Volume 2, Number 1, 2005
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In this paper eigenstructure assignment via proportional-plus-derivative feedback is investigated for a class of second-order descriptor linear systems. Under certain conditions, simple, general and complete parametric solutions of both finite closed-loop eigenvector matrices and feedback gain matrices are derived. The parametric approach utilizes directly original system data, involves manipulations only on n-dimensional matrices, and reveals all the design degrees of freedom which can be further utilized to achieve certain additional system specifications. A numerical example shows the e?ect of the proposed approach.
This paper presents a new algorithm for Support Vector Machine (SVM) training, which trains a machine based on the cluster centers of errors caused by the current machine. Experiments with various training sets show that the computation time of this new algorithm scales almost linear with training set size and thus may be applied to much larger training sets, in comparison to standard quadratic programming (QP) techniques.
To aid in the sustainable development of cities this paper examines methods for urbanization and epidemic control. Using, as a foundation, game theory from modern control theory, a set of strategies for modeling urbanization and epidemic control are examined by analyzing and studying the current condition of China including its population, economy, resources and city management methods. Urbanization and epidemic control solving strategies are probed and the solution to a simulated example is provided. The conclusion from this research is that the speed of Chinese urbanization should be slowed to match the condition of resources and level of city management available.
The achievable bit error rate of a linear equalizer is crucially determined by the choice of a decision delay parameter. This brief paper presents a simple method for the e?cient determination of the optimal decision delay parameter that results in the best bit error rate performance for a linear equalizer.
This paper presents the design and implementation of reconfigurable virtual environments (VEs) for virtual testing. It proposes a hybrid design approach that is derived from a so-called integration and composition of the reconfigu- ration strategy. The designing process has thus evolved from binding virtual objects using reconfiguration rules within the context of virtual testing scenarios. Therefore reconfigurable virtual environments are established with improved ?exibility and scalability, tailored to a wide range of virtual testing applications. Those virtual environments integrate virtual testing scenarios, data acquisition, databases, rule mapping and application interfaces, which yield modular testing functions and an open-ended system architecture with a set of extensible interface tools to realize data exchange within reconfigurable VEs. This enables virtual testing scenarios to be reconfigured interactively based on real time data and communication between virtual environments and real environments. A virtual testing application has been implemented using reconfigurable VEs.
This paper addresses the robust input-output energy decoupling problem for uncertain singular systems in which all parameter matrices except E exist as time-varying uncertainties. By means of linear matrix inequalities (LMIs), suffcient conditions are derived for the existence of linear state feedback and input transformation control laws, such that the resulting closed-loop uncertain singular system is generalized quadratically stable and the energy of every input controls mainly the energy of a corresponding output, and inffuences the energy of other outputs as weakly as possible.
In this paper a multivariable decoupling control algorithm for the coal-pulverizing system of a ball miller is provided. It is based on a three-neuron control mechanism and solves the problem of long delay and strong coupling in ball mill coal pulverizing systems. Our system has been used for more than a year, the principle and equipment of which have been proved e?ective and profitable.
A kind of transfigured loop shaping controller is presented in this paper. A transfigured loop shaping system puts a controller K in a feedback loop, while putting the dc gain of the controller K on the reference signal line. It is shown through frequency domain analysis and simulation that a transfigured controller can improve the dynamic behavior of a system. The transfigured loop shaping controller method is simple and e?ective and corresponds to the mixed sensitivity method of robust control theory, which improves the behavior of a system by iterative tuning of weighting functions. Satisfactory control results are obtained when it is applied to the design of an underwater vehicle.
In this paper, the following results are proved: (1) Using both deletion strategy and lock strategy, resolution is complete for a clause set where literals with the same predicate or proposition symbol have the same index. (2) Using deletion strategy, both positive unit lock resolution and input lock resolution are complete for a Horn set where the indexes of positive literals are greater than those of negative literals. (3) Using deletion strategy, input half-lock resolution is complete for a Horn set.
