938 resultados para Programmable controllers
Resumo:
The Methods for compensation of harmonic currents and voltages have been widely used since these methods allow to reduce to acceptable levels the harmonic distortion in the voltages or currents in a power system, and also compensate reactive. The reduction of harmonics and reactive contributes to the reduction of losses in transmission lines and electrical machinery, increasing the power factor, reduce the occurrence of overvoltage and overcurrent. The active power filter is the most efficient method for compensation of harmonic currents and voltages. The active power filter is necessary to use current and voltage controllers loop. Conventionally, the current and voltage control loop of active filter has been done by proportional controllers integrative. This work, investigated the use of a robust adaptive control technique on the shunt active power filter current and voltage control loop to increase robustness and improve the performance of active filter to compensate for harmonics. The proposed control scheme is based on a combination of techniques for adaptive control pole placement and variable structure. The advantages of the proposed method over conventional ones are: lower total harmonic distortion, more flexibility, adaptability and robustness to the system. Moreover, the proposed control scheme improves the performance and improves the transient of active filter. The validation of the proposed technique was verified initially by a simulation program implemented in C++ language and then experimental results were obtained using a prototype three-phase active filter of 1 kVA
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Blind Source Separation (BSS) refers to the problem of estimate original signals from observed linear mixtures with no knowledge about the sources or the mixing process. Independent Component Analysis (ICA) is a technique mainly applied to BSS problem and from the algorithms that implement this technique, FastICA is a high performance iterative algorithm of low computacional cost that uses nongaussianity measures based on high order statistics to estimate the original sources. The great number of applications where ICA has been found useful reects the need of the implementation of this technique in hardware and the natural paralelism of FastICA favors the implementation of this algorithm on digital hardware. This work proposes the implementation of FastICA on a reconfigurable hardware platform for the viability of it's use in blind source separation problems, more specifically in a hardware prototype embedded in a Field Programmable Gate Array (FPGA) board for the monitoring of beds in hospital environments. The implementations will be carried out by Simulink models and it's synthesizing will be done through the DSP Builder software from Altera Corporation.
Resumo:
Conventional control strategies used in shunt active power filters (SAPF) employs real-time instantaneous harmonic detection schemes which is usually implements with digital filters. This increase the number of current sensors on the filter structure which results in high costs. Furthermore, these detection schemes introduce time delays which can deteriorate the harmonic compensation performance. Differently from the conventional control schemes, this paper proposes a non-standard control strategy which indirectly regulates the phase currents of the power mains. The reference currents of system are generated by the dc-link voltage controller and is based on the active power balance of SAPF system. The reference currents are aligned to the phase angle of the power mains voltage vector which is obtained by using a dq phase locked loop (PLL) system. The current control strategy is implemented by an adaptive pole placement control strategy integrated to a variable structure control scheme (VS¡APPC). In the VS¡APPC, the internal model principle (IMP) of reference currents is used for achieving the zero steady state tracking error of the power system currents. This forces the phase current of the system mains to be sinusoidal with low harmonics content. Moreover, the current controllers are implemented on the stationary reference frame to avoid transformations to the mains voltage vector reference coordinates. This proposed current control strategy enhance the performance of SAPF with fast transient response and robustness to parametric uncertainties. Experimental results are showing for determining the effectiveness of SAPF proposed control system
Resumo:
Technological evolution of industrial automation systems has been guided by the dillema between flexibilization and confiability on the integration between devices and control supervisory systems. However, there are few supervisory systems whose attributions can also comprehend the teaching of the communication process that happens behind this technological integration, where those which are available are little flexible about accessibility and reach of patterns. On this context, we present the first module of a didactic supervisory system, accessible through Web, applied on the teaching of the main fieldbus protocols. The application owns a module that automatically discovers the network topology being used and allows students and professionals of automation to obtain a more practical knowledgment by exchanging messages with a PLC, allowing those who are involved to know with more details the communication process of an automation supervisory system. By the fact of being available through Web, the system will allow a remote access to the PLC, comprehending a larger number of users. This first module is focused on the Modbus protocol (TCP and RTU/ASCII)
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This work deals with an on-line control strategy based on Robust Model Predictive Control (RMPC) technique applied in a real coupled tanks system. This process consists of two coupled tanks and a pump to feed the liquid to the system. The control objective (regulator problem) is to keep the tanks levels in the considered operation point even in the presence of disturbance. The RMPC is a technique that allows explicit incorporation of the plant uncertainty in the problem formulation. The goal is to design, at each time step, a state-feedback control law that minimizes a 'worst-case' infinite horizon objective function, subject to constraint in the control. The existence of a feedback control law satisfying the input constraints is reduced to a convex optimization over linear matrix inequalities (LMIs) problem. It is shown in this work that for the plant uncertainty described by the polytope, the feasible receding horizon state feedback control design is robustly stabilizing. The software implementation of the RMPC is made using Scilab, and its communication with Coupled Tanks Systems is done through the OLE for Process Control (OPC) industrial protocol
