Publications

This paper is concerned with the remote state estimation problem for a class of linear discrete time-varying non-Gaussian systems with multiplicative noises. Due to bandwidth constraints in digital communication networks, the measured outputs are quantized before transmission by a probabilistic uniform quantizer. Our attention is focused on the design of a recursive quadratic estimator that exploits the quadratic functions of the measurements. By introducing a proper augmented system which aggregates the original state vector and its second-order Kronecker power, we are able to transfer the quadratic estimation problem into a corresponding linear estimation problem of the augmented state vector. An upper bound is first established for the covariance of the estimation error that is expressed in terms of the solutions to certain matrix difference equations, and such an upper bound is then minimized by designing the filter parameters in an iterative manner. Subsequently, we discuss the monotonicity of the optimized upper bound with respect to the quantization accuracy. A numerical example is provided to verify the effectiveness of the proposed filtering algorithm.

No abstract is provided for this article.

This paper deals with the dissipative problem for uncertain time-delay networked control systems with both multiple measurement and control packet dropouts. The uncertainty is assumed to satisfy a dissipative inequality, and the multiple measurement and control packet dropouts are described by two independent Bernoulli distributed sequences. By utilizing the Lyapunov functional method, a robust dissipative controller is designed such that the corresponding closed-loop system is asymptotically mean-square stable and strict (Q, S, R)-dissipative. The sufficient condition on the existence of the controller is formulated in the form of linear matrix inequalities. Then the controller gain is achieved by using an extended cone complementarity linearization method. An example is given to illustrate the effectiveness of the proposed design method.

This paper is concerned with event-triggered H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> filtering for networked systems. A novel event-triggering scheme is proposed by taking network dynamics into account simultaneously. First, an information dispatching middleware is constructed to establish a novel framework for networked systems, where two modules namely information selection module and congestion avoidance module are introduced. The information selection module aims to regulate the transmission of the sampled data in terms of a predefined event-triggering condition. The congestion avoidance module is used to schedule those sampled data released by the information selection module to the filter. Second, the on-line scheduling strategy is proposed under this framework. Then the filtering error system based on network dynamics is formulated as a system with an interval time-varying delay. Third, Lyapunov-Krasovskii functional approach is employed to formulate a new sufficient condition to ensure the stability and to guarantee a prescribed H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> noise attenuation performance for the filtering error system. Based on this condition, H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> filtering parameters, network dynamic controllers and event-triggering parameters can be co-designed provided that a set of linear matrix inequalities are feasible. Finally, an example is given to illustrate the merits and effectiveness of the method proposed in this paper.

This study is concerned with distributed H∞ filtering for continuous-time linear systems over sensor networks with heterogeneous Markovian coupling intercommunication delays. The set of sensor nodes forms a sensing and communication network whose topology is modelled by a directed graph that describes the measurement exchanged among neighbouring sensor nodes. Heterogeneous random coupling delays modelled by a Markov process are considered in the intercommunication between interacting sensor nodes. A refined two-step decoupling technique is presented to deal with the complicated coupling of exchanged measurement in the presence of the delays. A sufficient condition on the existence of desired distributed H∞ filters is derived such that the resultant filtering error system is mean square exponentially stable with prescribed weighting average H∞ performance. Two illustrative examples are given to show the effectiveness of the proposed results.

This paper addresses the problem of distributed networked set-membership filtering with ellipsoidal state estimations for a class of discrete time-varying systems in the presence of unknown-but-bounded process and measurement noises. Both global and local ellipsoidal state estimations are provided to locate the true state (target) via a distributed filtering network. A new geometric method based on Minkowski sum is proposed to produce the global ellipsoidal estimation. A novel convex optimization approach is developed to derive some sufficient conditions on the existence of local networked set-membership filters and to obtain the local ellipsoidal estimations by exchanging information among neighboring filters via communication networks. An experiment is conducted based on a 2-kW single-phase grid-connected power generation system platform to demonstrate the feasibility and the effectiveness of the proposed method in the real application.

This chapter deals with the network-based modeling, and observer-based FDFFault Detection Filter (FDF) and controller coordinated design for a UMVUnmanned Marine Vehicles (UMVs) in network environments. Network-based models for the UMVUnmanned Marine Vehicles (UMVs) subject to actuator faults and wave-induced disturbances are established by introducing an observer-based FDFFault Detection Filter (FDF). Based on these models, network-based FDF and controller coordinated design criteria are derived to asymptotically stabilize the residual system.

