19 resultados para Intelligent control systems
em Universidade Federal do Rio Grande do Norte(UFRN)
Resumo:
LOPES, Jose Soares Batista et al. Application of multivariable control using artificial neural networks in a debutanizer distillation column.In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING - COBEM, 19, 5-9 nov. 2007, Brasilia. Anais... Brasilia, 2007
Resumo:
This work develops a robustness analysis with respect to the modeling errors, being applied to the strategies of indirect control using Artificial Neural Networks - ANN s, belong to the multilayer feedforward perceptron class with on-line training based on gradient method (backpropagation). The presented schemes are called Indirect Hybrid Control and Indirect Neural Control. They are presented two Robustness Theorems, being one for each proposed indirect control scheme, which allow the computation of the maximum steady-state control error that will occur due to the modeling error what is caused by the neural identifier, either for the closed loop configuration having a conventional controller - Indirect Hybrid Control, or for the closed loop configuration having a neural controller - Indirect Neural Control. Considering that the robustness analysis is restrict only to the steady-state plant behavior, this work also includes a stability analysis transcription that is suitable for multilayer perceptron class of ANN s trained with backpropagation algorithm, to assure the convergence and stability of the used neural systems. By other side, the boundness of the initial transient behavior is assured by the assumption that the plant is BIBO (Bounded Input, Bounded Output) stable. The Robustness Theorems were tested on the proposed indirect control strategies, while applied to regulation control of simulated examples using nonlinear plants, and its results are presented
Resumo:
The sanitation companies from Brazil has a great challenge for the XXI century: seek to mitigate the rate of physical waste (water, chemicals and electricity) and financial waste caused by inefficient operating systems drinking water supply, considering that currently we already face, in some cases, the scarcity of water resources. The supply systems are increasingly complex as they seek to minimize waste and at the same time better serve the growing number of users. However, this technological change is to reduce the complexity of the challenges posed by the need to include users with higher quality and efficiency in services. A major challenge for companies of water supplies is to provide a good quality service contemplating reducing expenditure on electricity. In this situation we developed a research by a method that seeks to control the pressure of the distribution systems that do not have the tank in your setup and the water comes out of the well directly to the distribution system. The method of pressure control (intelligent control) uses fuzzy logic to eliminate the waste of electricity and the leaks from the production of pumps that inject directly into the distribution system, which causes waste of energy when the consumption of households is reduced causing the saturation of the distribution system. This study was conducted at Green Club II condominium, located in the city of Parnamirim, state of Rio Grande do Norte, in order to study the pressure behavior of the output of the pump that injects water directly into the distribution system. The study was only possible because of the need we had to find a solution to some leaks in the existing distribution system and the extensions of the respective condominium residences, which sparked interest in developing a job in order to carry out the experiments contained in this research
Resumo:
This work describes the development of a nonlinear control strategy for an electro-hydraulic actuated system. The system to be controlled is represented by a third order ordinary differential equation subject to a dead-zone input. The control strategy is based on a nonlinear control scheme, combined with an artificial intelligence algorithm, namely, the method of feedback linearization and an artificial neural network. It is shown that, when such a hard nonlinearity and modeling inaccuracies are considered, the nonlinear technique alone is not enough to ensure a good performance of the controller. Therefore, a compensation strategy based on artificial neural networks, which have been notoriously used in systems that require the simulation of the process of human inference, is used. The multilayer perceptron network and the radial basis functions network as well are adopted and mathematically implemented within the control law. On this basis, the compensation ability considering both networks is compared. Furthermore, the application of new intelligent control strategies for nonlinear and uncertain mechanical systems are proposed, showing that the combination of a nonlinear control methodology and artificial neural networks improves the overall control system performance. Numerical results are presented to demonstrate the efficacy of the proposed control system
Resumo:
LOPES, Jose Soares Batista et al. Application of multivariable control using artificial neural networks in a debutanizer distillation column.In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING - COBEM, 19, 5-9 nov. 2007, Brasilia. Anais... Brasilia, 2007
Resumo:
A self-flotator vibrational prototype electromechanical drive for treatment of oil and water emulsion or like emulsion is presented and evaluated. Oil production and refining to obtain derivatives is carried out under arrangements technically referred to as on-shore and off-shore, ie, on the continent and in the sea. In Brazil 80 % of the petroleum production is taken at sea and area of deployment and it cost scale are worrisome. It is associated, oily water production on a large scale, carrier 95% of the potential pollutant of activity whose final destination is the environment medium, terrestrial or maritime. Although diversified set of techniques and water treatment systems are in use or research, we propose an innovative system that operates in a sustainable way without chemical additives, for the good of the ecosystem. Labyrinth adsor-bent is used in metal spirals, and laboratory scale flow. Equipment and process patents are claimed. Treatments were performed at different flow rates and bands often monitored with control systems, some built, other bought for this purpose. Measurements of the levels of oil and grease (OGC) of efluents treaty remained within the range of legal framework under test conditions. Adsorbents were weighed before and after treatment for obtaining oil impregna-tion, the performance goal of vibratory action and treatment as a whole. Treatment technolo-gies in course are referenced, to compare performance, qualitatively and quantitatively. The vibration energy consumption is faced with and without conventional flotation and self-flotation. There are good prospects for the proposed, especially in reducing the residence time, by capillary action system. The impregnation dimensionless parameter was created and confronted with consecrated dimensionless parameters, on the vibrational version, such as Weber number and Froude number in quadratic form, referred to as vibrational criticality. Re-sults suggest limits to the vibration intensity
Resumo:
In this work a modification on ANFIS (Adaptive Network Based Fuzzy Inference System) structure is proposed to find a systematic method for nonlinear plants, with large operational range, identification and control, using linear local systems: models and controllers. This method is based on multiple model approach. This way, linear local models are obtained and then those models are combined by the proposed neurofuzzy structure. A metric that allows a satisfactory combination of those models is obtained after the structure training. It results on plant s global identification. A controller is projected for each local model. The global control is obtained by mixing local controllers signals. This is done by the modified ANFIS. The modification on ANFIS architecture allows the two neurofuzzy structures knowledge sharing. So the same metric obtained to combine models can be used to combine controllers. Two cases study are used to validate the new ANFIS structure. The knowledge sharing is evaluated in the second case study. It shows that just one modified ANFIS structure is necessary to combine linear models to identify, a nonlinear plant, and combine linear controllers to control this plant. The proposed method allows the usage of any identification and control techniques for local models and local controllers obtaining. It also reduces the complexity of ANFIS usage for identification and control. This work has prioritized simpler techniques for the identification and control systems to simplify the use of the method
Resumo:
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:
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:
This work presents an analysis of the control law based on an indirect hybrid scheme using neural network, initially proposed for O. Adetona, S. Sathanathan and L. H. Keel. Implementations of this control law, for a level plant of second order, was resulted an oscillatory behavior, even if the neural identifier has converged. Such results had motivated the investigation of the applicability of that law. Starting from that, had been made stability mathematical analysis and several implementations, with simulated plants and with real plants, for analyze the problem. The analysis has been showed the law was designed being despised some components of dynamic of the plant to be controlled. Thus, for plants that these components have a significant influence in its dynamic, the law tends to fail
Resumo:
The main objective of work is to show procedures to implement intelligent control strategies. This strategies are based on fuzzy scheduling of PID controllers, by using only standard function blocks of this technology. Then, the standardization of Foundation Fieldbus is kept. It was developed an environment to do the necessary tests, it validates the propose. This environment is hybrid, it has a real module (the fieldbus) and a simulated module (the process), although the control signals and measurement are real. Then, it is possible to develop controllers projects. In this work, a fuzzy supervisor was developed to schedule a network of PID controller for a non-linear plant. Analyzing its performance results to the control and regulation problem
Resumo:
Traditional irrigation projects do not locally determine the water availability in the soil. Then, irregular irrigation cycles may occur: some with insufficient amount that leads to water deficit, other with excessive watering that causes lack of oxygen in plants. Due to the nonlinear nature of this problem and the multivariable context of irrigation processes, fuzzy logic is suggested to replace commercial ON-OFF irrigation system with predefined timing. Other limitation of commercial solutions is that irrigation processes either consider the different watering needs throughout plant growth cycles or the climate changes. In order to fulfill location based agricultural needs, it is indicated to monitor environmental data using wireless sensors connected to an intelligent control system. This is more evident in applications as precision agriculture. This work presents the theoretical and experimental development of a fuzzy system to implement a spatially differentiated control of an irrigation system, based on soil moisture measurement with wireless sensor nodes. The control system architecture is modular: a fuzzy supervisor determines the soil moisture set point of each sensor node area (according to the soil-plant set) and another fuzzy system, embedded in the sensor node, does the local control and actuates in the irrigation system. The fuzzy control system was simulated with SIMULINK® programming tool and was experimentally built embedded in mobile device SunSPOTTM operating in ZigBee. Controller models were designed and evaluated in different combinations of input variables and inference rules base
Resumo:
This paper describes the study, computer simulation and feasibility of implementation of vector control speed of an induction motor using for this purpose the Extended Kalman Filter as an estimator of rotor flux. The motivation for such work is the use of a control system that requires no sensors on the machine shaft, thus providing a considerable cost reduction of drives and their maintenance, increased reliability, robustness and noise immunity as compared to control systems with conventional sensors
Resumo:
The control of industrial processes has become increasingly complex due to variety of factory devices, quality requirement and market competition. Such complexity requires a large amount of data to be treated by the three levels of process control: field devices, control systems and management softwares. To use data effectively in each one of these levels is extremely important to industry. Many of today s industrial computer systems consist of distributed software systems written in a wide variety of programming languages and developed for specific platforms, so, even more companies apply a significant investment to maintain or even re-write their systems for different platforms. Furthermore, it is rare that a software system works in complete isolation. In industrial automation is common that, software had to interact with other systems on different machines and even written in different languages. Thus, interoperability is not just a long-term challenge, but also a current context requirement of industrial software production. This work aims to propose a middleware solution for communication over web service and presents an user case applying the solution developed to an integrated system for industrial data capture , allowing such data to be available simplified and platformindependent across the network
Resumo:
The continuous gas lift method is the main artificial lifting method used in the oil industry for submarine wells, due to its robustness and the large range of flow rate that the well might operate. Nowadays, there is a huge amount of wells producing under this mechanism. This method of elevation has a slow dynamics due to the transients and a correlation between the injected gas rate and the of produced oil rate. Electronics controllers have been used to adjust many parameters of the oil wells and also to improve the efficiency of the gas lift injection system. This paper presents a intelligent control system applied to continuous gas injection in wells, based in production s rules, that has the target of keeping the wells producing during the maximum period of time, in its best operational condition, and doing automatically all necessary adjustments when occurs some disturbance in the system. The author also describes the application of the intelligent control system as a tool to control the flow pressure in the botton of the well (Pwf). In this case, the control system actuates in the surface control valve