914 resultados para linear dynamic output feedback control


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In this work the chaotic behavior of a micro-mechanical resonator with electrostatic forces on both sides is suppressed. The aim is to control the system in an orbit of the analytical solution obtained by the Method of Multiple Scales. Two control strategies are used for controlling the trajectory of the system, namely: State Dependent Riccati Equation (SDRE) Control and Optimal Linear Feedback Control (OLFC). The controls proved effectiveness in controlling the trajectory of the system. Additionally, the robustness of each strategy is tested considering the presence of parametric errors and measurement noise in control. © 2012 American Institute of Physics.

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The performance of the optimal linear feedback control and of the state-dependent Riccati equation control techniques applied to control and to suppress the chaotic motion in the atomic force microscope are analyzed. In addition, the sensitivity of each control technique regarding to parametric uncertainties are considered. Simulation results show the advantages and disadvantages of each technique. © 2013 Brazilian Society for Automatics - SBA.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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A recent trend in networked control systems (NCSs) is the use of wireless networks enabling interoperability between existing wired and wireless systems. One of the major challenges in these wireless NCSs (WNCSs) is to overcome the impact of the message loss that degrades the performance and stability of these systems. Moreover, this impact is greater when dealing with burst or successive message losses. This paper discusses and presents the experimental results of a compensation strategy to deal with this burst message loss problem in which a NCS mathematical model runs in parallel with the physical process, providing sensor virtual data in case of packet losses. Running in real-time inside the controller, the mathematical model is updated online with real control signals sent to the actuator, which provides better reliability for the estimated sensor feedback (virtual data) transmitted to the controller each time a message loss occurs. In order to verify the advantages of applying this model-based compensation strategy for burst message losses in WNCSs, the control performance of a motor control system using CAN and ZigBee networks is analyzed. Experimental results led to the conclusion that the developed compensation strategy provided robustness and could maintain the control performance of the WNCS against different message loss scenarios.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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This work presents a strategy to control nonlinear responses of aeroelastic systems with control surface freeplay. The proposed methodology is developed for the three degrees of freedom typical section airfoil considering aerodynamic forces from Theodorsen's theory. The mathematical model is written in the state space representation using rational function approximation to write the aerodynamic forces in time domain. The control system is designed using the fuzzy Takagi-Sugeno modeling to compute a feedback control gain. It useds Lyapunov's stability function and linear matrix inequalities (LMIs) to solve a convex optimization problem. Time simulations with different initial conditions are performed using a modified Runge-Kutta algorithm to compare the system with and without control forces. It is shown that this approach can compute linear control gain able to stabilize aeroelastic systems with discontinuous nonlinearities.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Pós-graduação em Engenharia Elétrica - FEIS

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Engenharia Elétrica - FEIS

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.

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This dissertation presents the competitive control methodologies for small-scale power system (SSPS). A SSPS is a collection of sources and loads that shares a common network which can be isolated during terrestrial disturbances. Micro-grids, naval ship electric power systems (NSEPS), aircraft power systems and telecommunication system power systems are typical examples of SSPS. The analysis and development of control systems for small-scale power systems (SSPS) lacks a defined slack bus. In addition, a change of a load or source will influence the real time system parameters of the system. Therefore, the control system should provide the required flexibility, to ensure operation as a single aggregated system. In most of the cases of a SSPS the sources and loads must be equipped with power electronic interfaces which can be modeled as a dynamic controllable quantity. The mathematical formulation of the micro-grid is carried out with the help of game theory, optimal control and fundamental theory of electrical power systems. Then the micro-grid can be viewed as a dynamical multi-objective optimization problem with nonlinear objectives and variables. Basically detailed analysis was done with optimal solutions with regards to start up transient modeling, bus selection modeling and level of communication within the micro-grids. In each approach a detail mathematical model is formed to observe the system response. The differential game theoretic approach was also used for modeling and optimization of startup transients. The startup transient controller was implemented with open loop, PI and feedback control methodologies. Then the hardware implementation was carried out to validate the theoretical results. The proposed game theoretic controller shows higher performances over traditional the PI controller during startup. In addition, the optimal transient surface is necessary while implementing the feedback controller for startup transient. Further, the experimental results are in agreement with the theoretical simulation. The bus selection and team communication was modeled with discrete and continuous game theory models. Although players have multiple choices, this controller is capable of choosing the optimum bus. Next the team communication structures are able to optimize the players’ Nash equilibrium point. All mathematical models are based on the local information of the load or source. As a result, these models are the keys to developing accurate distributed controllers.

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Pulse-width modulation is widely used to control electronic converters. One of the most topologies used for high DC voltage/low DC voltage conversion is the Buck converter. It is obtained as a second order system with a LC filter between the switching subsystem and the load. The use of a coil with an amorphous magnetic material core instead of air core lets design converters with smaller size. If high switching frequencies are used for obtaining high quality voltage output, the value of the auto inductance L is reduced throughout the time. Then, robust controllers are needed if the accuracy of the converter response must not be affected by auto inductance and load variations. This paper presents a robust controller for a Buck converter based on a state space feedback control system combined with an additional virtual space variable which minimizes the effects of the inductance and load variations when a not-toohigh switching frequency is applied. The system exhibits a null steady-state average error response for the entire range of parameter variations. Simulation results are presented.

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Civil engineering structures such as floor systems with open-plan layout or lightweight footbridges are susceptible to excessive level of vibrations caused by human loading. Active vibration control (AVC) via inertial mass actuators has been shown to be a viable technique to mitigate vibrations, allowing structures to satisfy vibration serviceability limits. Most of the AVC applications involve the use of SISO (single input single-output) strategies based on collocated control. However, in the case of floor structures, in which mostof the vibration modes are locally spatially distributed, SISO or multi-SISO strategies are quite inefficient. In this paper, a MIMO (multi-inputs multi-outputs) control in decentralised and centralised configuration is designed. The design process simultaneously finds the placement of multiple actuators and sensors and the output feedback gains. Additionally, actuator dynamics, actuator nonlinearities and frequency and time weightings are considered into the design process. Results with SISO and decentralised and centralised MIMO control (for a given number of actuators and sensors) are compared, showing the advantages of MIMO control for floor vibration control.