A discrete-time linear servo-mechanism problem with system constraints is considered. An approach is developed to solve such a problem using an idea borrowed from large-scale systems theory, in which a coordinating variable is introduced and used to satisfy state constraints. Under the assumption that the system is stabilizable and has a feasible solution, it is shown that the proposed procedure leads to the optimal solution while satisfying system constraints. A convergence analysis of the algorithm is undertaken and illustrative examples are provided to show the performance of the proposed algorithm.
This paper presents an overview of the methodologies and applications of artificially intelligent systems (AIS) in different engineering disciplines with the objective of unifying the basic information and outlining the main features. These are knowledge-based systems (KBS), artificial neural networks (ANN), and fuzzy logic and systems (FLS). To illustrate the concepts, merits, and demerits, a typical application is given from each methodology. The relationship between ANN and FLS is emphasized. Two recent developments are finally presented: one is intelligent and autonomous systems (IAS) with particular emphasis on intelligent vehicle and highway systems, and the other is the very large scale integration (VLSI) systems design, verification, and testing.
A multivariable process of four interconnected water tanks is considered for modeling and control. The objective of the current study is to design and implement a distributed control and estimation (DEC) for a multivariable four-tank process. Distributed model and inter-nodal communication structure are derived from global state–space matrices, thus combining the topology of plant flow sheet and the interaction dynamics across the plant subunits. Using experimental data, the process dynamics and disturbance effects are modeled. A typical lab-scale system was simulated and the obtained results demonstrated the potential of the DEC algorithm.
In this paper, we propose a new Generalized Distribution-Based Handover (DBHO) to deal with the inefficient utilization of spectral resources due to the non-uniform cell loads. The DBHO scheme is different from the existing adaptive schemes since it uses a new criterion to initiate handover when moving from/to a congested cell. Two risk factors are used to dynamically change handover boundaries according to the distribution of traffic loads. This controls the handover initiation process such that a user in a congested cell that is moving to a free cell is allowed to initiate a handover to a new cell earlier, as long as the signal received from the target cell is higher than a certain threshold. While delaying the handover initiation process for a user moving in the opposite direction, as long as the signal received from the serving cell is not lower than a certain threshold. Our results show a substantial reduction in the handover and call dropouts rates. Our scheme is complementary to the existing adaptive schemes proposed in the literature. The proposed scheme also gives cellular system designers a new tool to optimize the overall network performance by initiating handovers based on the traffic intensities.Frequent handovers increase the load on switching networks, which consequently degrades the Quality of Service (QoS). Existing handover schemes usually use parameters such as the received signal strength for initiating a handover with some additional measurements to reduce unnecessary handovers and call dropouts. These schemes perform well when cell loads are somewhat evenly distributed, but fail to account for nonuniform traffic, as is often the case in microcells. Hence, it is desirable to design efficient handover schemes to avoid unnecessary handovers, reduce call dropouts and yet dynamically adapt to the variation of traffic among cells. In this paper, we present a new adaptive handover scheme that dynamically changes the handover boundaries to balance cell loads and to effectively reduce the average number of handovers.
An efficient descriptor approach is developed to solving the robust mixed H 2 =H ? control design problem for a class of linear uncertain systems with time-varying delays. The rationale behind this approach is to exhibit the delay dependence dynamics in the design procedure with an injected relaxation variable. Therefore, the need for overbounding crossproduct terms is bypassed. In the system under consideration, the delay factor is an unknown differentiable function and the uncertainties are assumed to be real, time varying, and norm bounded. A state feedback control is derived for both nominal and uncertain systems such that the H 2 performance measure is minimized while guaranteeing a prescribed H ? norm bound on the controlled system. All the developed results are cast in the format of linear matrix inequalities (LMIs), and a detailed numerical example is presented to illustrate the theoretical analysis.
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