Comparison of Intelligent Fuzzy Controller and Fuzzy Rule Suram Algorithms in the Drying Process

Both the Intelligent Fuzzy Controller and Suram Fuzzy Rule are using a look-up table such as defuzzification analysis, which is based on weather variables, namely ambient temperature and ambient humidity for a drying process. State variable membership functions are expressed in terms of error values and error changes with typical triangular maps and trapezoidal maps. An Intelligent fuzzy controller is a hybrid controller which consists of an optimal fuzzy controller, fuzzy controller, and adaptive fuzzy controller. Membership function design is used to build the algorithm process. The algorithm process was developed based on the input-output knowledge pair for the drying process. The membership function must be stable and flexible with respect to weather and performance derived from the acquisition process, time constants, and system delays. The developed control system involves temperature control in different zones and ambient humidity. The system model was developed using a system identification scheme based on online input/output data and knowledge gathered through extensive testing. The knowledge base of fuzzy tuners is derived from drying schedules for certain wood specimens. The intelligent fuzzy control algorithm is used for scheduling the controller on various drying schedules. The results show that the proposed approach to overall control has great potential for performance improvement when applied to other industrial kilns. An intelligent fuzzy controller is also implemented, and its performance is compared with conventional controllers, it is more smooth, robust and controllable. On the other hand, the Suram fuzzy rule is an algorithm developed to control a drying system using diesel as an energy source by modifying the value of the fuzzy membership function [0.5,1]; and has been developed taking into account the wind speed in the drying process. The comparison results show that the Fuzzy Rule Suram is more efficient than the Intelligent Fuzzy Controller in terms of the use of electrical energy, by maximizing the use of solar energy

Online Intelligent Controllers for an Enzyme Recovery Plant: Design Methodology and Performance

This paper focuses on the development of intelligent controllers for use in a process of enzyme recovery from pineapple rind. The proteolytic enzyme bromelain (EC 3.4.22.4) is precipitated with alcohol at low temperature in a fed-batch jacketed tank. Temperature control is crucial to avoid irreversible protein denaturation. Fuzzy or neural controllers offer a way of implementing solutions that cover dynamic and nonlinear processes. The design methodology and a comparative study on the performance of fuzzy-PI, neurofuzzy, and neural network intelligent controllers are presented. To tune the fuzzy PI Mamdani controller, various universes of discourse, rule bases, and membership function support sets were tested. A neurofuzzy inference system (ANFIS), based on Takagi-Sugeno rules, and a model predictive controller, based on neural modeling, were developed and tested as well. Using a Fieldbus network architecture, a coolant variable speed pump was driven by the controllers. The experimental results show the effectiveness of fuzzy controllers in comparison to the neural predictive control. The fuzzy PI controller exhibited a reduced error parameter (ITAE), lower power consumption, and better recovery of enzyme activity

Identification and Study of Performance of Controllers on Heat Exchanger

This work is concerned with the identification of transfer function models for heat exchanger using system identification by selecting linear parametric models ARX, ARMAX, and according to the process requirement product temperature of the heat exchanger system has to be maintain at a desired set point. For this, firstly some conventional controllers like standard PID, Feed Forward with the feedback PID, IMC, and internal model based PID controllers were used. For the design of Feed Forward controller considered the disturbances as variation of the input flow. Due to some lower performance specifications and slow response time of conventional control techniques, intelligent controllers like fuzzy PID controller and FOPID controller using PSO algorithm are developed. These intelligent controllers maintains the temperature of the outlet fluid at a desired set point in the shortest possible time regardless of process disturbances, load, device saturation and nonlinearity

A DESIGN STUDY OF HEAT EXCHANGER PROCESS CONTROL BETWEEN CONVENTIONAL AND MAMDANI'S FUZZY LOGIC CONTROLLERS

A heat exchanger is a piece of equipment that continually transfers heat from one medium to another in order to carry process energy. In order to ensure its smooth operation, modeling and simulation of the system can be made so that its performance can be analyzed and improved. The scope of this study is more on simulation and software implementation of the control system design by using MATLAB. The main issue tackle in this study is to improve the performance of the heat exchanger process control. In this study, the heat exchanger is modeled using an empirical model to simulate the heat exchanger temperature response. A controller is then designed for the process using two approaches, one using a conventional PI method and another based on a fuzzy logic controller employing Mamdani inference method as an alternative approach. From the results obtained, it has been proven that both controllers are proven stable with good output temperature response. The responses of both controllers are further scrutinized where the fuzzy logic controller is shown to have better control performance compared to the PI controller. As a conclusion, intelligent control is better than the conventional PID control

Extruder for food product (otak–otak) with heater and roll cutter

Food extrusion is a form of extrusion used in food industries. It is a process by which a set of mixed ingredients are forced through an opening in a perforated plate or die with a design specific to the food, and is then cut to a specified size by blades [1]. Summary of the invention principal objects of the present invention are to provide a machine capable of continuously producing food products having an’ extruded filler material of meat or similarity and an extruded outer covering of a moldable food product, such as otak-otak, that completely envelopes the filler material

Neural Networks for Modeling and Control of Particle Accelerators

We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.Comment: 21 p

A model-free control strategy for an experimental greenhouse with an application to fault accommodation

Writing down mathematical models of agricultural greenhouses and regulating them via advanced controllers are challenging tasks since strong perturbations, like meteorological variations, have to be taken into account. This is why we are developing here a new model-free control approach and the corresponding intelligent controllers, where the need of a good model disappears. This setting, which has been introduced quite recently and is easy to implement, is already successful in many engineering domains. Tests on a concrete greenhouse and comparisons with Boolean controllers are reported. They not only demonstrate an excellent climate control, where the reference may be modified in a straightforward way, but also an efficient fault accommodation with respect to the actuators

Overview of rocket engine control

The issues of Chemical Rocket Engine Control are broadly covered. The basic feedback information and control variables used in expendable and reusable rocket engines, such as Space Shuttle Main Engine, are discussed. The deficiencies of current approaches are considered and a brief introduction to Intelligent Control Systems for rocket engines (and vehicles) is presented

A normative approach to multi-agent systems for intelligent buildings

Building Management Systems (BMS) are widely adopted in modern buildings around the world in order to provide high-quality building services, and reduce the running cost of the building. However, most BMS are functionality-oriented and do not consider user personalization. The aim of this research is to capture and represent building management rules using organizational semiotics methods. We implement Semantic Analysis, which determines semantic units in building management and their relationship patterns of behaviour, and Norm Analysis, which extracts and specifies the norms that establish how and when these management actions occur. Finally, we propose a multi-agent framework for norm based building management. This framework contributes to the design domain of intelligent building management system by defining a set of behaviour patterns, and the norms that govern the real-time behaviour in a building