This paper presents a distributed event-based control strategy for a networked dynamical system consisting of N linear time-invariant interconnected subsystems. Each subsystem broadcasts its state over the network acc...
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ISBN:
(纸本)9781612848006
This paper presents a distributed event-based control strategy for a networked dynamical system consisting of N linear time-invariant interconnected subsystems. Each subsystem broadcasts its state over the network according to some triggering rules which depend on local information only. The system converges to an adjustable region around the equilibrium point under the proposed control design, and the existence of a lower bound for the broadcasting period is guaranteed. The effect of the coupling terms over the region of convergence and broadcasting period lower bound is analyzed, and a novel model-based approach is derived to reduce the communications. Simulation results show the effectiveness of the proposed approaches and illustrate the theoretical results.
This paper examines the control of the heeling angle of a ship in still waters based on the utilisation of anti-heeling tanks operated by pressurized air. The proposed objective attempts to reduce the list angle to a ...
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This paper examines the control of the heeling angle of a ship in still waters based on the utilisation of anti-heeling tanks operated by pressurized air. The proposed objective attempts to reduce the list angle to a null value during the loading process in a fast ferry ship. A nonlinear adaptive controller has been designed as a means of counteracting the parameter inaccuracies that are involved in the nonlinear model. These are the linear and quadratic damping coefficients and the size of the cargo that is being handled. The design is based on a relatively new methodology, the backstepping procedure. With the objective of reducing the number of sensors a model reference based nonlinear observer has been introduced. The controller thus designed provides a robust control system under parametric uncertainties and state variable errors. The designed control implies an improvement on the actual systems based on the PID control implemented under programmable logic controllers (PLCs).
Complex chemical reaction networks often exhibit different dynamic behaviour on different time scales. A combined approach is proposed in this work for determining physically meaningful mass action realizations of com...
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In this paper nonlinear time-varying and bilinear discrete-time systems with additive bounded disturbances are considered. First, conditions guaranteeing uniform ultimate boundedness for time-varying nonlinear systems...
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ISBN:
(纸本)9781612848006
In this paper nonlinear time-varying and bilinear discrete-time systems with additive bounded disturbances are considered. First, conditions guaranteeing uniform ultimate boundedness for time-varying nonlinear systems are established. Then, algebraic conditions ensuring the existence of polyhedral Lyapunov functions, uniform boundedness and positive invariance for closed-loop bilinear systems are obtained. Finally, these results are applied to various robust stabilization problems for bilinear systems subject to persistent additive disturbances. It is shown that these problems can be reduced to a single or a series of linear programming problems.
Electrical Impedance Tomography (EIT), and in particular its application to pulmonary measurement, has been the subject of intensive research since its development in the early 1980s by Barber and Brown. One of the re...
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The extraction and representation of information from volume data are important research avenues in computer-based visualization. The interpretation of three- or multi-dimensional data from various scanning devices is...
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The extraction and representation of information from volume data are important research avenues in computer-based visualization. The interpretation of three- or multi-dimensional data from various scanning devices is important to medical imaging, diagnosis and treatment, reliability and sustainability analyses in various industrial branches, and, in more general terms, information visualization. In this paper, we present several approaches for the classification and representation of relevant information from volume data sets. The techniques are based on the gradient vector, a property directly derived from the original volume data. We show how this property can be computed and subsequently used for classification through gradient-based one- and multi-dimensional transfer functions, as well as for the enhancement of surface features. The described techniques are illustrated through images generated using our volume rendering framework, from Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) data sets. The resulting images show how gradient-based techniques are suited for improved volume classification and the better extraction of meaningful information.
We study the problem of finding the minimum-length curvature constrained closed path through a set of regions in the plane. This problem is referred to as the Dubins Traveling Salesperson Problem with Neighborhoods (D...
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We study the problem of finding the minimum-length curvature constrained closed path through a set of regions in the plane. This problem is referred to as the Dubins Traveling Salesperson Problem with Neighborhoods (DTSPN). Two algorithms are presented that transform this infinite dimensional combinatorial optimization problem into a finite dimensional asymmetric TSP by sampling and applying the appropriate transformations, thus allowing the use of existing approximation algorithms. We show for the case of disjoint regions, the first algorithm needs only to sample each region once to produce a tour within a factor of the length of the optimal tour that is independent of the number of regions. We present a second algorithm that performs no worse than the best existing algorithm and can perform significantly better when the regions overlap.
Fault detection and isolation (FDI) filters are typically synthesized for open-loop or closed-loop systems. The controller affects the FDI filter performance in the closed-loop. Performance metrics for FDI filters are...
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Plug-in hybrid electric vehicles (PHEVs) play an important role in making a greener future. Given a group of PHEVs distributed across a power network equipped with the smart grid technology (e.g. wireless communicatio...
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ISBN:
(纸本)9781457710001
Plug-in hybrid electric vehicles (PHEVs) play an important role in making a greener future. Given a group of PHEVs distributed across a power network equipped with the smart grid technology (e.g. wireless communication devices), the objective of this paper is to study how to schedule the charging of the PHEV batteries. To this end, we assume that each battery must be fully charged by a pre-specified time, and that the charging rate can be time-varying at discrete-time instants. The scheduling problem for the PHEV charging can be augmented into the optimal power flow (OPF) problem to obtain a joint OPF-charging (dynamic) optimization. A solution to this highly nonconvex problem optimizes the network performance by minimizing the generation and charging costs while satisfying the network, physical and inelastic-load constraints. A global optimum to the joint OPF-charging optimization can be found efficiently in polynomial time by solving its convex dual problem whenever the duality gap is zero for the joint OPF-charging problem. It is shown in a recent work that the duality gap is expected to be zero for the classical OPF problem. We build on this result and prove that the duality gap is zero for the joint OPF-charging optimization if it is zero for the classical OPF problem. The results of this work are applied to the IEEE 14 bus system.
Motivated by the increasing needs in the process industry for designing fault tolerant feedback controlsystems based on process data, data-driven design of feedback controlsystems with embedded residual generation i...
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ISBN:
(纸本)9781612848006
Motivated by the increasing needs in the process industry for designing fault tolerant feedback controlsystems based on process data, data-driven design of feedback controlsystems with embedded residual generation is addressed. For this purpose, an extended internal model control (EIMC) structure aiming at accessing the residuals embedded in control loop is first proposed. Based on the identification of the so-called parity subspace and a well-established mapping between the parity vector and the solution of the Luenberger equations, a direct design scheme of EIMC from process data is developed. The achieved results are illustrated by an academic example.
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