Geometric fault detection and isolation filters are known for having excellent fault isolation properties. However, they are generally assumed to be sensitive to model uncertainty and noise. This paper proposes a robu...
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ISBN:
(纸本)9781457700811
Geometric fault detection and isolation filters are known for having excellent fault isolation properties. However, they are generally assumed to be sensitive to model uncertainty and noise. This paper proposes a robust model matching method to incorporate model uncertainty into the design of geometric fault detection filters. Several existing methods for robust filter synthesis are described to solve the robust model matching problem. It is then shown that the robust model matching problem has an interesting self-optimality property for multiplicative input uncertainty models. Finally, a simple example is presented to study the effect of parametric uncertainty and unmodeled dynamics on the performance of a geometric filter.
This paper presents methodology of defining the sources of interferences on the basis of measuring the quality of electrical energy and monitoring the selected parameters of voltage and current waveforms. The presente...
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This paper presents methodology of defining the sources of interferences on the basis of measuring the quality of electrical energy and monitoring the selected parameters of voltage and current waveforms. The presented methodology was based on the example of industrial power network that supplied the new electroprecipitator cooperating with sulphuric acid recovery installation. After a few weeks of proper operation, the Ż electroprecipitator started to report frequent alarms that hindered its effective use. The measurements aimed at specifying the effect of the quality of electrical energy and disturbances occurring in the network on the alarms generated by the electroprecipitator automaticcontrol system. The example shows that as a result of use sophisticated measuring equipment and the analysis of preliminary (short-term) measurements and long-term measurements with the appropriate setting of recording events, it is possible to confirm or reject the hypothesis about the negative effect of low quality energy on the electroprecipitator operation.
This paper discusses energy harvesting techniques suitable for use with wireless remote condition monitoring, especially in the context of fixed asset monitoring. Different commercially available off-the-shelf technol...
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ISBN:
(纸本)9781849195584
This paper discusses energy harvesting techniques suitable for use with wireless remote condition monitoring, especially in the context of fixed asset monitoring. Different commercially available off-the-shelf technologies for energy harvesting are discussed, together with power management technologies and a discussion on system operation. The potential benefits of retrofitting energy harvesting to a battery powered wireless remote condition monitoring system is also presented.
In this paper we propose a distributed algorithm for solving linear programs with combinations of local and global constraints in a multi-agent setup. A fully distributed and asynchronous algorithm is proposed. The co...
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ISBN:
(纸本)9781612848006
In this paper we propose a distributed algorithm for solving linear programs with combinations of local and global constraints in a multi-agent setup. A fully distributed and asynchronous algorithm is proposed. The computation of the local decision makers involves the solution of two distinct (local) optimization problems, namely a local copy of a global linear program and a smaller problem used to generate "problem columns". We show that, when running the proposed algorithm, all decision makers agree on a common optimal solution, even if the original problem has several optimal solutions, or detect unboundedness and infeasibility if necessary.
The paper addresses the optimal design of parallel manipulators based on multi-objective optimization. The objective functions used are: Global Conditioning Index (GCI), Global Payload Index (GPI), and Global Gradient...
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ISBN:
(纸本)9781457708381
The paper addresses the optimal design of parallel manipulators based on multi-objective optimization. The objective functions used are: Global Conditioning Index (GCI), Global Payload Index (GPI), and Global Gradient Index (GGI). These indices are evaluated over a required workspace which is contained in the complete workspace of the parallel manipulator. The objective functions are optimized simultaneously to improve dexterity over a required workspace, since single optimization of an objective function may not ensure an acceptable design. A Multi-Objective Evolution Algorithm (MOEA) based on the control Elitist Non-dominated Sorting Genetic Algorithm (CENSGA) is used to find the Pareto front.
Mobile information systems (MIS) are finding their way into private and business every-day activities. There are also increased attempts to establish MIS for on-site activities in industrial facilities. Industrial env...
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A dynamical system can exhibit structure on multiple levels. Different system representations can capture different elements of a dynamical system's structure. We consider LTI input-output dynamical systems and pr...
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A dynamical system can exhibit structure on multiple levels. Different system representations can capture different elements of a dynamical system's structure. We consider LTI input-output dynamical systems and present four representations of structure: complete computational structure, subsystem structure, signal structure, and input output sparsity structure. We then explore some of the mathematical relationships that relate these different representations of structure. In particular, we show that signal and subsystem structure are fundamentally different ways of representing system structure. A signal structure does not always specify a unique subsystem structure nor does subsystem structure always specify a unique signal structure. We illustrate these concepts with a numerical example.
This paper focuses on model predictive direct torque control (MPDTC), which is a recent control scheme for three-phase ac electric drives combining the notions of model predictive control (MPC) and direct torque contr...
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This paper focuses on model predictive direct torque control (MPDTC), which is a recent control scheme for three-phase ac electric drives combining the notions of model predictive control (MPC) and direct torque control (DTC). Using a dynamic model of the drive, MPDTC predicts several future switch transitions, extends the outputs and chooses the inverter switch positions that minimize the switching frequency or the switching losses. The performance of MPDTC depends on the accuracy of the predictions. However, MPTDC schemes with very accurate predictions are computationally demanding necessitating very fast controller hardware. New methods for extending the output trajectories are proposed that yield fast yet accurate predictions giving rise to a computationally efficient MPDTC scheme. The advantages of the proposed methods are shown in terms of the associated computational complexity and the accuracy of the predictions.
Almost all existing fluid models of congestion control assume that the fluid flow at the output of a link is the same as the fluid flow at the input of the link. This means that all links in the path of a flow see the...
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Almost all existing fluid models of congestion control assume that the fluid flow at the output of a link is the same as the fluid flow at the input of the link. This means that all links in the path of a flow see the original source rate. In reality, a fluid flow is modified by the queueing processes on its path, so that an intermediate link will generally not see the original source rate. In this paper, we propose a simple model that explicitly takes into account of the effect of buffering on output flows. We study the dual and primal-dual algorithms that use implicit feedback and show that, while they are always asymptotically stable if feedback delay is ignored, they can be unstable in the new model.
Robust control and scheduling for networked embedded controlsystems (NECS) with uncertain but interval-bounded time-varying computation and transmission delay is addressed in this paper. The NECS is described by a se...
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ISBN:
(纸本)9781612848006
Robust control and scheduling for networked embedded controlsystems (NECS) with uncertain but interval-bounded time-varying computation and transmission delay is addressed in this paper. The NECS is described by a set of continuous-time plant models and associated quadratic cost functions. Since the uncertainty of the computation and transmission delay affects the discretized plant models and cost functions in a nonlinear manner, a polytopic overapproximation of the uncertainty utilizing a Taylor series expansion is considered. For the resulting discrete-time switched system model with polytopic uncertainty, a periodic control and online scheduling (PCS_(on)) strategy is proposed to guarantee stability and performance of the resulting controlled system. The design is based on a periodic parameter-dependent Lyapunov function and exhaustive search. Furthermore, a method for reducing the online complexity of the PCS_(on) strategy is presented. The effectiveness of modeling and design is evaluated for networked embedded control of a set of inverted pendulums.
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