Design of a fuzzy controller with simplified architecture

This work presents the design of a fuzzy controller with simplified architecture. This architecture tries to minimize the time processing used in? the several stages of hazy modeling of systems and processes. The basic procedures of fuzzification and defuzzification are simplified to the maximum while the inference procedures are computed in private way. Therefore, the simplified architecture allows a fast and easy configuration of the fuzzy controller.All rules that define the control actions are determined by inference procedures and the defuzzification is made automatically using a simplified algorithm. The fuzzy controller operation is standardized and the control actions are previously calculated For general-purpose application? ann results, the industrial systems of fluid pow cona ol will be considered.

Differential vascular adaptive response in spontaneously hypertensive and Wistar rats: Role of nitric oxide, and prehypertensive and hypertensive states

Stress-induced vascular adaptive response in SHR was investigated, focusing on the endothelium. Noradrenaline responses were studied in intact and denuded aortas from 6-week-old (prehypertensive) and 14-week-old (hypertensive) SHR and age-matched Wistar rats submitted or not to acute stress (20-min swimming and I-h immobilization 25 min apart), preceded or not by chronic stress (2 sessions 2 days apart of 1-h day immobilization for 5-consecutive days). Stress did not alter the reactivity of denuded aorta. Moreover, no alteration in the EC50 values was observed after stress exposure. In intact aortas, acute stress-induced hyporeactivity to noradrenaline similar between strains at both age. Chronic stress potentiated this adaptive response in 6- and 14-week-old Wistar but not in 6-week-old SHR, and did not alter the reactivity of 14-week-old SHR. Maximum response (g) in intact aortas [6-week-old: Wistar 3.25 +/- 0.12, Wistar/acute 1.95 +/- 0.12*, Wistar/chronic 1.36 +/- 0.21*(+), SHR 1.75 +/- 0.11, SHR/acute 0.88 +/- 0.08*, SHR/chronic 0.85 +/- 0.05*; 14-week-old: Wistar 3.83 +/- 0.13, Wistar/acute 2.72 +/- 0.13*, Wistar/chronic 1.91 +/- 0.19*', SHR 4.03 +/- 0.17, SHR/acute 2.26 +/- 0.12*, SHR/chronic 4.10 +/- 0.23; inside the same strain: *P < 0.05 relate to non-stressed rat, (+)P < 0.05 related to acute stressed rat; n = 6-18]. Independent of age and strain, L-NAME and endothelium removal abolished the stress-induced aorta hyporeactivity. Conclusion: the vascular adaptive response to stress is impaired in SHR, independently of the hypertensive state. Moreover, this vascular adaptive response is characterized by endothelial nitric oxide-system hyperactivity in both strains. (c) 2006 Elsevier B.V. All rights reserved.

Lógica fuzzy na avaliação da fertilidade do solo e produtividade do café conilon

The objective of this study was to analyze, using the geoestatistic and a system of classification fuzzy, the fertility of an experimental area with base in chemical attributes of the soil and its relationship with the productivity of the conilon coffee. The study was accomplished in the experimental farm of the INCAPER - ES. The soil samples were collected in the depth of 0 - 0.2 m, being analyzed the attributes: matches, potassium, calcium and magnesium, aluminum, sum of bases, cation exchange capacity (pH 7), and saturation percentage. The data were submitted to a descriptive, exploratory, and geostatistical analysis. A system of fuzzy classification was applied using the attributes described to infer about the fertility of the soil and its relationship with the productivity of the culture. The fertility possibility presented positive spatial relationship with the productivity of the culture, with higher values of this where the possibility of fertile soil is superior.

Urban Traffic Control and Monitoring - An Approach for the Brazilian Intelligent Cities Project

This paper describes an urban traffic control system which aims at contributing to a more efficient traffic management system in the cities of Brazil. It uses fuzzy sets, case-based reasoning, and genetic algorithms to handle dynamic and unpredictable traffic scenarios, as well as uncertain, incomplete, and inconsistent information. The system is composed by one supervisor and several controller agents, which cooperate with each other to improve the system's results through Artificial Intelligence Techniques.

A hierarchy of adaptive (X)over-bar control charts

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Fuzzy distributed artificial intelligence systems

In this paper, we introduce a DAI approach called hereinafter Fuzzy Distributed Artificial Intelligence (FDAI). Through the use of fuzzy logic, we have been able to develop mechanisms that we feel may effectively improve current DAI systems, giving much more flexibility and providing the subsidies which a formal theory can bring. The appropriateness of the FDAI approach is explored in an important application, a fuzzy distributed traffic-light control system, where we have been able to aggregate and study several issues concerned with fuzzy and distributed artificial intelligence. We also present a number of current research directions necessary to develop the FDAI approach more fully.

Fuzzy sets in distributed traffic control

The task of controlling urban traffic requires flexibility, adaptability and handling uncertain information spread through the intersection network. The use of fuzzy sets concepts convey these characteristics to improve system performance. This paper reviews a distributed traffic control system built upon a fuzzy distributed architecture previously developed by the authors. The emphasis of the paper is on the application of the system to control part of Campinas downtown area. Simulation experiments considering several traffic scenarios were performed to verify the capabilities of the system in controlling a set of coupled intersections. The performance of the proposed system is compared with conventional traffic control strategies under the same scenarios. The results obtained show that the distributed traffic control system outperforms conventional systems as far as average queues, average delay and maximum delay measures are concerned.

