This paper proposes a novel islanding fault detection scheme based on the networked ellipsoidal estimation method for distributed grid-connected photovoltaic (PV) generation systems. The detection of the islanding condition is determined by computing the intersection of the global ellipsoidal estimations. While the global estimations are integrated at each sampling instant with all the local ellipsoidal estimations provided respectively by the local estimators in the communication network. If the islanding fault exists, the intersection of the global ellipsoids would be empty. If the islanding condition does not happen, the intersection of the global ellipsoids would be non-empty. The conditions on the existence of the local and the global ellipsoidal estimation methods are derived by two convex optimization approaches respectively. A simulation is provided by Matlab based on a model of 2-kW single-phase grid-connected power generation system to illustrate the effectiveness of the designed scheme on the detection of the islanding fault.
This paper is concerned with stability of a linear system with a time-varying delay. The direct Lyapunov method is a powerful tool for studying stability of the system. Note that a tighter estimation on the time derivative of some Lyapunov-Krasovskii functional usually leads to a less conservative stability criterion. First, by introducing an auxiliary vector-valued function, this paper proposes a novel integral inequality, which can provide a tighter estimation on the integral term appearing in the time derivative of the Lyapunov-Krasovskii functional. Second, by introducing an augmented Lyapunov-Krasovskii functional, this novel integral inequality is employed to derive a stability criterion for the system with a time-varying delay. Finally, it is shown through a well-studied numerical example that the proposed stability criterion outperforms those using the IQC approach, the quadratic separation approach, the Wirtinger-based integral inequality approach and the free-matrix-based integral inequality approach.
Management of resources is a constant topic in industrial systems. How to use minimum communication resources is of particular interest for control and est
This paper deals with the problem of network-based controller design for the given T-S fuzzy model. The effects of both network-induced delays which are assumed to be interval time-varying, and data packet dropout will be investigated. Based on an integral inequality and a matrix inequality, a delay-dependent sufficient condition for the existence of a network-based controller is formulated in terms of a linear matrix inequality by adjusting two parameter matrices. And no model transformation is employed. Moreover, in order to obtain a less conservative design method of the network-based controller by solving the obtained nonlinear matrix inequalities and to avoid adjusting any parameter matrix, a novel iterative algorithm is proposed. An illustrative numerical example is also given to show the effectiveness of the proposed design method.
This paper is concerned with the synthesis of a state feedback control system which possesses both integrity and robustness. A state feedback control law which retains asymptotic stability against arbitrary actuator failure and parameter perturbations is derived using a positive definite symmetric solution of a new Riccati-type matrix equation. Moreover, a design procedure is proposed, and the effectiveness of the procedure is demonstrated with a numerical example and simulations results.
Chillers are indispensable machines for heat removal and the primary sources of power consumption in heating, ventilation, and air conditioning systems. In this paper, a cardinality-constrained global optimization problem is formulated to minimize power consumption for optimal chiller loading. The formulated problem is solved using a collaborative neurodynamic optimization method based on multiple neurodynamic models. Experimental results based on available actual chiller parameters are elaborated to demonstrate the superiority of the proposed approach to many baseline methods for optimal chiller loading.
To guarantee the safety and reliability of drilling riser after emergency disconnection, it is significant to investigate and refrain recoil response of the riser. This paper deals with the problem of Takagi–Sugeno (T-S) fuzzy recoil dynamic modeling and optimal recoil control of nonlinear deepwater drilling riser systems subject to friction resistance of fluid discharge and platform heave motion. First, a nonlinear recoil control model of coupled riser-tensioner is proposed by taking the nonlinear top tension of tensioner into account. Then, a T-S fuzzy dynamic model of the riser-tensioner system is established to approximate the original nonlinear one by using fuzzy modeling scheme. Third, an augmented T-S fuzzy model of riser system is proposed, where the linear exosystem model of friction resistance and platform heave motion is utilized. Fourth, a finite-time fuzzy optimal recoil controller is designed to suppress the recoil response of the riser, the existence and design algorithm of the fuzzy optimal recoil controller are derived. Simulation results demonstrate that the nonlinear recoil model is more accurate than the existing linear one to describe the recoil characteristics of the riser, and the fuzzy optimal recoil controllers are effective to reduce recoil responses and guarantee the safety of the riser significantly.
This paper is concerned with robust trajectory tracking control for cable-driven parallel robots (CDPRs) with uncertain dynamics. A new accurate trajectory tracking controller (ATTC) is proposed such that the pose of the mobile platform of CDPRs can accurately track a desired trajectory. To further alleviate the input chattering phenomenon, a practical trajectory tracking controller (PTTC) is designed to guarantee the trajectory tracking error is converged to a small neighborhood of the origin. Finally, an illustrative example on a 3-Cable 3-DOF CDPR is provided to evaluate the performance of both ATTC and PTTC, including a comparison study against a typical synchronization controller, which verifies the effectiveness of the proposed controllers.