Static self-optimising control is an important concept, which provides a link between static optimisation and control. According to the concept, a dynamic control system could be configured in such a way that when a set of certain variables are maintained at their setpoints, the overall process operation is automatically optimal or near optimal at steady- state in the presence of disturbances. A novel approach using constrained gradient control to achieve self-optimisation has been proposed by Cao. However, for most process plants, the information required to get the gradient measure may not be available in real-time. In such cases, controlled variable selection has to be carried out based on measurable candidates. In this work, the idea of direct gradient control has been extended to controlled variable selection based on gradient sensitivity analysis (indirect gradient control). New criteria, which indicate the sensitivity of the gradient function to disturbances and implementation errors, have been derived for selection. The particular case study shows that the controlled variables selected by gradient sensitivity measures are able to achieve near optimal performance.
This paper presents a linearized approach for the controller design of the shape of output probability density functions for general stochastic systems. A square root approximation to an output probability density function is realized by a set of B-spline functions. This generally produces a nonlinear state space model for the weights of the B-spline approximation. A linearized model is therefore obtained and embedded into a performance function that measures the tracking error of the output probability density function with respect to a given distribution. By using this performance function as a Lyapunov function for the closed loop system, a feedback control input has been obtained which guarantees closed loop stability and realizes perfect tracking. The algorithm described in this paper has been tested on a simulated example and desired results have been achieved.
This paper investigates a mobile telecommunications system that supports both ad hoc and infrastructure mode operations. Based on analytic and simulation models, our study investigates how base station (BS) and ad hoc channel capacity, and the mobility and locality of mobile stations a?ect the performance of a dual mode system. We show that a dual mode system can significantly outperform a single mode (infrastructure) system when the degree of locality is high. Furthermore, a dual mode system can support much faster mobile users with less BS channels in comparison to an infrastructure mode system. Our study quantitatively identifies the threshold value for the number of ad hoc channels such that beyond this threshold, increasing ad hoc channel capacity will not improve the performance of a dual mode system.
After the 9/11 terrorism attacks, the lock-out of the American West Ports in 2002 and the breakout of SARS disease in 2003 have further focused mind of both the public and industrialists to take effective and timely measures for assessing and controlling the risks related to container supply chains (CSCs). However, due to the complexity of the risks in the chains, conventional quantitative risk assessment (QRA) methods may not be capable of providing suffcient safety management information, as achieving such a functionality requires enabling the possibility of conducting risk analysis in view of the challenges and uncertainties posed by the unavailability and incompleteness of historical failure data.Combing the fuzzy set theory(FST)and an evidential reasoning(ER)approach,the paper presents a subjective method to deal with the vulnerability-based risks,which are more ubiquitous and uncertain than the traditional hazard-based ones in the chains.
Research into the moisture transport processes in porous materials is primarily important for theoretical mod- elling and industrial applications in the design of energy saving buildings and living environments, etc. Based on experimental investigation, we propose new models which describe one-dimensional transport through one-layered uniform materials and dissimilar two-layered composites. Di?usivity as a function of moisture content is obtained through a Boltzman trans- formation, master curves, and combined numerical and regression techniques. Transport processes in one and two-layered composites are simulated on the basis of extended unsaturated Darcy's Law using the finite element method (FEM). Simula- tion results show significantly di?erent transport patterns of moisture profile when moisture migrates in di?erent directions, and high agreement with experimental moisture profiles.
In implementations of MPC (Model Predictive Control) schemes, two issues need to be addressed. One is how to enlarge the stability region as much as possible. The other is how to guarantee stability when a computational time limitation exists. In this paper, a modified MPC scheme for constrained linear systems is described. An offine LMI-based iteration process is introduced to expand the stability region. At the same time, a database of feasible control sequences is generated offine so that stability can still be guaranteed in the case of computational time limitations. Simulation results illustrate the effectiveness of this new approach.
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