This paper addresses networking and traffic control problems in network systems along with the potential for introducing soft-computing applications at supervisory control level. The incentive Stackelberg strategy con...
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Given an expansion of a dynamical system in terms of a generalized orthonormal (Hambo) basis, the problem of realizing a state-space model of minimal McMillan degree such that its first N expansion coefficients match ...
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ISBN:
(纸本)0780370619
Given an expansion of a dynamical system in terms of a generalized orthonormal (Hambo) basis, the problem of realizing a state-space model of minimal McMillan degree such that its first N expansion coefficients match the given ones is addressed and solved. For the solution use is made of the properties of the Hambo operator transform theory. The resulting realization algorithms can be applied in an exact and approximative sense and can also be applied to solve a related interpolation problem.
This paper addresses networking and traffic control problems in network systems along with the potential for introducing soft-computing applications at supervisory control level. The incentive Stackelberg strategy con...
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This paper addresses networking and traffic control problems in network systems along with the potential for introducing soft-computing applications at supervisory control level. The incentive Stackelberg strategy control concept was introduced to the networking model that comprises subsidiary systems of users and of network. A linear strategy is proposed for the elastic traffic problem, and results are demonstrated and illustrated via Kelly's (1997) example. The presented method is extended to the non-elastic traffic problem and results are also illustrated via a slightly modified Kelly example. Ways of employing combined analytical and soft-computing approaches and techniques in a hybrid framework have been investigated. A fuzzy-Petri-net supervisor is proposed to implement the strategic decision and control layer. Insofar obtained results are rather encouraging, and this research continues further towards possible implementation as well as some open theoretical issues.
In this paper, cavitation in water hydraulic poppet valves is investigated by an experimental method with a half cut test model. The situation of cavitation appearance, the effects of cavitation on the characteristics...
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The problem of the pricing equilibrium in multi-service priority-based networks isstudied by using Stackelberg game theory. Some concepts of the game theory were revisited first. Then, the existing results on two-user...
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The problem of the pricing equilibrium in multi-service priority-based networks isstudied by using Stackelberg game theory. Some concepts of the game theory were revisited first. Then, the existing results on two-user, twolevel Nash problem was reviewed briefly. Following this background, a new one-leader, two-level, two-user incentive Stackelberg strategy was derived and proved by employing the time delay involved.
The problem of networking supervision and traffic rate control in multi-service network systems is studied by using concepts of Nash equilibrium and Stackelberg strategy under assumption of two-level system architectu...
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The problem of networking supervision and traffic rate control in multi-service network systems is studied by using concepts of Nash equilibrium and Stackelberg strategy under assumption of two-level system architecture. Models of users, network provider and overall system in game-theoretic setting are presented. Linear Stackelberg incentive strategies are derived for both elastic and non-elastic traffic, and verified using Kelly's example. Outlines of the two-level integrated control and supervision architecture, and of the proposed fuzzy-Perti-net supervisor are given.
A neuro controller for high precision manoeuvring of underwater vehicles require special attention to a number of factors including thruster and vehicle’s nonlinearities, couplings which exist between various degrees...
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A neuro controller for high precision manoeuvring of underwater vehicles require special attention to a number of factors including thruster and vehicle’s nonlinearities, couplings which exist between various degrees of freedom as well as effects of the sea currents. The neuro control system for underwater vehicle maneouvring described here is based on the conventional controller supported with the so called adaptive neural network.
Maintaining the technical currency becomes one of the challenging tasks facing industrial professionals. There is a strong need to extend the traditional topics such as feedback control, with topics concerning conditi...
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Maintaining the technical currency becomes one of the challenging tasks facing industrial professionals. There is a strong need to extend the traditional topics such as feedback control, with topics concerning condition monitoring and automatic fault diagnosis. A framework for disseminating basic underlying knowledge through the life-cycle paradigm is presented. The paper addresses the design requirements and practical guidelines with experimental validation on laboratory test processes. The approach should help the practitioners to better understand the potentials of model-based fault diagnosis in industrial practice.
The problem of detecting sensor faults in the presence of modelling errors in linear discrete time systems is addressed. In order to avoid false alarms due to such errors, a statistical test is proposed in which the e...
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The problem of detecting sensor faults in the presence of modelling errors in linear discrete time systems is addressed. In order to avoid false alarms due to such errors, a statistical test is proposed in which the effects of missmodelling are properly taken into account by using stochastic embedding technique. The effectiveness of the resulting (cautious) decision rule is demonstrated on a simulated DC motor-generator process.
This paper deals with sensitivity optimization of detection filters. The robust detection filter design problem as a H ∞ filtering problem is considered. The objective is to provide the smallest scaled L 2 gain of th...
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This paper deals with sensitivity optimization of detection filters. The robust detection filter design problem as a H ∞ filtering problem is considered. The objective is to provide the smallest scaled L 2 gain of the unknown input of the system that is guaranteed to be less than a prespecified level, i.e. , to produce a filter with optimal disturbance suppression capability in such a way that sufficient sensitivity to failure modes is still maintained. The effect of two different input scaling approaches to the optimization process is investigated. It is shown how to obtain bounds on the scaled L 2 gain by transforming the standard H ∞ filtering problem into a convex feasibility problem, specifically, a structured, linear matrix inequality (LMI). Numerical examples demonstrating the effect of the scaled optimization with respect to conventional H ∞ filtering is presented.
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