Maneuverable threat poses significant risks to the operational safety of spacecraft in orbit, thereby jeopardizing mission success in the contested space environment. To address the coordinated orbital game between multiple pursuers (spacecraft) and one evader (threat), this paper proposes a reward-centering multi-agent deep deterministic policy gradient (MADDPG) algorithm, which has two-folds: Firstly, a relative dynamical model consideringJ2perturbation is established to characterize orbital interactions among multiple players, laying a physics-based foundation for decision-making. Secondly, an improved multi-agent reinforcement learning framework is constructed with two components. For individual spacecraft of multiple pursuers, a state-driven exploration-exploitation tradeoff mechanism is incorporated to avoid suboptimal strategy convergence. For the spacecraft group (namely multiple pursuers), reward functions are designed to align individual behaviors with collective objectives. Furthermore, a reward-centering mechanism along with theoretical analysis is introduced to dynamically calibrate the reward baseline, which stabilizes policy update via reducing gradient variance. Simulation results show the proposed algorithm enables spacecraft to autonomously develop coordinated strategies, ultimately confining the threat within predefined interception threshold.

This work is concerned with the asynchronous output feedback sliding mode control (SMC) of stochastic nonlinear Markov jump systems (MJSs) via Takagi–Sugeno fuzzy models. Due to some real-world environment limitations, the actual system modes that are not directly available for controller synthesis are known as hidden modes. Then the sliding surface/sliding mode controller modes are featured as observable modes, and the relationship between these two concepts is established by employing emission probabilities. As a two-layer stochastic process, the hidden Markov model (HMM) governs the jump parameters and characterizes the asynchronous mode switching phenomenon between the original plant and the sliding surface/sliding mode controller. By integrating the sliding surface with the dynamical features of fuzzy MJSs, the dynamics of the sliding motion are described by constructing a T–S fuzzy singular MJS. Under a unified convexification setup, novel dissipative performance and stochastic stability analysis results on the sliding motion are proposed. In view of the full MJS states also not measurable, a novel observed-mode-based asynchronous output feedback dynamic SMC synthesis approach is propounded to ensure the MJSs’ states are located in a vicinity of the sliding surface. Illustrative simulation examples are finally provided to validate the superiority and effectiveness of the developed scheme.

The complex coupling relationship among attitude, orbit, and vibration challenges the control of flexible spacecraft. This article investigates the integrated attitude–orbit dynamical modeling and control of flexible spacecraft, which accurately describes the above complex coupling relationship to improve control performance. First, a twistor-based attitude–orbit integrated model of flexible spacecraft is established, avoiding the unitary constraint of the dual-quaternion-based model. Then, the attitude–orbit integrated control strategy based on the fully actuated system (FAS) approach is proposed for flexible spacecraft, which yields an arbitrary designable linear closed-loop system. Finally, the correctness of the dynamical model and the effectiveness and superiority of the proposed control strategy are demonstrated by two sets of simulations.

This article studies the asynchronous dissipative-based sliding mode control (SMC) for nonlinear Markov jump system (MJS) by Takagi–Sugeno (T–S) fuzzy models, which suffer from mismatched parameter uncertainties and exogenous disturbances. The actual system modes are usually not accessible directly for controller design due to some practical environment constraints, and the modes of the sliding surface and controller are characterized as observed modes. The hidden Markov model (HMM) is first utilized to detect the system mode information, which also describes the asynchronous phenomenon of the jump mode between the sliding surface/controller and the original plant. Based on the observed modes, a suitable sliding surface is designed via consisting of both the system states and the control input. By sufficiently exploiting the dynamical features of the fuzzy MJSs and associating with the sliding surface, new sliding surface existence conditions are proposed, which also ensure the stochastic stability (SS) and desired dissipative performance for the sliding motion. Then, a novel asynchronous dynamic SMC law is proposed to drive the fuzzy MJS states into a neighborhood of the designed sliding surface. Finally, simulation studies are conducted to show the validity of the proposed approach.

This article investigates the optimal consensus problem for general linear multiagent systems (MASs) via a dynamic event-triggered approach. First, a modified interaction-related cost function is proposed. Second, a dynamic event-triggered approach is developed by constructing a new distributed dynamic triggering function and a new distributed event-triggered consensus protocol. Consequently, the modified interaction-related cost function can be minimized by applying the distributed control laws, which overcomes the difficulty in the optimal consensus problem that seeking the interaction-related cost function needs all agents' information. Then, some sufficient conditions are obtained to guarantee optimality. It is shown that the developed optimal consensus gain matrices are only related to the designed triggering parameters and the desirable modified interaction-related cost function, relaxing the constraint that the controller design requires the knowledge of system dynamics, initial states, and network scale. Meanwhile, the tradeoff between optimal consensus performance and event-triggered behavior is also considered. Finally, a simulation example is provided to verify the validity of the designed distributed event-triggered optimal controller.