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A neuro-fuzzy system consists of two or more control techniques in only one structure. The main characteristic of this structure is joining one or more good aspects from each technique to make a hybrid controller. This controller can be based in Fuzzy systems, artificial Neural Networks, Genetics Algorithms or rein forced learning techniques. Neuro-fuzzy systems have been shown as a promising technique in industrial applications. Two models of neuro-fuzzy systems were developed, an ANFIS model and a NEFCON model. Both models were applied to control a ball and beam system and they had their results and needed changes commented. Choose of inputs to controllers and the algorithms used to learning, among other information about the hybrid systems, were commented. The results show the changes in structure after learning and the conditions to use each one controller based on theirs characteristics
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Foundation Fieldbus Industrial networks are the high standard technology which allows users to create complex control logic and totally decentralized. Although being so advanced, they still have some limitations imposed by their own technology. Attempting to solve one of these limitations, this paper describes how to design a Fuzzy controller in a Foundation Fieldbus network using their basic elements of programming, the functional blocks, so that the network remains fully independent of other devices other than the same instruments that constitute it. Moreover, in this work was developed a tool that aids this process of building the Fuzzy controller, setting the internal parameters of functional blocks and informing how many and which blocks should be used for a given structure. The biggest challenge in creating this controller is exactly the choice of blocks and how to arrange them in order to effectuate the same functions of a Fuzzy controller implemented in other kind of environment. The methodology adopted was to divide each one of the phases of a traditional Fuzzy controller and then create simple structures with the functional blocks to implement them. At the end of the work, the developed controller is compared with a Fuzzy controller implemented in a mathematical program that it has a proper tool for the development and implementation of Fuzzy controllers, obtaining comparatives graphics of performance between both
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This work proposes the design, the performance evaluation and a methodology for tuning the initial MFs parameters of output of a function based Takagi-Sugeno-Kang Fuzzy-PI controller to neutralize the pH in a stirred-tank reactor. The controller is designed to perform pH neutralization of industrial plants, mainly in units found in oil refineries where it is strongly required to mitigate uncertainties and nonlinearities. In addition, it adjusts the changes in pH regulating process, avoiding or reducing the need for retuning to maintain the desired performance. Based on the Hammerstein model, the system emulates a real plant that fits the changes in pH neutralization process of avoiding or reducing the need to retune. The controller performance is evaluated by overshoots, stabilization times, indices Integral of the Absolute Error (IAE) and Integral of the Absolute Value of the Error-weighted Time (ITAE), and using a metric developed by that takes into account both the error information and the control signal. The Fuzzy-PI controller is compared with PI and gain schedule PI controllers previously used in the testing plant, whose results can be found in the literature.
Resumo:
Fuzzy intelligent systems are present in a variety of equipment ranging from household appliances to Fuzzy intelligent systems are present in a variety of equipment ranging from household appliances to small devices such as digital cameras and cell phones being used primarily for dealing with the uncertainties in the modeling of real systems. However, commercial implementations of Fuzzy systems are not general purpose and do not have portability to different hardware platforms. Thinking about these issues this work presents the implementation of an open source development environment that consists of a desktop system capable of generate Graphically a general purpose Fuzzy controller and export these parameters for an embedded system with a Fuzzy controller written in Java Platform Micro Edition To (J2ME), whose modular design makes it portable to any mobile device that supports J2ME. Thus, the proposed development platform is capable of generating all the parameters of a Fuzzy controller and export it in XML file, and the code responsible for the control logic that is embedded in the mobile device is able to read this file and start the controller. All the parameters of a Fuzzy controller are configurable using the desktop system, since the membership functions and rule base, even the universe of discourse of the linguistic terms of output variables. This system generates Fuzzy controllers for the interpolation model of Takagi-Sugeno. As the validation process and testing of the proposed solution the Fuzzy controller was embedded on the mobile device Sun SPOT ® and used to control a plant-level Quanser®, and to compare the Fuzzy controller generated by the system with other types of controllers was implemented and embedded in sun spot a PID controller to control the same level plant of Quanser®
