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Communication network could suffer uncertainties originating from link faults and network attacks. This situation, in multi-agent systems, can be featured by unknown weights of network topology. To impair the influence of the uncertain topology, typical compensation should be taken into account in distributed protocols to the workability of multi-agent systems. This paper, in the context of uncertain topology, addresses finite-time leader-following consensus for second-order uncertain nonlinear multi-agent systems. In addition to uncertainties in topology, the systems also allow unknown control coefficients, which together with the unknown weights renders the realisation of finite-time leader-following consensus nontrivial. Specifically, a fully distributed protocol based on distributed finite-time observer is designed via integrating the adaptive compensation scheme. Notably, in the designed protocol, dynamic high gains are introduced for the compensations of the network uncertainties and agents uncertainties. It turns out that the designed fully distributed protocol guarantees the global finite-time leader-following consensus. Simulation examples are provided to illustrate the validity of the proposed approach. [ABSTRACT FROM AUTHOR]

Among many damage imaging methods based on Lamb wave, phased array Delay and Sum (DAS) has attracted much attention because of its high efficiency. However, inherent dispersion effect leads to the inaccurate acquisition of time-domain features, which affects imaging accuracy. The imaging index based on the amplitude of scattering wave ignores the interaction between Lamb wave and damage, which is difficult to reflect the physical characteristics of damage scattering, and further affects imaging accuracy. We use the physical characteristic parameter-reflectivity of the damage surface as the imaging index and establish an inverse scattering model of damage in frequency domain with dispersion relationship. The simulation and experiment results show that the DAS method combined with the frequency-domain inverse scattering model can realise the high-quality imaging of the damage in the isotropic waveguide structure. [ABSTRACT FROM AUTHOR]

In this article, the adaptive finite-time consensus problem is discussed for uncertain nonlinear multiagent systems. In contrast with the correlative literature, the systems permit multiple uncertainties (not only in control coefficients but also in inherent nonlinearities), and typically the consensus protocol is pursued in a fully distributed fashion (independent from any global information of network topology). This essentially challenges the realization of the finite-time consensus. To overcome the challenge, a new continuous fully distributed protocol is proposed by combining adaptive techniques such that the finite-time consensus of the systems under investigation is achieved. Remarkably, a dynamic high gain, rather than multiple ones in the related literature, is adequate to resist two kinds of uncertainties and to guarantee the fully distributed fashion of the consensus protocol. Moreover, the adaptive finite-time consensus protocol is specified on the scenario of leader-following multiagent systems. Simulation results of three interaction topologies are acquired to illustrate the validity and the wider applicability of the proposed protocol. [ABSTRACT FROM AUTHOR]

This article investigates the event‐triggered stabilization for a class of hyperbolic PDE‐ODE cascade systems with nonlocal term. The presence of unknown parameters in the system brings technical challenges from design to analysis. This compels us to integrate certain powerful dynamic compensation into event‐triggering control mechanism. To solve the problem, by adaptive technique, a compensation strategy is developed to counteract the parametric uncertainties. Then, a desired event‐triggered controller is delicately designed to guarantee that all the signals in the closed‐loop system are bounded and the original system states converge to zero in the L2 norm. Particularly, the event‐triggering mechanism with an additional dynamic signal in the threshold is devised to overcome the negative influence of execution error, while ensuring a positive lower bound for the interexecution intervals. Finally, a simulation example is given to illustrate the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This article is devoted to explore the periodic event-triggered stabilization for continuous-time stochastic systems, and to develop analysis tools/methods for stochastic periodic event-triggered control. Notably, without real-time monitoring of system behavior as in the scenario with continuous event evaluation, it is critical to delicately estimate and govern the execution/sampling error to achieve the desired system performance. This, under stochastic effects, would be substantially challenging, since the behavior of the stochastic system is hard to predict and is disparate between trials even with the same initial conditions. In this article, a framework of global stabilization via periodic event-triggered output-feedback is established: 1) a criterion condition based on the ISS-Lyapunov function is presented for the feasibility of the desired event-triggered stabilization; 2) both the asymptotic stabilization and exponential stabilization are achieved for the systems, with delicately specifying the periodic event-triggering mechanism; and 3) the involved analysis, without applying the well-known Lyapunov theorems, can serve as a pattern from estimating sampling and execution errors to assess the closed-loop stability for stochastic periodic event-triggered control. Moreover, based on the established framework, we contribute the stabilizing controller design via periodic event-triggered output-feedback for a class of stochastic nonlinear systems. [ABSTRACT FROM AUTHOR]