This article studies the asynchronous observer-based output feedback control for the continuous-time networked nonlinear systems via the Takagi–Sugeno (T–S) fuzzy affine models with quantized measurements. To tackle the premise variables’ asynchronous phenomena between the original plant and the observer/controller, an asynchronous piecewise fuzzy affine observer design approach is proposed to estimate the immeasurable system state vectors via making full utilization of some advanced matrix inequalities, a novel existence criterion for the asynchronous observer-based piecewise output feedback controller is derived in an unified convex optimization setup, which successfully relax the constraint that the control input matrices are required to be common and uncertainty-free under each fuzzy rules. Simulation studies are provided to justify the efficacy of the proposed method.

This work investigates the issue of output-feedback sliding-mode control (SMC) for nonlinear 2-D systems by Takagi-Sugeno fuzzy-affine models. Via combining with the sliding surface, the sliding-mode dynamical properties are depicted by a singular piecewise-affine system. Through piecewise quadratic Lyapunov functions, new stability and robust performance analysis of the sliding motion are carried out. An output-feedback dynamic SMC design approach is developed to guarantee that the system states can converge to a neighborhood of the sliding surface. Simulation studies are given to verify the validity of the proposed scheme.

This article investigates the nonsynchronous-observer -based output-feedback control of nonlinear systems by Takagi–Sugeno fuzzy affine models. In order to estimate the unmeasurable system states and handle the nonsynchronization issue of premise variables between the observer/controller and the original system, a new nonsynchronous piecewise fuzzy affine observer is first synthesized to estimate the unmeasurable system state variables. Via utilizing some elegant matrix inequalities with convexification techniques, new observer-based piecewise output-feedback controller design results are proposed within the framework of piecewise quadratic Lyapunov functions. Simulation studies are given to illustrate the validity of the developed approach.

The fuzzy observer-based output feedback control of continuous-time nonlinear two-dimensional (2-D) systems is studied by Takagi–Sugeno (T–S) fuzzy models in this work. The plant information of the 2-D systems evolves along two independent directions dynamically. The nonlinear 2-D systems are firstly expressed by T–S fuzzy models with parameter uncertainties. By a Lyapunov method together with some convexification techniques, two methods are developed for fuzzy observer-based output feedback controller synthesis of the underlying fuzzy 2-D systems, and novel output feedback controller synthesis results are proposed within a convex optimization setup. Simulation studies are provided to illustrate the validity of the proposed methods.

The observer-based output feedback control problem for nonlinear systems is studied through Takagi–Sugeno fuzzy affine models. A novel piecewise fuzzy affine observer is designed to estimate the unmeasurable state variables. To remove the assumptions in the existing works that the system input matrices and/or output matrices should be common, full rank, and uncertainties-free, a new approach is developed for the observer-based piecewise output feedback controller synthesis by making sufficient use of Young's inequality with its variance. Through fuzzy piecewise quadratic Lyapunov functions, improved and less conservative results on the output feedback controller design are obtained in terms of linear matrix inequalities, and the restrictions imposed in the existing results can be relaxed. Simulation studies are provided to confirm the effectiveness and conservatism reduction of the developed method.

This article focuses on the sampled-data output-feedback control problem for nonlinear systems represented by Takagi-Sugeno fuzzy affine models. An input delay approach is adopted to describe the sample-and-hold behavior of the measurement output. Via augmenting the system states with the control input, the resulting closed-loop system is converted into a singular system first. Based on the piecewise quadratic Lyapunov-Krasovskii functionals, some novel results on the sampled-data piecewise affine output-feedback controller design are attained by employing some convexification techniques. The simulation studies are presented to illustrate the effectiveness of the proposed scheme.

This article studies the asynchronous sampled-data filtering design problem for Itô stochastic nonlinear systems via Takagi-Sugeno fuzzy-affine models. The sample-and-hold behavior of the measurement output is described by an input delay method. Based on a novel piecewise quadratic Lyapunov-Krasovskii functional, some new results on the asynchronous sampled-data filtering design are proposed through a linearization procedure by using some convexification techniques. Simulation studies are given to illustrate the effectiveness of the proposed method.

