In this paper,we investigate a decentralized diagnosis problem of a discrete-evnt system(DES) subject to unreliable sensors,where the sensor observations of local diagnosers may be non-deterministic as a result of pos...
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In this paper,we investigate a decentralized diagnosis problem of a discrete-evnt system(DES) subject to unreliable sensors,where the sensor observations of local diagnosers may be non-deterministic as a result of possible *** studies on decentralized robust diagnosis can only deal with different types of sensor failures separately,e.g.,all sensors suffer from the same type of sensor failures such as intermittent sensor failures or permanent sensor ***,since sensors of different local diagnosers may face different external environments and have different internal characteristics,sensors corresponding to different local diagnosers may also have their own fault *** this paper,we propose a flexible framework of decentralized diagnosis for DES subject to unreliable sensors such that sensors of different local diagnosers are permitted to have different types of sensor *** this end,we extend the existing decentralized diagnosis framework to the case where there exist common sensors broadcasting their observations to all local *** apply linear temporal logic(LTL) to constrain infinite behaviors of private sensors of local diagnosers and common ***,a new notion of φ-codiagnosability is proposed as the necessary and sufficient condition for the existence of a decentralized diagnoser that works correctly under sensors,satisfying LTL-based sensor ***,we provide an effective approach to verify the φ-codiagnosability.
In this paper, a distributed adaptive dynamic programming(ADP) framework based on value iteration is proposed for multi-player differential games. In the game setting,players have no access to the information of other...
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In this paper, a distributed adaptive dynamic programming(ADP) framework based on value iteration is proposed for multi-player differential games. In the game setting,players have no access to the information of others' system parameters or control laws. Each player adopts an on-policy value iteration algorithm as the basic learning framework. To deal with the incomplete information structure, players collect a period of system trajectory data to compensate for the lack of information. The policy updating step is implemented by a nonlinear optimization problem aiming to search for the proximal admissible policy. Theoretical analysis shows that by adopting proximal policy searching rules, the approximated policies can converge to a neighborhood of equilibrium policies. The efficacy of our method is illustrated by three examples, which also demonstrate that the proposed method can accelerate the learning process compared with the centralized learning framework.
Ship cyber-physical system (SCPS) is a complex system that integrates advanced information and communication technology to achieve efficient energy management and navigation plans. Thus, SCPS is susceptible to cyber a...
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This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set...
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This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set and a probabilistic reachable set based on the priori knowledge of system *** with enhanced robust tubes, the chance constraints are then formulated into a deterministic form. To alleviate the online computational burden, a novel event-triggered stochastic model predictive control is developed, where the triggering condition is designed based on the past and future optimal trajectory tracking errors in order to achieve a good trade-off between system resource utilization and control performance. Two triggering parameters σ and γ are used to adjust the frequency of solving the optimization problem. The probabilistic feasibility and stability of the system under the event-triggered mechanism are also examined. Finally, numerical studies on the control of a heating, ventilation, and air conditioning(HVAC) system confirm the efficacy of the proposed control.
This paper investigates the strong structural controllability(SSC) of multi-agent systems(MASs) defined over Laplacian dynamics on directed graphs. The agents that are divided into leaders and followers are connected ...
This paper investigates the strong structural controllability(SSC) of multi-agent systems(MASs) defined over Laplacian dynamics on directed graphs. The agents that are divided into leaders and followers are connected based on the consensus law and only leaders are manipulated by the external control input directly. In contrast to existing work, the topology of MAS contains uncertain interconnection edges between agents. The interconnection graph has a zero/nonzero/arbitrary structure, to handle the parameters uncertainty problem in MASs. Under this framework, the authors propose a color-changing rule based on the zero-forcing set(ZFS). A graph-theoretic sufficient condition of SSC is proved. Next, the authors investigate the leader selection problem to ensure the SSC of MASs. A greedy algorithm based on ZFS is introduced. In addition, the authors figure out that the redundant property of edges in MASs can help us decide the leader selection problem. A new heuristic algorithm of polynomial complexity is developed to select minimum leaders of the multi-agent ***, the authors support the proposed analysis with numerical results on various simulations.
This paper investigates the safety-aware task scheduling problem of real-time controlsystems in the presence of burst computing tasks. The basic idea is to adaptively release resources from low-criticality control ta...
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To address the periodic disturbances introduced by the manipulator mounted on the drone, as well as the overall system parameter variations caused by the robotic arm carried by the Unmanned Aerial Vehicle (UAV), the f...
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This study investigates the controllability of a general heterogeneous networked sampled-data system(HNSS) consisting of nonidentical node systems, where the inner coupling between any pair of nodes can be described b...
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This study investigates the controllability of a general heterogeneous networked sampled-data system(HNSS) consisting of nonidentical node systems, where the inner coupling between any pair of nodes can be described by a unique *** signals on control and transmission channels are sampled and held by zero-order holders, and the control sampling period of each node can be different. Necessary and sufficient controllability conditions are developed for the general HNSS, using the Smith normal form and matrix equations, respectively. The HNSS in specific topology or dynamic settings is discussed subsequently with easier-to-verify conditions derived. These heterogeneous factors have been determined to independently or jointly affect the controllability of networked sampled-data systems. Notably, heterogeneous sampling periods have the potential to enhance the overall controllability, but not for systems with some special dynamics. When the node dynamics are heterogeneous,the overall system can be controllable even if it is topologically uncontrollable. In addition, in several typical heterogeneous sampled-data multi-agent systems, pathological sampling of single-node systems will necessarily cause overall uncontrollability.
The surface of a high-speed vehicle reentering the atmosphere is surrounded by plasma *** to the influence of the inhomogeneous flow field around the vehicle,understanding the electromagnetic properties of the plasma ...
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The surface of a high-speed vehicle reentering the atmosphere is surrounded by plasma *** to the influence of the inhomogeneous flow field around the vehicle,understanding the electromagnetic properties of the plasma sheath can be *** the electron density of the plasma sheath is crucial for understanding and achieving plasma stealth of *** this work,the relationship between electromagnetic wave attenuation and electron density is deduced *** attenuation distribution along the propagation path is found to be proportional to the integral of the plasma electron *** result is used to predict the electron density ***,the average electron density is obtained using a back-propagation neural network ***,the spatial distribution of the electron density can be determined from the average electron density and the normalized derivative of attenuation with respect to the propagation *** to traditional probe measurement methods,the proposed approach not only improves efficiency but also preserves the integrity of the plasma environment.
This paper proposes a hierarchical data-driven scheduling-control framework for a multi-machine/mode production system to operate in an energy-efficient manner. At the scheduling layer, the scheduling problem incorpor...
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