly, a command filtered backstepping control method is improved by introducing a fixed‐time command filter and modifying virtual control laws with compensation mechanisms. By incorporating the adaptive neural networks into the command filtered backstepping design framework, a novel adaptive fault‐tolerant control law is constructed. Under the presented control law, the negative influence of the actuator fault and unknown dynamics is effectively compensated simultaneously. Besides, the "explosion of complexity" and "singularity" problems of backstepping is avoided. Moreover, the practical fixed‐time stability is guaranteed for the resulted closed‐loop system. [ABSTRACT FROM AUTHOR]

In this paper, a problem of data‐driven optimal control is studied for discrete‐time periodic systems with unknown system matrices and input matrices. For this problem, a value iteration‐based adaptive dynamic programming algorithm is proposed to obtain the suboptimal controller. The core of the algorithm proposed in this paper is to obtain an approximation of the unique positive definite solution of the algebraic Riccati equation and the optimal feedback gain matrix by using the collected real‐time data of the system states and control inputs. Without an initial stabilizing feedback gain, the proposed algorithm could be activated by an arbitrary bounded control input. Finally, the effectiveness of the proposed approach is demonstrated by two examples. [ABSTRACT FROM AUTHOR]

Control laws can be constructed in systems design by introducing parameters to obtain good system performance or robustness. Cai et al., in their paper 'Design of LPV controller for morphing aircraft using inexact scheduling parameters', establish a linear parameter-varying model for a morphing aircraft by Jacobian linearization. With such a model, Cai et al. investigate the design problem of gain-scheduled output-feedback controllers by using inexact scheduling parameters for morphing aircraft during the wing transition process. [Extracted from the article]

The problem of attitude consensus control is addressed for multiple rigid spacecraft under a fixed interaction network where only a subset of followers can obtain the leader's state information. To estimate the attitude and angular velocity of the leader, a group of distributed finite‐time observers is constructed for each follower. Then fast non‐singular terminal sliding mode attitude controllers are proposed for followers based on the observed information. Rigorous proofs are presented to show the finite‐time attitude consensus performance of the closed‐loop multiple rigid spacecraft systems under the proposed consensus protocol including distributed observers and attitude controllers. Numerical simulations are provided to illustrate the performance of the proposed attitude consensus protocol. [ABSTRACT FROM AUTHOR]

Summary: In this paper, the problem of fixed‐time attitude consensus control is addressed for a group of rigid spacecraft in the presence of inertia uncertainties and external disturbances. By applying the adaptive technique and neural network approximation technique to handle the disturbances and uncertainties, an adaptive neural network‐based distributed protocol is proposed to achieve attitude consensus control for multiple rigid spacecraft. The proposed distributed attitude consensus protocol is composed of a group of distributed fixed‐time observers for followers to estimate the leader's information and an adaptive neural network‐based fixed‐time sliding mode control law to realize attitude tracking control. Rigorous proofs are provided to demonstrate that the estimation errors of the proposed observers are convergent in a fixed time. Further, it is also proven that attitude tracking errors reach some adjustable regions in a fixed time under the proposed attitude consensus protocol. Numerical simulations are conducted to illustrate the performance of the proposed distributed attitude consensus protocol. [ABSTRACT FROM AUTHOR]

In this article, a novel control approach with a dynamic parameter and an attitude maneuver planning scheme is proposed for flexible spacecraft to achieve anti‐unwinding attitude maneuver control and vibration suppression. In order to suppress the flexible modal vibration of the flexible spacecraft during the attitude maneuver, an attitude maneuver path is planned by the proposed attitude maneuver planning scheme with four input impulses satisfying some conditions. For tracking the planned reference attitude maneuver path without unwinding phenomenon, a robust attitude maneuver controller with a dynamic parameter is proposed based on a novel switching function which contains terminal and non‐terminal sliding manifolds. Besides, the obtained sliding surface contains two equilibria. Finite‐time convergence and unwinding‐free performance of the closed‐loop system are analyzed by Lyapunov theory. The simulation results demonstrate that the proposed attitude control scheme possesses robustness and anti‐unwinding performance. Besides, the flexible vibration can be suppressed by tracking the planned attitude maneuver path. [ABSTRACT FROM AUTHOR]