This article is devoted to the optimal protocol for the leader-following consensus of second-order multiagent systems. Remarkably, the global consensus cost functional and the directed topology are pregiven, and the optimal protocol to be sought is distributed. This makes the Riccati-based strategies inapplicable, by which merely centralized protocol can be derived. As the main contribution of this article, an effective strategy of seeking a distributed optimal protocol is proposed for second-order agents over the digraph of the directed tree. Detailedly, the feasibility of distributed optimal protocol is first affirmed, that is, the existence of optimal gain parameters can be guaranteed. Then, by recursively deriving the completely explicit formulas of the consensus errors of relative position and velocity, an online implementable algorithm is developed to achieve the parameterization of the cost functional, that is, to obtain the explicit formula of the cost functional with respect to gain parameters of all agents. Lastly, the desired optimal gain parameters are obtained by minimizing the explicit formula. [ABSTRACT FROM AUTHOR]

This paper is devoted to the output-feedback stabilisation for a class of wave equations. Remarkably, only one boundary measurement corrupted by disturbance is available for feedback, and the boundary condition at the control end is dynamic, rather than static. This renders the control problem more challenging than those in the related literature, largely because certain reconstruction and compensation mechanisms respectively for the state and disturbance are necessary but difficult to integrate with the control design for dynamic boundary condition. For this, a powerful adaptive output-feedback stabilising scheme is proposed. Specifically, a delicate observer is constructed for the state in the space domain, with which a dynamic estimate for the disturbance is incorporated. Then, a desired output-feedback controller is designed by backstepping method, which renders the states of the original system and observer to converge to zero, while the estimate of the unknown disturbance converges to its true value. [ABSTRACT FROM AUTHOR]

Summary: Adaptive output‐feedback control is investigated for a class of uncertain damped wave equations. The remarkable features of the system in question are as follows: (i) Unknown damping is allowed at the boundary; (ii) The boundary measurement is corrupted by an unknown harmonic disturbance. These features make the control problem essentially different from those in the related literature. To solve the problem, a novel adaptive output‐feedback control scheme is established for the system. Specifically, an ingenious observer is first introduced to reconstruct the unmeasured system state in the space domain. Based on this, a certain compensation mechanism is designed for the unknown damping coefficient and output disturbance by adaptive technique based on projection operator. Then, an output‐feedback controller is successfully designed by the backstepping method for ODEs, which guarantees that all states of the resulting closed‐loop system are bounded, and the original system state ultimately converges to an arbitrarily prescribed small neighborhood of the origin. Finally, a simulation example is provided to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper is devoted to the boundary stabilisation via event-triggered output-feedback for a class of 2 × 2 hyperbolic systems. Different from the closely related works, the system parameters are spatially varying and only one boundary measurement is available for feedback, which brings essential difficulties to the analysis and synthesis of event-triggered control. To solve the problem, by using the time-varying strategy and the infinite-dimensional backstepping technique, a novel event-triggered output-feedback controller is designed for the systems. Particularly, a time-varying event-triggering mechanism, with an extra decaying signal introduced into the threshold, is determined. It is rigorously shown that the designed event-triggered controller can guarantee that all the states of the resulting closed-loop system exponentially converge to zero in the sense of L 2 norm while no Zeno phenomenon occurs. Two simulation examples are given to illustrate the effectiveness of the established boundary control strategy. [ABSTRACT FROM AUTHOR]

This paper addresses the linear quadratic regulator optimal leader-following consensus for multiagent systems in a single-integrator form. Substantially different from the existing related works, the cost function, a global one, and the topology structure are both pregiven, and the optimal protocol to be sought is distributed (which merely depends on relative state information). This violates the optimal protocol design based on the algebraic Riccati equation, although a centralized protocol can be derived. To solve the problem, a novel design strategy of distributed optimal protocol is proposed for the multiagent systems over the digraph of a directed tree. Specifically, the dynamics of the consensus error is explicitly obtained, by which an online-implementable algorithm is given to achieve the parameterization of the cost function. Namely, the completely explicit formula with respect to the gain parameters of all agents is derived for the cost function. Based on this, the existence of optimal gain parameters is rigorously proven, which means the existence of the desired distributed optimal protocol. Furthermore, the optimal gain parameters are derived by minimizing the explicit formula. Two simulation examples are provided to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper focuses on the almost sure consensus via time-varying feedback for a class of uncertain stochastic nonlinear multiagent systems. A remarkable feature of the systems is that the nonlinearities allow serious unknowns and time-variations. Moreover, there exists no known bound for the unknown control coefficients. To handle the unknowns and time-variations, a time-varying consensus scheme is developed. The main idea of the scheme is to incorporate a delicate function of time into consensus protocols such that the unknowns and time-variations can be compensated as time increases. Based on the proposed protocols, the almost sure leaderless consensus and almost sure leader-following consensus are achieved. Finally, two simulation examples are provided to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

