Search

In this paper, the results carried out about a study over the possibilities of the Predictive Functional Control (PFC) are presented. The French professor Jacques Richalet and his collaborators developed the PFC. The results presented were obtained, when PFC is applied to industrial processes with complex dynamics such as high order, integral effects in the direct step that make the process asymptotically unstable in open loop and the undesirable phenomena of delay and inverse response. The main objective of the study is to demonstrate the potential offered by the PFC algorithm, in its simplestform, for the control of such processes. To this end, a methodology for synthesizing the PFC controller is developed based on the postulates and principles proposed by the precursors of the method, applied to several real case studies. In all cases, completely satisfactory results were obtained by means of simulation in Simulink-MatLab and finally the results of applying the method to the temperature control of the TCLab minilaboratory developed at the University of Utah are compared. This verifies the real possibilities of the FPC as a prominent alternative to control of real process. [ABSTRACT FROM AUTHOR]

Copyright of Scientia et Technica is the property of Scientia et Technica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Inge@UAN. Tendencias de la Ingeniería is the property of Universidad Antonio Narino and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents the procedure of tuning and simulation of an adaptive predictive control strategy to control the longitudinal and latero-directional movements of a unmanned aerial vehicle (UAV), using the Matlab ® - Simulink® platform. Uses the mathematical model of a UAV which are initially performed simulations of the system in open loop, identification is carried on online, and predictive control and PID controllers algorithms are implemented with the parameters obtained, to control the angle of pitch, roll and yaw. Control strategies used presented a good performance and manage to stabilize the aircraft properly. Finally, they are presented and analyzed the results of the performance of the system with predictive control and PID control using metrics of the integral of the error and of the work of the manipulated variable. [ABSTRACT FROM AUTHOR]

In this paper we present the time delay compensation through the design of control strategies like Filtered Smith Predictor, Modified Smith Predictor (MSP) and Predictive Control, for stable, unstable and non-minimal phase multivariable processes. Three case studies are used, where the behavior of each strategy is shown by simulation, according to the dynamic characteristics of the process. The simulation results are obtained by Matlab® and the comparison of the control strategies used is performed by the time performance of the controlled system, rejection of disturbances, monitoring of references and handling of uncertainties. In addition, a modification to the MSP is presented for the case of disturbance in the load. The simulation results show that the performance of the proposal is higher than the original MSP version. [ABSTRACT FROM AUTHOR]

This paper shows the design of a model based predictive controller to perform a speed control of an induction motor with squirrel cage rotor with a speed reference changing through the time. To achieve this goal the software MATLAB®/Simulink® were used. The control is performed employing an OPC server which acts like a gateway between MATLAB®/Simulink® and a Programmable Logic Controller (PLC). This PLC sends the control signal to a speed driver which handles the motor. The field bus employed for the communications between the Personal Computer (PC) and the PLC was Ethernet. The designed controller is compared with an auto-tuned PID controller from the PLC OMRON®. [ABSTRACT FROM AUTHOR]

Copyright of Revista Tecno Lógicas is the property of Instituto Tecnologico Metropolitano and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper the application of model based predictive control to batch sucrose crystallization process in single effect evaporator or vacuum pan of sugar industry is undertaken. Based on model developed by the author, witch is non-linear and time variant, with two input variable (feeding liquor and vapour temperature in the pan calender) and an out put variable (super saturation of mother liquor), by simulation method a linear model based state variables is obtained. Using that model a predictor on mod format of MATLAB is developed to be used in the design of required MPC. By means of simulation method the adequate character of the model to real MISO systems, considering the super saturation of mother liquor, where the sugar crystal grows, and the average diameter of sugar crystal as out put variables is tested. [ABSTRACT FROM AUTHOR]

Hybrid systems arise by the interaction between continuous dynamical systems and Discrete-event systems. This paper presents two modeling frameworks for this type of systems, in particular Mixed and Logical Dynamical (MLD) systems is explained. Then, model predictive control using MLD models is presented. The results are applied to a three-tank benchmark system as example. [ABSTRACT FROM AUTHOR]