Approximation paper, part 1

In this paper we discuss approximations between neural nets, fuzzy expert systems, fuzzy controllers, and continuous processes

Control Strategies of a Gas Turbine Generator: A Comparative Study

Gas turbine generators are commonly used in oil and gas industries due to their robustness and association with other operating systems in the combined cycles.  The electrical generators may become unstable under severe load fluctuations. For these raisons, maintaining the stability is paramount to ensure continuous functioninality.This paper deals with the modeling and simulation of a single shaft gas turbine generator using the model developed by Rowen and incorporating different types of controllers, viz a Zeigler- Nichols PID controller, a Fuzzy Logic Controller (FLC), FLC-PID and finally a hybridPID/FLC/FLC-PIDcontroller. The study was undertaken under Matlab / Simulink environment with data related to an in service power plant owned by Sonatrach, Algiers, Algeria. The results show that FLC-PID and hybrid tuned controllers provide the best time domain performances

A type-2 fuzzy modelling framework for aircraft taxi-time prediction

Knowing aircraft taxi-time precisely a-priori is increasingly important for any airport management system. This work presents a new approach for estimating and characterising the taxi-time of an aircraft based on historical information. The approach makes use of the interval type-2 fuzzy logic system, which provides more robustness and accuracy than the conventional type-1 fuzzy system. To compensate for erroneous modelling assumptions, the error distribution of the model is further analysed and an error compensation strategy is developed. Results, when tested on a real data set for Manchester Airport (U.K.), show improved taxi-time accuracy and generalisation capability over a wide range of modelling assumptions when compared with existing fuzzy systems and linear regression-based methods

Komputasi Parameter Adaptif Fuzzy Controller pada Sistem Pengering Kayu

Komputasi terhadap parameter kontrol menjadi penting dilakukan sesuai hasil pengukuran pada sebuah prototipe sistem pengering kayu, dengan tujuan untuk mendapatkan hasil yang lebih riil. Parameter yang dianalisis berkaitan dengan penerapan adaptif fuzzy controller (AFC) pada prototipe alat pengering kayu tenaga panas surya, yaitu berupa besaran control priode sistem untuk perlakukan yang berbeda-beda dari aktuator. AFC di implementasikan dengan mekanisme adaptasi yang diarahkan bekerja pada sistem ketika terjadi Perubahan humiditi drying dari sebuah jadwal pengeringan kayu sengon, tetapi dengan kondisi temperatur drying yang tetap. Mekanisme ini membandingkan model reference dan situasi riil ruang pengering sesuai kondisi cuaca untuk mendapatkan kondisi yang diinginkan. Hasil implementasi disajikan dalam bentuk look-up table dari perlakuan aktuator pada rule AFC

Telerobotic control of a mobile coordinated robotic server, executive summary

This interim report continues with the research effort on advanced adaptive controls for space robotics systems. In particular, previous results developed by the principle investigator and his research team centered around fuzzy logic control (FLC) in which the lack of knowledge of the robotic system as well as the uncertainties of the environment are compensated for by a rule base structure which interacts with varying degrees of belief of control action using system measurements. An on-line adaptive algorithm was developed using a single parameter tuning scheme. In the effort presented, the methodology is further developed to include on-line scaling factor tuning and self-learning control as well as extended to the multi-input, multi-output (MIMO) case. Classical fuzzy logic control requires tuning input scale factors off-line through trial and error techniques. This is time-consuming and cannot adapt to new changes in the process. The new adaptive FLC includes a self-tuning scheme for choosing the scaling factors on-line. Further the rule base in classical FLC is usually produced by soliciting knowledge from human operators as to what is good control action for given circumstances. This usually requires full knowledge and experience of the process and operating conditions, which limits applicability. A self-learning scheme is developed which adaptively forms the rule base with very limited knowledge of the process. Finally, a MIMO method is presented employing optimization techniques. This is required for application to space robotics in which several degrees-of-freedom links are commonly used. Simulation examples are presented for terminal control - typical of robotic problems in which a desired terminal point is to be reached for each link. Future activities will be to implement the MIMO adaptive FLC on an INTEL microcontroller-based circuit and to test the algorithm on a robotic system at the Mars Mission Research Center at North Carolina State University

Модифицированный предиктор Смита для объекта с переменной задержкой

A conventional Smith predictor presents poor stability when controlling systems with time-varying delay. In this paper, an improved adaptive PID-Smith predictor is proposed. It uses a PID controller as the primary controller as well as the estimator for unknown time delay. The goal is to ensure system stability and resistance to modeling errors. This article discusses two structures of the estimator unit - based on a neural network and on a fuzzy controller. In the first variant, the genetic algorithm is used to find the optimal parameters of the estimator in the autonomous mode. In the second variant, the fuzzy controller of the Takagi – Sugeno type uses a variety of models with different delay time. At each time point the error of output is calculated for all models. The output signal of the estimator is formed by the rule of defuzzification. Simulation results show the effectiveness of the proposed modification of the Smith predictor.При управлении системами с переменным временем задержки традиционный предиктор Смита обладает плохой устойчивостью. Предлагается разработка усовершенствованного адаптивного ПИД-Смит предиктора, который использует ПИД-регулятор в качестве основного контроллера и, кроме того, блок оценки неизвестного времени задержки. Цель состоит в том, чтобы гарантировать стабильность работы системы и устойчивость к ошибкам моделирования. Рассматриваются два варианта организации блока оценки: на базе нейронной сети и на базе нечеткого регулятора. В первом варианте генетический алгоритм применяется для поиска оптимальных параметров блока оценки в автономном режиме. Во втором варианте нечеткий регулятор типа Такаги — Сугено использует множество моделей с различным временем задержки. В каждый момент времени вычисляется ошибка выхода для каждой модели. Выходной сигнал блока оценки рассчитывается по правилу дефаззификации. Результаты моделирования показывают эффективность предложенного метода

Design of robust control for uncertain fuzzy quadruple-tank systems with time-varying delays

Producción CientíficaThe robust H∞ observer-based control design is addressed here for non-linear Takagi-Sugeno (T-S) fuzzy systems with time-varying delays, subject to uncertainties and external disturbances. This is motivated by the quadruple-tank with time delay control problem. The observer design methodology is based on constructing an appropriate Lyapunov–Krasovskii functional (LKF) for an augmented system formed from the original and the delayed states. The bilinear terms are transferred to the linear matrix inequalities, thanks to a change of variables which can be solved in one step. Furthermore, by employing the L2 performance index, the adverse effects of persistent bounded disturbances is largely avoided. The proposed method has the advantage of relating the controller and Lyapunov function to both the original and delayed states. Then, the controller and observer gains are obtained simultaneously by solving these inequalities with off-the-shelf software (Yalmip/MATLAB toolbox). Finally, an application to a simulated quadruple-tank system with time delay is carried out to demonstrate the benefits of the proposed technique, showing a compromise between controller simplicity and robustness that outperforms previous approaches.Publicación en abierto financiada por el Consorcio de Bibliotecas Universitarias de Castilla y León (BUCLE), con cargo al Programa Operativo 2014ES16RFOP009 FEDER 2014-2020 DE CASTILLA Y LEÓN, Actuación:20007-CL - Apoyo Consorcio BUCL