Navegando por Assunto "Controle preditivo"

Agora exibindo 1 - 4 de 4

Acesso aberto (Open Access)
Augmentação estocástica com horizonte de predição estendido baseada no PID para um sistema multivariável
(Universidade Federal do Pará, 2019-10-25) CRUZ, Jahyrahã Leal dos Santos; SILVEIRA, Antonio da Silva; http://lattes.cnpq.br/1828468407562753
The objective of this research was to investigate and design a control system based on the Stochastic Augmentation with Extended Prediction Horizon using 10-steps ahead, consisting of the union of characteristics of a linear deterministic controller with a stochastic predictive controller, resulting in a control system with guaranteed robustness and with predictive, linear, and stochastic characteristics. For the application of the Stochastic Augmentation, the chosen controllers were the classic PID and the GMV in its incremental form, where the former was augmented resulting in a controller with extended prediction horizon, the AEHP. The classic PID controller in the discrete time domain is compared to AEHP. Both controllers were tested in simulations with a process model that represents the dynamics of a helicopter, denominated 2DOF Helicopter (H2DOF), produced by the Quanser company. The H2DOF is a multivariable system, whose model in the state space is transformed to the transfer function form, generating two coupled subsystems, one for the pitch angle and other to the yaw angle, in which the couplings influence were considered as disturbances in the controllers design stage. The transformation of the system model to the transfer function form reduced the complexity of multivariable system in the state space, allowing the use of a more simple control law. Furthermore, it was performed the pairing of input and output, to verify what output was more sensible the one specific input, by means of Relative Gain Array. And to prove the control system efficiency based in the Stochastic Augmentation with extended prediction horizon, simulations were realized using the software Matlab®, assessing the performance of extended prediction horizon, enduring the coupled dynamics, facing load disturbances and Gaussian disturbances. The essays were evaluated by robustness and performance indices. The predictive AEHP controller obtained better results for most indices with guaranteed robustness, compared to the discrete-time PID controller.
Acesso aberto (Open Access)
Controle MPC multivariável com restrições usando funções de Laguerre
(Universidade Federal do Pará, 2018-03-01) PINHEIRO, Tarcísio Carlos Farias; SILVEIRA, Antonio da Silva; http://lattes.cnpq.br/1828468407562753
This work presents a constrained multivariable model predictive controller using Laguerre Functions. This controller uses a set of orthonormal Laguerre networks for representation of the control trajectory within a control horizon. In order to demonstrate the advantages of applying this type of controller in MIMO (Multiple-Input and Multiple-Output) systems, the Laguerre Functions Functions are used to decrease the computational load used to calculate the optimal control. In addition, It improves the compromise between control signal viability and closed-loop performance of the system. The Laguerre Functions are also used in conjunction with Hildreth’s Quadratic Programming to find the optimal solution for the case where the control signal is constrained. The proposed controller presents advantages when compared to the classical model predictive control approach, where forward shift operators are used to predict the future trajectory of the control signal, leading to unsatisfactory solutions and a high computational load for cases where the control signal demands a long prediction horizon and a high closed-loop performance.It is also reported the practical testes with a robotic manipulator configured as a MIMO system with three inputs and three outputs and tests simulated with the Wood and Berry binary distillation column which is a MIMO system with two inputs and two outputs, also containing transport time delays. The tests aim to compare the controller results presented with the traditional predictive control approach and thereby demonstrate the advantages of the method using the Laguerre functions and their efficiency for MIMO systems.
Acesso aberto (Open Access)
Projeto de estabilizadores de sistemas elétricos de potência utilizando controle de variância mínima no espaço de estados
(Universidade Federal do Pará, 2018-01-24) CASTRO, Luís Augusto Mesquita de; ARAÚJO, Rejane de Barros; http://lattes.cnpq.br/8760830024389437; SILVEIRA, Antonio da Silva; http://lattes.cnpq.br/1828468407562753
The use of power system stabilizers is essential for reliable operation of large electrical systems. Most stabilizers in operation are designed using classical control techniques based on linearized power systems models. Although this type of stabilizer presents satisfactory performance for the damping of oscillations inherent in the power system, many studies show that use of adaptive and intelligent control techniques for the synthesis of the control law in these stabilizers can produce even better results. In this work it is investigated the performance of a predictive control strategy, of the minimum variance control type in the state space, GMVSS, applied to the damping of electromechanical oscillations in interconnected power systems. The design procedure is based on the premise that the controller structure is inherited from the design model, where estimated state variables, come into play in the synthesis of a state feedback control law. The complexity of the controller structure is then dictated by the complexity of the design model. This procedure differs from the original transfer function method, GMV, however matching exactly the same results. The most significant contribution of such a strategy is the simplicity of design due to the absence of the Diophantine equation in the procedure. The Diophantine equation is indirectly solved in a natural way by the problem formulation itself, from a Kalman filter obtained from an ARMAX state space representation. Finally, the synthesized control law is applied to the nonlinear system by means of numerical simulations using nonlinear models of the system, evaluating the characteristics of robustness and performance of the proposed controller via sensitivity functions, Nyquist diagram, poles and zeros map and performance indexes for the entire operating range. The results show that the predictive stabilizer is able to contribute positively to the damping of the most problematic oscillation modes, thus increasing the stability limits of the power system.
Acesso aberto (Open Access)
Técnica de controle preditivo baseado em modelo aplicada ao controle de tensão de um gerador síncrono - resultados experimentais
(2012-10) MOUTINHO, Marcelo Nascimento; BARRA JUNIOR, Walter; COSTA JÚNIOR, Carlos Tavares da; BARREIROS, José Augusto Lima
This paper presents the results of the experimental evaluation of a digital self-tuning predictive control methodology applied to the voltage control of a small-scale energy generation system. A recursive estimator based on the well known least-squares method is used in the identification stage of the proposed controller. The stage for calculation of the signal control method is performed with the Generalized Predictive Controller (GPC) algorithm. The experimental evaluation was performed using step perturbations applied in different operating conditions of the studied power system. For comparison purposes, the results of the evaluation of a self-tuning controller using the pole-placement method for the control signal formulation and three digital controllers with fixed parameters also will be presented.