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In this work is proposed an indirect approach to the DualMode Adaptive Robust Controller (DMARC), combining the typicals transient and robustness properties of Variable Structure Systems, more specifically of Variable Structure Model Reference Adaptive Controller (VS-MRAC), with a smooth control signal in steady-state, typical of conventional Adaptive Controllers, as Model Reference Adaptive Controller (MRAC). The goal is to provide a more intuitive controller design, based on physical plant parameters, as resistances, inertia moments, capacitances, etc. Furthermore, with the objective to follow the evolutionary line of direct controllers, it will be proposed an indirect version for the Binary Model Reference Adaptive Controller (B-MRAC), that was the first controller attemptting to act as MRAC as well as VS-MRAC, depending on a pre-defined fixed parameter
Resumo:
The present work has as objective to present a method of project and implementation of controllers PID, based on industrial instrumentation. An automatic system of auto-tunning of controllers PID will be presented, for systems of first and second order. The software presented in this work is applied in controlled plants by PID controllers implemented in a CLP. Software is applied to make the auto-tunning of the parameters of controller PID of plants that need this tunning. Software presents two stages, the first one is the stage of identification of the system using the least square recursive algorithm and the second is the stage of project of the parameters of controller PID using the root locus algorithm. An important fact of this work is the use of industrial instrumentation for the accomplishment of the experiments. The experiments had been carried through in controlled real plants for controllers PID implemented in the CLP. Thus has not only one resulted obtained with theoreticians experiments made with computational programs, and yes resulted obtained of real systems. The experiments had shown good results gotten with developed software
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This work shows a study about the Generalized Predictive Controllers with Restrictions and their implementation in physical plants. Three types of restrictions will be discussed: restrictions in the variation rate of the signal control, restrictions in the amplitude of the signal control and restrictions in the amplitude of the Out signal (plant response). At the predictive control, the control law is obtained by the minimization of an objective function. To consider the restrictions, this minimization of the objective function is done by the use of a method to solve optimizing problems with restrictions. The chosen method was the Rosen Algorithm (based on the Gradient-projection). The physical plants in this study are two didactical systems of water level control. The first order one (a simple tank) and another of second order, which is formed by two tanks connected in cascade. The codes are implemented in C++ language and the communication with the system to be done through using a data acquisition panel offered by the system producer
Resumo:
A hierarchical fuzzy control scheme is applied to improve vibration suppression by using an electro-mechanical system based on the lever principle. The hierarchical intelligent controller consists of a hierarchical fuzzy supervisor, one fuzzy controller and one robust controller. The supervisor combines controllers output signal to generate the control signal that will be applied on the plant. The objective is to improve the performance of the electromechanical system, considering that the supervisor could take advantage of the different techniques based controllers. The robust controller design is based on a linear mathematical model. Genetic algorithms are used on the fuzzy controller and the supervisor tuning, which are based on non-linear mathematical model. In order to attest the efficiency of the hierarchical fuzzy control scheme, digital simulations were employed. Some comparisons involving the optimized hierarchical controller and the non-optimized hierarchical controller will be made to prove the efficiency of the genetic algorithms and the advantages of its use
Resumo:
This work addresses the dynamic control problem of two-wheeled differentially driven non-holonomic mobile robot. Strategies for robot positioning control and robot orientating control are presented. Such strategies just require information about the robot con¯guration (x, y and teta), which can be collected by an absolute positioning system. The strategies development is related to a change on the controlled variables for such systems, from x, y and teta to s (denoting the robot linear displacement) and teta, and makes use of the polar coordinates representation for the robot kinematic model. Thus, it is possible to obtain a linear representation for the mobile robot dynamic model and to develop such strategies. It is also presented that such strategies allow the use of linear controllers to solve the control problem. It is shown that there is flexibility to choice the linear controller (P, PI, PID, Model Matching techniques, others) to be implemented. This work presents an introduction to mobile robotics and their characteristics followed by the control strategies development and controllers design. Finally, simulated and experimental results are presented and commented
Resumo:
There are two main approaches for using in adaptive controllers. One is the so-called model reference adaptive control (MRAC), and the other is the so-called adaptive pole placement control (APPC). In MRAC, a reference model is chosen to generate the desired trajectory that the plant output has to follow, and it can require cancellation of the plant zeros. Due to its flexibility in choosing the controller design methodology (state feedback, compensator design, linear quadratic, etc.) and the adaptive law (least squares, gradient, etc.), the APPC is the most general type of adaptive control. Traditionally, it has been developed in an indirect approach and, as an advantage, it may be applied to non-minimum phase plants, because do not involve plant zero-pole cancellations. The integration to variable structure systems allows to aggregate fast transient and robustness to parametric uncertainties and disturbances, as well. In this work, a variable structure adaptive pole placement control (VS-APPC) is proposed. Therefore, new switching laws are proposed, instead of using the traditional integral adaptive laws. Additionally, simulation results for an unstable first order system and simulation and practical results for a three-phase induction motor are shown