This article focuses on the integral sliding mode control (SMC) issue for nonlinear singularly perturbed systems via T-S fuzzy models. A new sufficient criterion for the sliding surface design is attained by adopting convexification techniques, which also guarantees the asymptotic stability of the sliding motion. Then, a new dynamic SMC synthesis scheme is developed to ensure the finite-time reachability of the sliding surface. A simulation example is shown to illustrate the validity of the developed scheme.

The system information of 2-D systems is usually in propagation along two independent directions. This article focuses on the issue of output feedback sliding mode control (SMC) for 2-D nonlinear systems through T-S fuzzy affine models. Associated with the sliding surface function, a singular system is established to describe the sliding mode dynamics. Based on piecewise quadratic Lyapunov functions, some new stability analysis results on the sliding mode dynamical system are attained, and the analysis conservatism can be further reduced. A robust output feedback dynamic SMC synthesis scheme is developed to guarantee the finite-time reachability of the sliding surface. It is also worthy of mentioning that the proposed dynamic SMC synthesis method can handle the mismatched disturbances, and the control input channels are permitted to have parameter uncertainties. Simulation studies are given to illustrate the validity of the developed scheme.

This article addresses the sampled-data piecewise affine (PWA) filter design problem for Itô stochastic nonlinear systems represented by Takagi–Sugeno fuzzy affine models. An input delay method is used to describe the sample-and-hold behavior of the measurement output. Based on a novel piecewise quadratic Lyapunov–Krasovskii functional, some new results on the robust sampled-data PWA filtering design are proposed through a linearization procedure by using some convexification techniques. Simulation studies on a tunnel diode circuit system, and an inverted pendulum system are given to illustrate the effectiveness of the proposed method.

This paper investigates the problem of output feedback sliding mode control (SMC) for a class of uncertain nonlinear systems through Takagi-Sugeno fuzzy affine models. By adopting a state-input augmentation method, a descriptor system is first constructed to characterize the dynamical properties of the sliding motion. Based on a common quadratic Lyapunov function and piecewise quadratic Lyapunov functions, sufficient conditions for asymptotic stability analysis of the sliding motion are obtained with some convexification techniques. An output feedback dynamic SMC design scheme is proposed to force the states of the resulting closed-loop system onto the sliding surface locally in finite time. Two simulation examples are finally shown to illustrate the effectiveness of the proposed approaches.

This paper addresses the output feedback sliding-mode control (SMC) problem for discrete-time uncertain nonlinear systems through Takagi-Sugeno fuzzy dynamic models. Combining with the sliding surface, a descriptor system is constructed to characterize the sliding motion dynamics. Sufficient conditions for asymptotic stability analysis of the sliding motion are attained by the piecewise quadratic Lyapunov functions within a convex optimization setup. Two SMC design approaches are proposed to ensure the finite-time convergence of the sliding surface. Two simulation examples are presented to show the effectiveness of the proposed approaches.

This paper investigates the problem of delay-dependent H∞memory filtering for continuous-time semi-Markovian jump linear systems (MJLSs) with time-varying delay in an input-output framework. Differing from the constant transition rates (TRs) in the conventional MJLSs, the TRs of the semi-MJLSs depend on the random sojourn-time and are thus with time-varying characteristics. By utilizing a two-term approximation for the terms with time-varying delay, it is first shown that the filtering error system (FES) can be reformulated into a feedback interconnection form and the stability and performance analysis problem of the FES can be recast as the scaled small gain (SSG) problem of an interconnected system. Then, based on a semi-Markovian Lyapunov-Krasovskii formulation of SSG condition combined with projection lemma, the H∞filter synthesis for the underlying semi-MJLSs is formulated in terms of linear matrix inequalities. Finally, simulation studies are provided to evaluate the effectiveness and superiority of the proposed design method.

This paper deals with the robust ℋ∞non-fragile controller design for a class of uncertain T-S fuzzy-affine systems. More specifically, a non-fragile piecewise affine static output feedback (SOF) controller with additive gain variations is constructed to ensure the stability and ℋ∞performance of the closed-loop fuzzy-affine dynamic system. Through applying a common/piecewise quadratic Lyapunov functions, different sufficient conditions are derived to solve the robust and non-fragile piecewise affine SOF control problem. Finally, simulation results verify the effectiveness of the proposed approaches.