Autonomous marine vehicles, which provide a platform for the successful implementation of special tasks, such as maritime rescue, maritime measurement, and dangerous goods monitoring, have been widely utilized. In the last decade, considerable attention has been paid to the analysis, modeling, and networked control of autonomous marine vehicles. This survey provides recent advances in networked and DRL-based control for autonomous marine vehicles. Typical mathematical models of autonomous marine vehicles are introduced first as the foundation for control of autonomous marine vehicles. Then, networked and DRL-based control for autonomous marine vehicles is reviewed. Finally, some challenges and open issues are presented to motivate the future research.

This paper presents the optimal tracking control methodology for an offshore steel jacket platform subject to external wave force. Based on a dynamic model of an offshore steel jacket platform with an active mass damper mechanism and a linear exogenous system model of the external wave force on the offshore platform, an optimal tracking control scheme with feedforward compensation is proposed to attenuate the wave-induced vibration of the offshore platform. A feedforward and feedback optimal tracking controller (FFOTC) can be obtained by solving an algebraic Riccati equation and a Sylvester equation, respectively. It is demonstrated that the wave-induced vibration amplitudes of the offshore platform under the FFOTC are much smaller than the ones under the feedback optimal tracking controller (FOTC) and the feedforward and feedback optimal controller (FFOC). Furthermore, the required control force under the FFOTC is smaller than the ones under the FOTC and the FFOC.

This article deals with the problem of electromagnetic source localization (ESL). An evolutionary particle filter, which is first used to make a decision on the positions of electromagnetic sources, has two characteristics. One characteristic is that the number of particles can be significantly reduced while the other characteristic is that the particle diversity can be well improved. On the basis of the estimated positions of electromagnetic sources, the position and velocity of the virtual leader can be determined. Then, an event-based fixed-time consensus control approach is proposed such that the positions and velocities of robots reach consensus with the virtual leader over a fixed-time interval while saving resource consumption by reducing the communication frequencies and updating times of control inputs. Finally, simulation and experimental results show the effectiveness of the proposed decision and event-based fixed-time consensus control approach for ESL.

GPSR routing protocol is incapable of controlling the energy consumption of single node, causing network monitoring loophole. In the current study, a new routing algorithm NEWGPSR was developed from by original GPSR protocol with the introduction of LEACH clustering thought and the improvement of its head selection algorithm, appending active excitation mode, the heuristic rules and local optimization strategy, improving surrounding forward mode.Results of simulation analysis using NS3 platform showed that the new NEWGPSR algorithm was capable of effectively reducing system energy consumption, prolonging the network life cycle, and improving the performance of the entire network.

The cooperative formation control for multiple unmanned surface vehicles (USVs) is studied in this paper. Virtual leaders are introduced to calibrate reference

This chapter addresses the decentralized control for a large-scale system with an IP-based communication network.

This paper is concerned with event-triggered sampled-data consensus for distributed multi-agent systems with directed graph. A novel distributed event-triggered sampled-data transmission strategy is proposed, which allows the event-triggering condition to be intermittently examined at constant sampling instants. Based on this novel strategy, a sampled-data consensus control protocol is presented, with which the consensus of distributed multi-agent systems can be transformed into the stability of a system with a time-varying delay. Then, a sufficient condition on the consensus of the multi-agent system is derived. Correspondingly, a co-design algorithm for obtaining both the parameters of the distributed event-triggered transmission strategy and the consensus controller gain is proposed. Two numerical examples are given to show the effectiveness of the proposed method.

In this paper, the fixed-time leader-following consensus problem is investigated for high-order multivariable multiagent systems with external disturbances. A new distributed observer is proposed for each follower under a directed information flow to estimate the leader state in a fixed time. Based on the observer, a novel tracking controller is designed such that the estimated leader state is tracked with disturbance rejection in a fixed time. Consensus conditions are established to guarantee the fixed-time stability. Different from some existing finite-/fixed-time consensus approaches, an explicit estimate for the upper bound of the settling time is derived, which provides additional system specification in advance. Moreover, for disturbance rejection, the chattering phenomenon is effectively reduced by using a distributed multivariable signum function. Finally, illustrative examples are provided to demonstrate the theoretical results.