Applications of Model Predictive Controllers in a Sugar Factory

INTERNATIONAL SYMPOSIUM ON ADVANCED CONTROL OF CHEMICAL PROCESSThis paper presents two applications of Model Predictive Control in a sugar factory: temperature control in the diffusion process and density control in the wastewater treatment plant. The implementation is done using a Generalized Predictive Controller (GPC) designed for a wide class of industrial process, with the same computational requirements as a PID routine and embedded in the existing control system. The processes have in common the existence of long and uncertain dead times, therefore the original GPC algorithm is improved by the use of the T polynomial, which increases the stability robustness by filtering the predictions.Comisión Interministerial de Ciencia y Tecnología (CICYT) TAP 96-0884Comisión Interministerial de Ciencia y Tecnología (CICYT) TAP 98-0541Comisión Interministerial de Ciencia y Tecnología (CICYT) 1FD97-083

Application of simple cascade GPC with robust behaviour to a sugar refinery

This paper presents the application of a Generalized Pre dictive Controller (GPC) to sludge density control in a sugar factory. The loop is controlled by a cascade strategy where both the master and the slave controllers are predic tive ones. The control law is extremely simple to compute and the tuning is straightforward since a method to im plement GPC previously developed by the authors which is very simple to implement and tune has been used. The controllers are embedded in the existing control system needing the same computational requirements as pid rou tines. The original GPC algorithm is improved by the use of the socalled T polynomial which increases the stabil ity robustness by ltering the predictions in order to cope with model uncertainties and di erent process dynamics caused by changes in the process operating pointsMinisterio de Ciencia y Tecnología s TAP 96-884 (CICYT)Ministerio de Ciencia y Tecnología TAP 95-370 (CICYT

Implementation of GPC for integrating··processes with low computational. Requirenients

This paper presents a straightforward method for im­plementing generalized predictive self-tuning controllers with low computational requirements. The method makes use of the fact that a generalized predictive con­troller results in a control law that can be described with few parameters. The controller has been developed for processes having an integral effect. A set of simple functions relating the controller parameters to the process parameters has been obtained. With this set of functions either a fixed or a selftuning GPC can be implemented in a straight­forward manner. An application to the control of a DC motor is given

Mass spectrum and decay constants of radially excited vector mesons

We calculate the masses and weak decay constants of flavorless ground and radially excited $J^P=1^-$ mesons and the corresponding quantities for the K^*, within a Poincar\'e covariant continuum framework based on the Bethe-Salpeter equation. We use in both, the quark's gap equation and the meson bound-state equation, an infrared massive and finite interaction in the leading symmetry-preserving truncation. While our numerical results are in rather good agreement with experimental values where they are available, no single parametrization of the QCD inspired interaction reproduces simultaneously the ground and excited mass spectrum, which confirms earlier work on pseudoscalar mesons. This feature being a consequence of the lowest truncation, we pin down the range and strength of the interaction in both cases to identify common qualitative features that may help to tune future interaction models beyond the rainbow-ladder approximation

Volterra Model Based Predictive Control, application to a Pem Fue Cell

14th Nordic Process Control Workshop - Espoo, Finland Duration: 23 Aug 2007 → 25 Aug 2007This paper presents a non linear model predictive controller for a PEM fuel cell for which the starvation control is the main objective. A second order Volterra model for control is obtained using input/output data for which the power supplied by the fuel cell is considered as a measurable disturbance. The controller developed allows to solve the nonlinear objective function in a way that it can be actually implemented in fast systems like Fuel cells. The use of a nonlinear controller is justified while comparing the outcome obtained with a linear controller of the same class

A Robust Adaptive Dead-Time Compensator with Application to A Solar Collector Field

This paper describes an easy-to-use PI controller with dead-time compensation that presents robust behaviour and can be applied to plants with variable dead-time. The formulation is based on an adaptive Smith predictor structure plus the addition of a filter acting on the error between the output and its prediction in order to improve robustness. The implementation of the control law is straightforward, and the filter needs no adjustment, since it is directly related to the plant dead-time. An application to an experimentally validated nonlinear model of a solar plant shows that this controller can improve the performance of classical PID controllers without the need of complex calculations.Ministerio de Ciencia y Tecnología TAP95-37

Torque distribution strategy for a four In-wheel fully electric car

Jornadas de Automática, 2 - 4 de septiembre de 2015. BilbaoElectromobility promises to have a strong impact in several aspects of our life: introducing new means of transport concepts, proposing new business models and allowing to create new vehicle configurations impossible with traditional combustion engines. Regarding the latter, this paper presents a novel torque distribution strategy for a 4 in-wheel electric vehicle which aims to reduce the total longitudinal slip. The control strategy is designed off-line supported by a simulator and tested both in simulation (with a different model from the used for designing) as well as on a real sized prototype. The results show that the total longitudinal slip is successfully reduced after applying the control strategy and additionally, the radius described by the vehicle while cornering is slightly closer to the theoretical Ackerman radius.Ministerio de Economía y Competitividad DPI2013-46912-C2-

Development and experimental evaluation of the control system of a hybrid fuel cell vehicle

This work presents the development and experimental evaluation of a Fuel Cell Hybrid Vehicle, focusing on the control system. The main objective of this paper is to present a real vehicle which has been designed in order to demonstrate the feasibility of the use of hydrogen as an energy source for automotive applications. The paper describes the components that are integrated in the vehicle and presents several experimental results obtained during normal operation. A control system is designed and tested in order to perform all the operations related to the coordinated operation of the fuel cell, the intermediate electrical storage and the power train. Its main task is to compute the power that must be demanded to the fuel cell in real time. This computation is done in order to satisfy the power demand of the electric motor taking into account the state of charge of the batteries and the operating regime of the fuel cell. This is accomplished by manipulating the electronic converter which regulate the current that the fuel cell supplies to the batteries.Ministerio de Ciencia y Tecnología DPI2007-66718-C04-0

Solar Thermal Plants Integration in Smart Grids

Solar energy penetration has been increasingly growing in recent years. Since solar energy is intermittent its integration in existing grids is difficult. This paper deals with the optimal integration of solar power plants in grids. The paper proposes a modification of energy hubs which allows to solve the optimization problem with a mixed integer programming algorithm in a distributed way. An introductory simulation study case is givenMinisterio de Educación DPI2008-05818Junta de Andalucía P07-TEP-02720Comisión Europea HD-MP

Min-Max Predictive Control of a Pilot Plant using a QP Approach

47th IEEE Conference on Decision and Control 9-11 Dec. 2008The practical implementation of min-max MPC (MMMPC) controllers is limited by the computational burden required to compute the control law. This problem can be circumvented by using approximate solutions or upper bounds of the worst possible case of the performance index. In a previous work, the authors presented a computationally efficient MMMPC control strategy in which a close approximation of the solution of the min-max problem is computed using a quadratic programming problem. In this paper, this approach is validated through its application to a pilot plant in which the temperature of a reactor is controlled. The behavior of the system and the controller are illustrated by means of experimental results