Compact Fuzzy Systems Based on Boolean Relations

Helbert Espitia; José Soriano; Iván Machón; Hilario López

doi:10.3390/app11041793

Compact Fuzzy Systems Based on Boolean Relations

Applied Sciences ◽

10.3390/app11041793 ◽

2021 ◽

Vol 11 (4) ◽

pp. 1793

Author(s):

Helbert Espitia ◽

José Soriano ◽

Iván Machón ◽

Hilario López

Keyword(s):

Design Process ◽

Fuzzy System ◽

Fuzzy Systems ◽

Hydraulic System ◽

Design Methodology ◽

Satisfactory Performance ◽

And Control ◽

Equivalent Expressions ◽

Nonlinear Plant

This document presents some considerations and procedures to design a compact fuzzy system based on Boolean relations. In the design process, a Boolean codification of two elements is extended to a Kleene’s of three elements to perform simplifications for obtaining a compact fuzzy system. The design methodology employed a set of considerations producing equivalent expressions when using Boole and Kleene algebras establishing cases where simplification can be carried out, thus obtaining compact forms. In addition, the development of two compact fuzzy systems based on Boolean relations is shown, presenting its application for the identification of a nonlinear plant and the control of a hydraulic system where it can be seen that compact structures describes satisfactory performance for both identification and control when using algorithms for optimizing the parameters of the compact fuzzy systems. Finally, the applications where compact fuzzy systems are based on Boolean relationships are discussed allowing the observation of other scenarios where these structures can be used.

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Design and Optimization of a Neuro-Fuzzy System for the Control of an Electromechanical Plant

Applied Sciences ◽

10.3390/app12020541 ◽

2022 ◽

Vol 12 (2) ◽

pp. 541

Author(s):

Helbert Espitia ◽

Iván Machón ◽

Hilario López

Keyword(s):

Control System ◽

Design Process ◽

Fuzzy System ◽

Fuzzy Systems ◽

Fuzzy Controller ◽

Initial Configuration ◽

Control Action ◽

Linear Controller ◽

Neuro Fuzzy ◽

And Control

One characteristic of neuro-fuzzy systems is the possibility of incorporating preliminary information in their structure as well as being able to establish an initial configuration to carry out the training. In this regard, the strategy to establish the configuration of the fuzzy system is a relevant aspect. This document displays the design and implementation of a neuro-fuzzy controller based on Boolean relations to regulate the angular position in an electromechanical plant, composed by a motor coupled to inertia with friction (a widely studied plant that serves to show the control system design process). The structure of fuzzy systems based on Boolean relations considers the operation of sensors and actuators present in the control system. In this way, the initial configuration of fuzzy controller can be determined. In order to perform the optimization of the neuro-fuzzy controller, the continuous plant model is converted to discrete time to be included in the closed-loop controller training equations. For the design process, first the optimization of a Proportional Integral (PI) linear controller is carried out. Thus, linear controller parameters are employed to establish the structure and initial configuration of the neuro-fuzzy controller. The optimization process also includes weighting factors for error and control action in such a way that allows having different system responses. Considering the structure of the control system, the optimization algorithm (training algorithm) employed is dynamic back propagation. The results via simulations show that optimization is achieved in the linear and neuro-fuzzy controllers using different weighting values for the error signal and control action. It is also observed that the proposed control strategy allows disturbance rejection.

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Design of a Mobile Robot to Clean the External Walls of Oil Tanks

Mobile Ad Hoc Robots and Wireless Robotic Systems - Advances in Computational Intelligence and Robotics ◽

10.4018/978-1-4666-2658-4.ch012 ◽

2013 ◽

pp. 237-247

Author(s):

Hernán Gonzalez Acuña ◽

Alfonso René Quintero Lara ◽

Ricardo Ortiz Guerrero ◽

Jairo de Jesús Montes Alvarez ◽

Hernando González Acevedo ◽

...

Keyword(s):

Mobile Robot ◽

Design Process ◽

Design Methodology ◽

Mechanical Design ◽

Research Work ◽

Control Design ◽

Research Groups ◽

Successful Design ◽

Oil Tanks ◽

And Control

This chapter describes a Mechatronics Design methodology applied to the design of a mobile robot to climb vertical surfaces. The first part of this chapter reviews different ways to adhere to vertical surfaces and shows some examples developed by different research groups. The second part presents the stages of Mechatronics design methodology used in the design, including mechanical design, electronics design, and control design. These stages describe the most important topics for optimally successful design. The final part provides results that were obtained in the design process and construction of the robot. Finally, the conclusions of this research work are presented.