This paper is to investigate the effect of a small time-delay on dynamic output feedback control of an offshore steel jacket structure subject to a nonlinear wave-induced self-excited hydrodynamic force. Firstly, a conventional dynamic output feedback controller is designed to reduce the internal oscillations of the offshore structure. It is found that the obtained controller is of a large gain in the sense of Euclidean norm, which demands a large control force. Secondly, a small time-delay is introduced intentionally to design a new dynamic output feedback controller such that (i) the controller is of a small gain in the sense of Euclidean norm; and (ii) the internal oscillations of the offshore structure can be dramatically reduced. It is shown through simulation results that purposefully introducing time-delays can be used to improve control performance.
This article is concerned with event-triggered dynamic positioning for a mass-switched unmanned marine vehicle (UMV) in network environments. First, a switched dynamic positioning system (DPS) model for a mass-switched marine vehicle is established. The switched DPS model takes into consideration changes in the marine vehicle's mass and the resultant switching of the marine vehicle's parameters. Second, for a mass-switched UMV controlled through a communication network, a novel weighted event-triggering communication scheme considering switching features is proposed. The weighted error data of multiple sampling instants are utilized to avoid a long-time nontriggering phenomenon. The consideration of switching features guarantees the current sampled data to be transmitted if a switch occurs between the last sampling instant and the current sampling instant. Then, under the event-triggering scheme, an asynchronously switched DPS model for the mass-switched UMV is established in network environments. Based on this model, a mode-dependent DPS controller and event generator co-design method are proposed to attenuate the disturbance induced by wind, waves, and ocean currents. The DPS performance analysis demonstrates the effectiveness of the proposed method.
Fault-tolerant cooperative control of multiagent systems has attracted ever-increasing attention in recent years due to the fact that multiple agents can provide much more redundancy than a single agent system, thereby making the fault tolerant cooperative control design more flexible. However, multiagent systems may bring severe challenges that do not exist in single-agent systems. This article aims at presenting a survey of trends and methodologies of fault tolerant cooperative control in multiagent systems. Depending on the countermeasure against the faults, the existing fault-tolerant cooperative control methodologies are first classified into four categories: Individual methodologies, cooperative methodologies, topology reconfiguration-based methodologies, and composition reconfiguration-based methodologies. Then the characteristics and implementation schemes of four categories of methodologies are discussed in detail. Furthermore, the applicability of fault tolerant cooperative control in smart grids is outlined. Finally, several challenging issues are envisioned for future research.
In the operation planning of heating, ventilation, and air conditioning systems, optimal chiller loading assigns cooling loads to chillers with minimized power consumption. In this article, a mixed-integer optimization problem is formulated for distributed chiller loading and is then decomposed into two optimization subproblems with binary and continuous variables. A collaborative neurodynamic optimization approach is proposed for distributed chiller loading by solving the formulated subproblems. In the collaborative neurodynamic optimization framework, multiple projection neural networks and discrete Hopfield networks are used for scattered searches and a metaheuristic rule is adopted for reinitializing neuronal states upon their local convergence. Experimental results based on the specifications and parameters of three actual chiller systems are elaborated to substantiate the high performance of the approach.
This article revisits some delay-dependent stability criteria previous discussed in the literature. A more systematic approach is taken, and different forms of stability criteria are developed. The form is more convenient to treat related uncertainty in different system matrices. The relationship between the stability criteria based on simple Lyapunov-Krasovskii functional method and on Razumikhin Theorem are more explicitly shown
The convergence of sensing, computing, communication and control elements drives the traditional point-to-point control systems towards networked control systems. Sampled-data control systems, which focus on the significant interplay between sampling and control, play a critical role in modern networked control systems, including intelligent transportation systems, smart grids, and advanced manufacturing systems. This paper presents a survey of methods and trends in non-uniform sampled-data control systems, where sampling and control actions are performed in an aperiodic manner. First, some fundamental issues of both continuous- and discrete-time sampled-data control systems are discussed. Next, main methods in both continuous-time and discrete-time domains are elaborated, respectively. Then, event-triggered sampling, under which sampling is executed only when the system needs attention, is examined. Typical triggering mechanisms in the existing literature are reviewed and classified into four types according to different threshold functions. Furthermore, two applications in terms of automated vehicle platoons and islanded microgrids are provided to demonstrate that sampled-data control methods are capable to support relevant practical application scenarios. Finally, several challenging issues are envisioned to direct future research.
This paper is concerned with fault detection filter design for discrete-time networked control systems (NCSs) under consideration of packet dropouts, network-induced delays and data drift. By considering packet dropouts and network-induced delays separately, new models for discrete-time NCSs with faults are established. Based on the established models, fault detection filter design criteria are proposed to asymptotically stabilize the residual systems in the sense of mean-square and preserve a guaranteed performance. When transferring nonlinear matrix inequalities into a solvable optimization problem, new bounding inequalities are proposed to introduce less conservatism. The designed fault detection filters can ensure the sensitivity of the residual signal with respect to faults, and robustness of the considered systems with respect to data drift. A numerical example is given to illustrate the effectiveness of the obtained results.
