The problem of simultaneous state and system parameter estimation for aquatic ecosystems is considered in this paper. This problem has been solved through the identification of an innovation dynamical model representa...
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Recent years has seen much progress in the theory and application of iterative learning control schemes for both linear and (classes of) nonlinear dynamics. In the case of the former, many algorithms based on minimizi...
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Recent years has seen much progress in the theory and application of iterative learning control schemes for both linear and (classes of) nonlinear dynamics. In the case of the former, many algorithms based on minimizing a suitable cost function have been reported. Here the interest is in the so-called norm optimal approach where the basic philosophy is to compute the control input on the current trial such that the tracking error is reduced in an optimal way without too much deviation from the control input used on the previous trial. This paper compares the performance of a range of controllers arising from use of the norm optimal approach - both stand alone and against alternatives.
We consider the iterative learning control problem from a 2D systems/adaptive control viewpoint. In particular, it is shown how some fundamental results from nonlinear adaptive control can be successfully applied in t...
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Power systems for hybrid electric vehicles, like most autonomous power systems, must fully and effectively utilize internal power resources to ensure the desired performance on one hand and longevity of system compone...
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Power systems for hybrid electric vehicles, like most autonomous power systems, must fully and effectively utilize internal power resources to ensure the desired performance on one hand and longevity of system components on the other. The optimum solution involves tradeoffs between two often contradictory things. Achieving the optimum depends on the capabilities of design tools used. The Synergetic Approach used in the work described here opens new opportunities to solve this problem more effectively.
Analysis of complex systems such as hierarchically structured network systems that are employed in modelling and analysis various aspects and issues of control and management in telecommunications is investigated. The...
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Real-time scheduling methods introduce various types of jitter in task instance execution. For real-time computer-controlled systems, the introduced sampling jitter and sampling-actuation delays may degrade the system...
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Real-time scheduling methods introduce various types of jitter in task instance execution. For real-time computer-controlled systems, the introduced sampling jitter and sampling-actuation delays may degrade the system performance and even lead to instability in the system. The degradation of the system performance can be compensated on-line by updating the controller parameters at each controller task instance execution, in what we call the compensation approach. In this paper we present stability analysis for controller tasks that perform the compensation approach.
In this paper, the Hopfield neural network with delay (HNND) is studied from the standpoint of regarding it as an optimizing computational model. Two general updating rules for networks with delay (GURD) are given bas...
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In this paper, the Hopfield neural network with delay (HNND) is studied from the standpoint of regarding it as an optimizing computational model. Two general updating rules for networks with delay (GURD) are given based on Hopfield-type neural networks with delay for optimization problems and characterized by dynamic thresholds. It is proved that in any sequence of updating rule modes, the GURD monotonously converges to a stable state of the network. The diagonal elements of the connection matrix are shown to have an important influence on the convergence process, and they represent the relationship of the local maximum value of the energy function to the stable states of the networks. All the ordinary discrete Hopfield neural network (DHNN) algorithms are instances of the GURD. It can be shown that the convergence conditions of the GURD may be relaxed in the context of applications, for instance, the condition of nonnegative diagonal elements of the connection matrix can be removed from the original convergence theorem. A new updating rule mode and restrictive conditions can guarantee the network to achieve a local maximum of the energy function with a step-by-step algorithm. The convergence rate improves evidently when compared with other methods. For a delay item considered as a noise disturbance item, the step-by-step algorithm demonstrates its efficiency and a high convergence rate. Experimental results support our proposed algorithm.
This paper presents a feasible open-canal water-distribution control system based on the dynamic regulation principle and the theory of Kalman optimal controller. The existing nonlinear phenomena, as well as the trans...
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This paper presents a feasible open-canal water-distribution control system based on the dynamic regulation principle and the theory of Kalman optimal controller. The existing nonlinear phenomena, as well as the transport delay phenomenon are accounted for. The obtained controller is simulated using the full Saint-Venant partial differential equations
In general, characteristics of classical control theory and properties of real-time scheduling algorithms may cause unexpected control system responses in the implementation of real-time computer-controlled systems. R...
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In general, characteristics of classical control theory and properties of real-time scheduling algorithms may cause unexpected control system responses in the implementation of real-time computer-controlled systems. Revising real-time scheduling properties, we analyse which are the main timing problems that current scheduling algorithms may introduce in the execution of control loops. Next, we categorise those timing problems, that is, jitters on task-instances executions, in a control context. Afterwards, we show, by simulations, different types of control system performance degradation that these jitters may cause. Finally, we propose possible solutions that solves this degradation, based on irregular sampling discrete-time system models with varying time delays.
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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