945 resultados para Sistemas de controle linear
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With the technology progess, embedded systems using adaptive techniques are being used frequently. One of these techniques is the Variable Structure Model- Reference Adaptive Control (VS-MRAC). The implementation of this technique in embedded systems, requires consideration of a sampling period which if not taken into consideration, can adversely affect system performance and even takes the system to instability. This work proposes a stability analysis of a discrete-time VS-MRAC accomplished for SISO linear time-invariant plants with relative degree one. The aim is to analyse the in uence of the sampling period in the system performance and the relation of this period with the chattering and system instability
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This paper presents a methodology for solving a set of linear sparse equations on vector computers. The new methodology is able to exploit the matrix and vector sparsities. The implementation was made on a CRAY Y-MP 2E/232 computer and the results were taken from electric power systems with 118, 320, 725 and 1729 buses. The proposed methodology was compared with three previous methods and the results show the superior performance of the new one.
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This work presents an algorithm for the security control of electric power systems using control actions like generation reallocation, determined by sensitivity analysis (linearized model) and optimization by neural networks. The model is developed taking into account the dynamic network aspects. The preventive control methodology is developed by means of sensitivity analysis of the security margin related with the mechanical power of the system synchronous machines. The reallocation power in each machine is determined using neural networks. The neural network used in this work is of Hopfield type. These networks are dedicated electric circuits which simulate the constraint set and the objective function of an optimization problem. The advantage of using these networks is the higher speed in getting the solutions when compared to conventional optimization algorithms due to the great convergence rate of the process and the facility of the method parallelization. Then, the objectives are: formulate and investigate these networks implementations in determining. The generation reallocation in digital computers. Aiming to illustrate the proposed methodology an application considering a multi-machine system is presented.
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This paper presents the Benders decomposition technique and Branch and Bound algorithm used in the reactive power planning in electric energy systems. The Benders decomposition separates the planning problem into two subproblems: an investment subproblem (master) and the operation subproblem (slave), which are solved alternately. The operation subproblem is solved using a successive linear programming (SLP) algorithm while the investment subproblem, which is an integer linear programming (ILP) problem with discrete variables, is resolved using a Branch and Bound algorithm especially developed to resolve this type of problem.
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Given a linear time-invariant plant Gol(s) with one input and q outputs, where q > 1, a method based on the Routh-Hurwitz Stability Criterion is proposed to obtain a constant tandem matrix F ∈ ℝq, such that FGOl(s) is a minimumphase system. From this solution, the system FGol(s) is represented in state space by {A, B, FC} and a constant output feedback matrix K0 ∈ ℝ is obtained such that the feedback system {A - BK0C, B, FC} is Strictly Positive Real (SPR). The proposed procedure offers necessary and sufficient conditions for both problems. Initially, the general case, with a generic q, is analyzed. Following, the particular cases q = 2 and q = 3 are studied.
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In some practical problems, for instance, in the suppression of vibration in mechanical systems, the state-derivative signals are easier to obtain than the state signals. Thus, a method for state-derivative feedback design applied to uncertain nonlinear systems is proposed in this work. The nonlinear systems are represented by Takagi-Sugeno fuzzy models during the modeling of the problem, allowing to use Linear Matrix Inequalities (LMIs) in the controller design. This type of modeling ease the control design, because, LMIs are easily solved using convex programming technicals. The control design aimed at system stabilisation, with or without bounds on decay rate. The efficiency of design procedure is illustrated through a numerical example.
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The maintenance of a given body orientation is obtained by the complex relation between sensory information and muscle activity. Therefore, this study purpose was to review the role of visual, somatosensory, vestibular and auditory information in the maintenance and control of the posture. Method. a search by papers for the last 24 years was done in the PubMed and CAPES databases. The following keywords were used: postural control, sensory information, vestibular system, visual system, somatosensory system, auditory system and haptic system. Results. the influence of each sensory system and its integration were analyzed for the maintenance and control of the posture. Conclusion. the literature showed that there is information redundancy provided by sensory channels. Thus, the central nervous system chooses the main source for the posture control.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Engenharia Elétrica - FEIS
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)