The design of constrained, "plant-friendly" multisine input signals that optimize a geometric discrepancy criterion arising from Weyl's theorem is examined in this paper. Such signals are meaningful for ...
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The design of constrained, "plant-friendly" multisine input signals that optimize a geometric discrepancy criterion arising from Weyl's theorem is examined in this paper. Such signals are meaningful for data-centric estimation and control methods, where uniform coverage of the output state-space contributes greatly to good performance. The optimization problem includes a search for both the Fourier coefficients and phases in the multisine signal, resulting in a uniformly distributed output signal that achieves a desirable balance between high and low gain directions, an important consideration when identifying strongly interactive multivariable systems. The solution involves very little user intervention and has significant benefits compared to multisine signals that minimize crest factor. The usefulness of this problem formulation is shown by applying it to a case study involving composition control of a binary distillation column.
This paper discusses the application of the idea of federated filtering to the estimation of intrinsically nonlinear distributed systems by examining its impacts on filtering performance by using the Extended Kalman F...
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This paper discusses the application of the idea of federated filtering to the estimation of intrinsically nonlinear distributed systems by examining its impacts on filtering performance by using the Extended Kalman Filter (EKF) as state estimator. Specifically, the performance of the traditional centralized solution is compared with the filtering structure obtained using the federating idea, and their conceptions, and their ability to balance between fault tolerance and estimation accuracy is examined. Our research demonstrates how successfully the EKF for solving nonlinear estimation problems in federated structures can be used, noting that the idea of federation have only been demonstrated for linear problems previously. In addressing the demands of both fault tolerance and estimation accuracy, it is shown that increased filtering accuracy is relied on the proper choice of sharing of the error covariance information between local filters, while sensor fault tolerance is provided by the utilization of an appropriate resetting policy of the filter.
A distributed-port-Hamiltonian system is a generalized model for passivity-based controls. The system representation has been extended to an infinite-dimensional conservative system derived from variational calculus, ...
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A distributed-port-Hamiltonian system is a generalized model for passivity-based controls. The system representation has been extended to an infinite-dimensional conservative system derived from variational calculus, which is called a field-port-Lagrangian system. A lot of practical systems for controlengineering include dissipative elements; however such a non-conservative structure usually cannot be defined by a variational problem. This paper shows that a system with the dissipative structure can be defined as a time-varying fieldport-Lagrangian system by a gauge transformation. First, we show that the gauge transformation generates a time-dependent Lagrangian density functional that introduces the time-varying port-representation. Next, we present that a class of dissipative systems can be identified with a conservative system possessing an internal irreversible energy flow. Finally, we illustrate an equation of elastic films with viscosity damping with the time-varying port-representation.
The number of hybrid vehicles is expanding contributing to reducing CO 2 emission and fuel consumption in relation to environmental issue. In addition, to materialize more safety vehicles, the future active safety sys...
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ISBN:
(纸本)0930815823
The number of hybrid vehicles is expanding contributing to reducing CO 2 emission and fuel consumption in relation to environmental issue. In addition, to materialize more safety vehicles, the future active safety system is being developed. Consequently, the next generation vehicles to realize low emission, safety driving and comfortable compartments are increasingly required. systems for the next generation vehicles require many electronics such as sensing devices, electronically control components, inverters and control units, since the systems are electrically-powered and electronically-controlled. Those electronic components should be not only small, lightweight and low cost but also highly reliable. The higher power density of the component due to smaller packaging requires technologies of high heat dissipation and heat resistance. We place expectations on materials as a break-through technology for automotive electronics. Advanced materials and approaches for automotive electronics are presented in this paper.
Bucky gel actuator is a novel electro-active polymer (EAP), which is a low-voltage driven dry soft actuator. Its device has a bimorph structure with polymer-supported bucky gel electrodes and a polymer-supported ionic...
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Bucky gel actuator is a novel electro-active polymer (EAP), which is a low-voltage driven dry soft actuator. Its device has a bimorph structure with polymer-supported bucky gel electrodes and a polymer-supported ionic gel electrolyte. It can be fabricated by layer-by-layer casting, to form any shape easily. In addition, the bucky gel device generates electromotive force when bending, and then it also can be used as a sensor. Since sensor and actuator functions exist in a same device, flexible and miniature integrated actuator-sensor systems for soft robotics can be constructed easily. In this study, we conduct some experiments to verify the possibility of the bucky gel actuator/sensor. Feedback controls of the actuator are demonstrated and the characteristics of the sensor are investigated. By utilizing both functions of the actuator and the sensor, feedback control based on the sensor signal is demonstrated.
Supply chain management (SCM) is concerned with the efficient movement of goods through a network of suppliers and retailers. Effective SCM represents a crucial imperative for all modern, global enterprises. As delaye...
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The development of control-oriented decision policies for inventory management in supply chains has received considerable interest in recent years, and demand modeling to supply forecasts for these policies is an impo...
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The development of control-oriented decision policies for inventory management in supply chains has received considerable interest in recent years, and demand modeling to supply forecasts for these policies is an important component of an effective solution to this problem. Drawing from the problem of control-relevant identification, we present an approach for demand modeling based on data that relies on a control-relevant prefilter to tailor the emphasis of the fit to the intended purpose of the model, which is to provide forecast signals to a tactical inventory management policy based on Model Predictive control. Integrating the demand modeling and inventory control problems offers the opportunity to obtain reduced-order models that exhibit superior performance, with potentially lower user effort relative to traditional “open-loop„ methods. A systematic approach to generating these prefilters is presented and the benefits resulting from their use are demonstrated on a representative production/inventory system case study.
Supply chain management (SCM) is concerned with the efficient movement of goods through a network of suppliers and retailers. Effective SCM represents a crucial imperative for all modern, global enterprises. As delaye...
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Supply chain management (SCM) is concerned with the efficient movement of goods through a network of suppliers and retailers. Effective SCM represents a crucial imperative for all modern, global enterprises. As delayed and uncertain dynamical systems, supply chains provide an excellent opportunity for demonstrating the benefits of control principles to what is traditionally perceived as a “business” problem. This paper describes a series of controlsystems for a standard production-inventory system (the basic unit of a supply chain) which have been used at Arizona State University as MATLAB®-based exercises in both undergraduate and graduate-level process control courses. Among the important control concepts illustrated by these exercises are: 1) modeling of supply chain dynamics using fluid analogies, 2) the benefits of multi-degree-of-freedom feedback-feedforward control over feedback-only control, and 3) the application of Internal Model control and Model Predictive control.
This paper presents an approach based on the use of correspondence analysis (CA) for the task of fault detection and diagnosis. Unlike other tools (PCA / DPCA) that are used for this latter task, CA is shown to use a ...
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This paper presents an approach based on the use of correspondence analysis (CA) for the task of fault detection and diagnosis. Unlike other tools (PCA / DPCA) that are used for this latter task, CA is shown to use a different metric to represent the information content in the data matrix X . Decomposition of the information represented in the metric is shown to yield superior performance from the viewpoints of data compression, discrimination and classification as well as early detection of faults. We demonstrate these performance improvements over PCA and DPCA on the Tennessee Eastman problem, which is a representative benchmark problem used in the literature. CA is shown to yield vastly superior performance for the monitoring of the TE problem, when compared with PCA and DPCA.
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