In the near future, plug-in electric vehicles (PEVs) will dominate the car market. The peak-valley difference would increase greatly due to the random nature of PEVs charging behaviors. In this paper, a new problem on studying the dynamic economic/emission dispatch (DEED) including PEVs for peak shaving and valley filling is proposed, and furthermore, the effect caused by different vehicle-to-grid (V2G) and grid-to-vehicle (G2V) loads on DEED is analyzed. The optimization model of the problem is constructed including several practical constraints, such as power flow constraints and ramp rate limits. The battery degradation cost is also included, which reshapes the objective function of DEED. Based on the model, a strategy for DEED including PEVs for peak shaving and valley filling is given, and a multiobjective optimization algorithm is adopted to solve the proposed problem. To demonstrate the feasibility and effectiveness of the proposed strategy, three DEED cases are considered under different V2G power. The analysis of the effect on fuel cost and emission caused by different V2G power shows that the proposed strategy can effectively reduce the emission and cut down the investment in peak load plants. [ABSTRACT FROM AUTHOR]

We present a hybrid metaheuristic optimization algorithm for solving economic dispatch problems in power systems. The proposed algorithm, based on bat algorithm, combines chaotic map and random black hole model together. Chaotic map is used to prevent premature convergence, and the random black hole model is helpful not only in avoiding premature convergence, but also in increasing the global search ability, enlarging exploitation area and accelerating convergence speed. The pseudocode and related parameters of the proposed algorithm are also given in this paper. Different from other related works, the costs of conventional thermal generators and random wind power are both included in the cost function because of the increasing penetration of wind power. The proposed algorithm has no requirement on the convexity or continuous differentiability of the cost function, although the effect on fuel cost, caused by the underestimation and overestimation of wind power, is included. This makes it feasible to take more practical nonlinear constraints into account, such as prohibited operating zones and ramp rate limits. Three test cases are given to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: This paper investigates the global practical tracking via adaptive output‐feedback for a class of uncertain nonlinear systems. Essentially different from the closely related literature, the system under investigation possesses unknown time‐varying control coefficients and a polynomial‐of‐output growth rate, and meanwhile, the system nonlinearities and the reference signal allow serious unknowns. For this, an adaptive observer is designed to reconstruct the system unmeasured states, where a new dynamic gain is introduced to compensate the serious unknowns in the system nonlinearities and the reference signal. Based on this and by backstepping technique, an adaptive output‐feedback controller is successfully designed, such that all the states of the closed‐loop system are bounded, and the tracking error will be prescribed sufficiently small after a finite time. A numerical simulation is provided to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper considers the global finite-time output-feedback stabilization for a class of uncertain nonlinear systems. Comparing with the existing related literature, two essential obstacles exist: On the one hand, the systems in question allow serious parametric unknowns and serious time variations coupling to the unmeasurable states, which is reflected in that the systems have the unmeasurable states dependent growth with the rate being an unknown constant multiplying a known continuous function of time. On the other hand, the systems possess remarkably inherent nonlinearities, whose growth allows to be not only low-order but especially high-order with respect to the unmeasurable states. To effectively cope with these obstacles, we established a time-varying output-feedback strategy to achieve the finite-time stabilization for the systems under investigation. First, a time-varying state-feedback controller is constructed by adding an integrator method, and by homogeneous domination approach, a time-varying reduced-order observer is designed to precisely rebuild the unmeasurable states. Then, by certainty equivalence principle, a desired time-varying output-feedback controller is constructed for the systems. It is shown that, as long as the involved time-varying gain is chosen fast enough to overtake the serious parametric unknowns and the serious time variations, the output-feedback controller renders that the closed-loop system states converge to zero in finite time. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper is concerned with the global practical tracking via adaptive output feedback for a class of uncertain nonlinear systems. The system under investigation possesses function control coefficients, the polynomial-of-output growth rate and serious unknowns in the system nonlinearities and the reference signal, and hence is essentially different from those in the closely related literature. To solve the problem, a high-gain observer is introduced to reconstruct the unmeasured system states. The involved high gain is the multiplication of two dynamic gains: one is to compensate the polynomial-of-output in the system growth rate, and the other one is to overcome the serious unknowns in the system and reference signal and the extra system nonlinearities in function control coefficients. Based on the high-gain observer, an adaptive output-feedback controller is successfully designed to guarantee that, for any initial condition of the system, all signals of the closed-loop system are bounded, and the tracking error will be prescribed sufficiently small after a finite time. A numerical example demonstrates the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper is devoted to the semiglobal stabilization via output-feedback for a class of uncertain nonlinear systems. Remark that the systems in question contain an unknown control coefficient which inherently depends on the system output and allow larger-than-two order growing unmeasurable states which is the obstruction of global stabilization via output-feedback. By introducing a recursive reduced-order observer and combining with saturated state estimate, a desired output-feedback controller is explicitly constructed for the systems. Under the appropriate choice of design parameters, the controller can make the closed-loop system semiglobally attractive and locally exponentially stable at the origin. A simulation example is provided to illustrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]