In this paper, we propose an atlas-based method for hippocampus-amygdala complex segmentation. An atlas is registered on all subjects and its transformation is calculated for each subject. This transformation is appli...
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Experimental validation of a two-stage method for the identification of physical system parameters from experimental data is presented. The first stage compresses the data as an empirical model and the second stage th...
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Experimental validation of a two-stage method for the identification of physical system parameters from experimental data is presented. The first stage compresses the data as an empirical model and the second stage then uses data extracted from the empirical model of the first stage within a non-linear estimation scheme to estimate the unknown physical parameters. The approach handles unstable systems using exponential weighting.
We present robust stability results for discrete-time nonlinear systems using certainty equivalence output feedback, particularly those that employ a model predictive control (MPC) formulation to generate the feedback...
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We present robust stability results for discrete-time nonlinear systems using certainty equivalence output feedback, particularly those that employ a model predictive control (MPC) formulation to generate the feedback control law. To this end, we discuss nominal robustness properties of general discrete-time nonlinear systems, including those that use discontinuous control laws in the feedback loop. This is important for systems employing MPC since the method can, and sometimes necessarily does, result in discontinuous control laws. Coupling assumptions of nominal robustness with certain uniform observability or detectability assumptions (for each of which we give an observer), we assert that, in particular, MPC is robustly globally asymptotically stabilizing when used in a certainty equivalence output feedback structure. Finally, we give an example to illuminate our results.
In this paper a model reference variable structure controller (VSC) for an active suspension system is designed. A half vehicle model is used in which, the vertical and pitch motions of the mass supported by the suspe...
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In this paper a model reference variable structure controller (VSC) for an active suspension system is designed. A half vehicle model is used in which, the vertical and pitch motions of the mass supported by the suspension and the vertical motion of the suspension masses are considered. Sliding mode controller is applied for the purpose of disturbance attenuation. Unit vector approach, which is a sliding mode control structure for multivariable systems, is used and a robust adaptive nonlinear controller is designed. A reduced-order observer is designed to use only output information. Robust eigenstructure assignment method is implemented in the line of sliding surface design. Simulation results verify the effectiveness of the proposed nonlinear controller scheme in comparison with the passive suspension system and also H ∞ technique. The output of the closed-loop system can also smoothly track a set point in a manner that the vertical position of vehicle may be regulated toward the desired point.
Among ac drives, the permanent magnet synchronous motor has been gaining popularity owing to its high torque to current ratio, large power to weight ratio, high efficiency, high power factor and robustness. Because of...
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Among ac drives, the permanent magnet synchronous motor has been gaining popularity owing to its high torque to current ratio, large power to weight ratio, high efficiency, high power factor and robustness. Because of its technical and economic advantages, Permanent Magnet Synchronous Motor drive technology is a serious contender for replacing the existing technologies. In this paper we report the utilization of a novel controller (BELBlC) based on emotion processing mechanism in brain. Our results show superior control characteristics especially very fast response, simple implementation and robustness with respect to disturbances and manufacturing imperfections. Our proposed method enables the designer to shape the response in accordance with the multiple objectives of his/her choice.
This paper presents a new method to solve the constrained unit commitment problem by applying ant colony optimization (ACO) based on the diversity control approach. The pheromone updating rule is modified to control t...
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This paper presents a new method to solve the constrained unit commitment problem by applying ant colony optimization (ACO) based on the diversity control approach. The pheromone updating rule is modified to control the diversification by adopting a simple mechanism for random selection in ACO. The proposed method is tested on the 10-unit test system with a scheduling time horizon of 24 hours. The numerical results show an economical saving in the total operating cost when compared to the previous literature results. Moreover, two types of the proposed diversity control technique have the features of easy implementation and a better convergence rate superior to a standard ACO.
This paper presents an efficient method to obtain the optimal power flow (OPF) problem under constrained emission dispatch by applying reactive tabu search (RTS) algorithm. The RTS is developed as a derivative-free op...
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This paper presents an efficient method to obtain the optimal power flow (OPF) problem under constrained emission dispatch by applying reactive tabu search (RTS) algorithm. The RTS is developed as a derivative-free optimization technique in solving constrained emission OPF problem significantly reduces the computational burden with the strategies that make the search process robust and fast. The effectiveness of the proposed approach has been demonstrated through the IEEE 30-bus, 6-generator, test system. The simulation results reveal that the proposed RTS can yield highly optimal solution and tan reduce computational execution time superior to a standard tabu search. Moreover, the proposed method provides better solution than previous literatures with promising results.
This paper reports an industrial application of principle component analysis to process abnormality detection in a sugar mill. The process under investigation is a continuous pan which is one of the most crucial proce...
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This paper reports an industrial application of principle component analysis to process abnormality detection in a sugar mill. The process under investigation is a continuous pan which is one of the most crucial processes in sugar production. Two sets of experimental results are obtained in this work: one is related to an artificially induced fault by a stuck valve; the other captures a naturally occurred fault due to equipment failure. The principle component analysis algorithm successfully detects both faults. Only the latter case is reported in this paper.
In this paper we report the utilization of a novel controller (BELBIC) based un emotion processing mechanism in brain for power system. Using the BELBIC controller, both transient stability and voltage regulation of p...
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In this paper we report the utilization of a novel controller (BELBIC) based un emotion processing mechanism in brain for power system. Using the BELBIC controller, both transient stability and voltage regulation of power systems are achieved. The special characteristic of this controller that makes it effective is its flexibility its five gain parameters that give good freedom for choosing favorite response. With this degree of freedom choosing of these parameters involves trade-off between overshoot and speed of response. The effectiveness of the proposed BELBIC controller is shown through some computer simulations on a (SMIB) power system.
This paper investigates digital modeling and control strategies applied to the voltage regulation of a microgenerator system, placed in the Electric Energy Generation Laboratory of Federal University of Para. Identifi...
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This paper investigates digital modeling and control strategies applied to the voltage regulation of a microgenerator system, placed in the Electric Energy Generation Laboratory of Federal University of Para. Identification parametric techniques are used in order to obtain a representative model for the controller design. With a suitable model, controllers of proportional integral type are designed, based on the root locus and fuzzy systems strategies, in order to improve the voltage regulation of the microgenerator system.
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