Immunological alterations in patients with primary tumors in central nervous system

Natural killer (NK) cells play an important role in immune surveillance against tumors. The present work aimed to study the cytotoxic activity of NK cells and T cell subsets in peripheral blood of 13 patients with primary tumors in central nervous system (CNS). As controls 29 healthy subjects with the age range equivalent to the patients were studied. The methods employed were: a) determination of cytotoxic activity of NK cells towards K562 target cells, evaluated by single cell-assay; b) enumeration of CD3+ lymphocytes and their CD4+ and CD8+ subsets defined by monoclonal antibodies; c) the identification of tumors were done by histologic and immunochemistry studies. The results indicated that adults and children with tumor in CNS display reduced percentage of total T cells, helper/inducer subset and low helper/suppressor ratio. The cytotoxic activity of NK cells was decreased in patients with CNS tumors due mainly to a decrease in the proportion of target-binding lymphocytes. These results suggest that cytotoxic activity of NK cells may be affected by the immunoregulatory disturbances observed in patients with primary tumors in CNS.

New approach of induction machine drive using an adaptive digital PID controller with gain planning based on artificial neural networks

The present work introduces a new strategy of induction machines speed adjustment using an adaptive PID (Proportional Integral Derivative) digital controller with gain planning based on the artificial neural networks. This digital controller uses an auxiliary variable to determine the ideal induction machine operating conditions and to establish the closed loop gain of the system. The auxiliary variable value can be estimated from the information stored in a general-purpose artificial neural network based on CMAC (Cerebellar Model Articulation Controller).

Novos resultados sobre a estabilidade e controle de sistemas nao-lineares utilizando modelos fuzzy e LMI

Relaxed conditions for the stability study of nonlinear, continuous and discrete-time systems given by fuzzy models are presented. A theoretical analysis shows that the proposed method provides better or at least the same results of the methods presented in the literature. Digital simulations exemplify this fact. These results are also used for the fuzzy regulators design. The nonlinear systems are represented by the fuzzy models proposed by Takagi and Sugeno. The stability analysis and the design of controllers are described by LMIs (Linear Matrix Inequalities), that can be solved efficiently by convex programming techniques. The specification of the decay rate, constraints on control input and output are also described by LMIs. Finally, the proposed design method is applied in the control of an inverted pendulum.

A fast electric load forecasting using adaptive neural networks

This work presents a procedure for electric load forecasting based on adaptive multilayer feedforward neural networks trained by the Backpropagation algorithm. The neural network architecture is formulated by two parameters, the scaling and translation of the postsynaptic functions at each node, and the use of the gradient-descendent method for the adjustment in an iterative way. Besides, the neural network also uses an adaptive process based on fuzzy logic to adjust the network training rate. This methodology provides an efficient modification of the neural network that results in faster convergence and more precise results, in comparison to the conventional formulation Backpropagation algorithm. The adapting of the training rate is effectuated using the information of the global error and global error variation. After finishing the training, the neural network is capable to forecast the electric load of 24 hours ahead. To illustrate the proposed methodology it is used data from a Brazilian Electric Company. © 2003 IEEE.

Isolated Richter's syndrome in central nervous system: Case report

Diffuse large cell non Hodgkin's lymphoma associated with chronic lymphoid leukemia (CLL), or Richter's syndrome, is a rare and serious complication. Isolated Richter's syndrome in the central nervous system is very rare; only 12 cases have been reported. We describe a 74-year-old patient with diffuse large cell non Hodgkin's lymphoma in the right frontal region with the appearance of multiform glioblastoma.

Fuzzy logic to predict thermal damages of ground parts

One of the critical problems in implementing an intelligent grinding process is the automatic detection of workpiece surface burn. This work uses fuzzy logic as a tool to classify and predict burn levels in the grinding process. Based on acoustic emission signals, cutting power, and the mean-value deviance (MVD), linguistic rules were established for the various burn situations (slight, intermediate, severe) by applying fuzzy logic using the Matlab Toolbox. Three practical fuzzy system models were developed. The first model with two inputs resulted only in a simple analysis process. The second and third models have an additional MVD statistic input, associating information and precision. These two models differ from each other in terms of the rule base developed. The three developed models presented valid responses, proving effective, accurate, reliable and easy to use for the determination of ground workpiece burn. In this analysis, fuzzy logic translates the operator's human experience associated with powerful computational methods.

Fuzzy environmental quality index

This paper presents the construction of a fuzzy environmental quality index for decision support in municipal environmental management. Five groups of indicators were selected in order to obtain an equation that best represented reality in terms of environmental quality. The calculation was carried out using fuzzy mathematical concepts, with the aid of the package Fuzzy Logical Toolbox 2.1 for Matlab ® 6.1, which provides functions and some applications of the theory of fuzzy sets. The work seeks to create a method of inference concerning the nature of urban areas that are unsustainable with respect to the environment, an issue that is often relegated to the background during public policy discussions. The development of this index, together with its implementation and dissemination, could improve public awareness of environmental issues, and promote mobilization towards the use of best practices in local development. © 2010 IEEE.

Estabilização de sistemas fuzzy T-S incertos usando realimenta̧ão derivativa

In some practical problems, for instance, in the suppression of vibration in mechanical systems, the state-derivative signals are easier to obtain than the state signals. Thus, a method for state-derivative feedback design applied to uncertain nonlinear systems is proposed in this work. The nonlinear systems are represented by Takagi-Sugeno fuzzy models during the modeling of the problem, allowing to use Linear Matrix Inequalities (LMIs) in the controller design. This type of modeling ease the control design, because, LMIs are easily solved using convex programming technicals. The control design aimed at system stabilisation, with or without bounds on decay rate. The efficiency of design procedure is illustrated through a numerical example.