Fuzzy Logic Control (fuzzy + logic_control)

Distribution by Scientific Domains

Selected Abstracts

The design of supervisory rule-based control in the operating theatre via an anaesthesia simulator

EXPERT SYSTEMS, Issue 1 2002
M. Mahfouf
The development of online drug administration strategies in operating theatres represents a highly safety-critical situation. The usefulness of different levels of simulation prior to clinical trials has been shown in previous studies in muscle relaxant anaesthesia. Thus, in earlier work on predictive self-tuning control for muscle relaxation a dual computer real-time simulation was undertaken, subsequent to algorithm validation via off-line simulation. In the present approach a supervised rule-based control algorithm is used. The control software was implemented on the actual machine to be used in theatre, while another computer acted as a real-time patient simulator. This set-up has further advantages of providing accurate timing and also finite data accuracy via the ADC/DAC interface, or the equivalent digital lines. Also, it provides for controller design fast simulation studies compared to the real-time application. In this paper, a new architecture which combines several hierarchical levels for control (a Mamdani-type fuzzy controller), adaptation (self-organizing fuzzy logic control) and performance monitoring (fault detection, isolation and accommodation) is developed and applied to a computer real-time simulation platform for muscle relaxant anaesthesia. Experimental results showed that the proposed algorithm fulfilled successfully the requirements for autonomy, i.e. automatic control, adaptation and supervision, and proved effective in dealing with the faults and disturbances which are normally encountered in operating theatres during surgery. [source]

Fuzzy controlled central heating system

Faruk Mendi
Abstract In this paper a comparison study was carried out in order to understand how two different systems, classical and fuzzy logic control of central heating affect the economy and comfort of private homes or offices. Also a literature review was done to help decide which one of these systems is more effective. The objective of the fuzzy controller heating system is to estimate the actual heat requirement of the house. It uses a total of five inputs, four of which are derived from energy consumption curve, using conventional digital filtering techniques; the fifth is the average outdoor temperature, whereas, the classical control system burns diesel type fuel in its furnace to heat the water supply (boiler). From the boiler, the hot water is distributed by a pipe system to the individual radiators in the house. Thereby, it is shown that the fuzzy controlled heating system is more effective, also it maximizes the economy and the comfort of the consumer. Copyright 2002 John Wiley & Sons, Ltd. [source]

An affordable modular mobile robotic platform with fuzzy logic control and evolutionary artificial neural networks

Maurice Tedder
Autonomous robotics projects encompass the rich nature of integrated systems that includes mechanical, electrical, and computational software components. The availability of smaller and cheaper hardware components has helped make possible a new dimension in operational autonomy. This paper describes a mobile robotic platform consisting of several integrated modules including a laptop computer that serves as the main control module, microcontroller-based motion control module, a vision processing module, a sensor interface module, and a navigation module. The laptop computer module contains the main software development environment with a user interface to access and control all other modules. Programming language independence is achieved by using standard input/output computer interfaces including RS-232 serial port, USB, networking, audio input and output, and parallel port devices. However, with the same hardware technology available to all, the distinguishing factor in most cases for intelligent systems becomes the software design. The software for autonomous robots must intelligently control the hardware so that it functions in unstructured, dynamic, and uncertain environments while maintaining an autonomous adaptability. This paper describes how we introduced fuzzy logic control to one robot platform in order to solve the 2003 Intelligent Ground Vehicle Competition (IGVC) Autonomous Challenge problem. This paper also describes the introduction of hybrid software design that utilizes Fuzzy Evolutionary Artificial Neural Network techniques. In this design, rather than using a control program that is directly coded, the robot's artificial neural net is first trained with a training data set using evolutionary optimization techniques to adjust weight values between neurons. The trained neural network with a weight average defuzzification method was able to make correct decisions to unseen vision patterns for the IGVC Autonomous Challenge. A comparison of the Lawrence Technological University robot designs and the design of the other competing schools shows that our platforms were the most affordable robot systems to use as tools for computer science and engineering education. 2004 Wiley Periodicals, Inc. [source]

Application of a fuzzy logic control system for continuous anaerobic digestion of low buffered, acidic energy crops as mono-substrate

P. Scherer
Abstract A fuzzy logic control (FLC) system was developed at the Hamburg University of Applied Sciences (HAW Hamburg) for operation of biogas reactors running on energy crops. Three commercially available measuring parameters, namely pH, the methane (CH4) content, and the specific gas production rate (spec. GPR,=,m3/kg VS/day) were included. The objective was to avoid stabilization of pH with use of buffering supplements, like lime or manure. The developed FLC system can cover most of all applications, such as a careful start-up process and a gentle recovery strategy after a severe reactor failure, also enabling a process with a high organic loading rate (OLR) and a low hydraulic retention time (HRT), that is, a high throughput anaerobic digestion process with a stable pH and CH4 content. A precondition for a high load process was the concept of interval feeding, for example, with 8 h of interval. The FLC system was proved to be reliable during the long term fermentation studies over 3 years in one-stage, completely stirred tank reactors (CSTR) with acidic beet silage as mono-input (pH 3.3,3.4). During fermentation of the fodder beet silage (FBS), a stable HRT of 6.0 days with an OLR of up to 15 kg,VS/m3/day and a volumetric GPR of 9 m3/m3/day could be reached. The FLC enabled an automatic recovery of the digester after two induced severe reactor failures. In another attempt to prove the feasibility of the FLC, substrate FBS was changed to sugar beet silage (SBS), which had a substantially lower buffering capacity than that of the FBS. With SBS, the FLC accomplished a stable fermentation at a pH level between 6.5 and 6.6, and a volatile fatty acid level (VFA) below 500 mg/L, but the FLC had to interact and to change the substrate dosage permanently. In a further experiment, the reactor temperature was increased from 41 to 50C. Concomitantly, the specific GPR, pH and CH4 dropped down. Finally, the FLC automatically enabled a complete recovery in 16 days. Biotechnol. Bioeng. 2009; 102: 736,748. 2008 Wiley Periodicals, Inc. [source]