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Advanced Supervision Of Oil Wells Based On Soft Computing Techniques

Journal of Artificial Intelligence and Soft Computing Research ◽

10.1515/jaiscr-2015-0010 ◽

2014 ◽

Vol 4 (3) ◽

pp. 215-225 ◽

Cited By ~ 5

Author(s):

Edgar Camargo ◽

Jose Aguilar

Keyword(s):

Fuzzy System ◽

Fuzzy Systems ◽

Oil Well ◽

Soft Computing Techniques ◽

Operational Diagnosis ◽

Petroleum Wells ◽

Operational Failures ◽

And Control ◽

Intelligent Model ◽

Gas Lift

Abstract In this work is presented a hybrid intelligent model of supervision based on Evolutionary Computation and Fuzzy Systems to improve the performance of the Oil Industry, which is used for Operational Diagnosis in petroleum wells based on the gas lift (GL) method. The model is composed by two parts: a Multilayer Fuzzy System to identify the operational scenarios in an oil well and a genetic algorithm to maximize the production of oil and minimize the flow of gas injection, based on the restrictions of the process and the operational cost of production. Additionally, the first layers of the Multilayer Fuzzy System have specific tasks: the detection of operational failures, and the identification of the rate of gas that the well requires for production. In this way, our hybrid intelligent model implements supervision and control tasks.

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Modeling and Control of Complex Nonlinear Systems Based on TS Model

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.380-384.417 ◽

2013 ◽

Vol 380-384 ◽

pp. 417-420

Author(s):

Yu Chi Zhao ◽

Jing Liu

Keyword(s):

System Theory ◽

Nonlinear System ◽

Nonlinear Systems ◽

Fuzzy System ◽

Fuzzy Systems ◽

Fuzzy Model ◽

Modeling And Control ◽

Linear Control Theory ◽

Complex Nonlinear Systems ◽

And Control

The current theory of nonlinear systems is still not perfect. The modeling and control of nonlinear system problem has always been the difficulty. In a variety of methods of its study, fuzzy system theory because of having the language descriptive way similar to the human mind, can obtain and deal with the qualitative information intelligently. The theory itself also has non-linear characteristics. Therefore the use of fuzzy systems theory to establish the fuzzy model of nonlinear system can well describe the nonlinear characteristics. T-S fuzzy systems, due to the combination of the good performance of the fuzzy system to deal with nonlinear problems with the simple linear expressions, are not only suitable for modeling the nonlinear system, but also use T-S fuzzy model and the linear control theory method to design the controller. So it has been widely used in nonlinear system control problems, and has also greatly developed the T-S fuzzy system theory, appearing a lot of methods of structural and parameter identification. However, this study of T-S fuzzy rules makes us have to face the difference of different ways to select the number of rules as well as online self-adaptability of the number of rules which off-line method lacks when using T-S fuzzy model to deal with nonlinear system modeling and control problem. In view of this, this paper researches on modeling and controlling of complex nonlinear systems based on TS model from different perspectives.

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Indirect adaptive controller based on a self-structuring fuzzy system for nonlinear modeling and control

International Journal of Applied Mathematics and Computer Science ◽

10.2478/v10006-009-0049-8 ◽

2009 ◽

Vol 19 (4) ◽

pp. 619-630 ◽

Cited By ~ 11

Author(s):

Ruiyun Qi ◽

Mietek Brdys

Keyword(s):

Fuzzy System ◽

Closed Loop ◽

Nonlinear Modeling ◽

Fuzzy Model ◽

Adaptive Controller ◽

Modeling And Control ◽

Control Scheme ◽

On Line ◽

And Control ◽

Nonlinear Plant

Indirect adaptive controller based on a self-structuring fuzzy system for nonlinear modeling and controlIn this paper, a unified nonlinear modeling and control scheme is presented. A self-structuring Takagi-Sugeno (T-S) fuzzy model is used to approximate the unknown nonlinear plant based on I/O data collected on-line. Both the structure and the parameters of the T-S fuzzy model are updated by an on-line clustering method and a recursive least squares estimation (RLSE) algorithm. The rules of the fuzzy model can be added, replaced or deleted on-line to allow a more flexible and compact model structure. The overall controller consists of an indirect adaptive controller and a supervisory controller. The former is the dominant controller, which maintains the closed-loop stability when the fuzzy system is a good approximation of the nonlinear plant. The latter is an auxiliary controller, which is activated when the tracking error reaches the boundary of a predefined constraint set. It is proven that global stability of the closed-loop system is guaranteed in the sense that all the closed-loop signals are bounded and simulation examples demonstrate the effectiveness of the proposed control scheme.

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Design of a Mobile Robot to Clean the External Walls of Oil Tanks

Robotics ◽

10.4018/978-1-4666-4607-0.ch036 ◽

2013 ◽

pp. 743-753

Author(s):

Hernán González Acuña ◽

Alfonso René Quintero Lara ◽

Ricardo Ortiz Guerrero ◽

Jairo de Jesús Montes Alvarez ◽

Hernando González Acevedo ◽

...

Keyword(s):

Mobile Robot ◽

Design Process ◽

Design Methodology ◽

Mechanical Design ◽

Research Work ◽

Control Design ◽

Research Groups ◽

Successful Design ◽

Oil Tanks ◽

And Control

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A Mathematical Model Including Mechanical Structure, Hydraulic and Control of LHDS

Robotica ◽

10.1017/s0263574720001204 ◽

2021 ◽

pp. 1-16

Author(s):

Guoliang Ma ◽

Kaixian Ba ◽

Zhiwu Han ◽

Zhengguo Jin ◽

Bin Yu ◽

...

Keyword(s):

Simulation Model ◽

Hydraulic System ◽

Inverse Dynamics ◽

Hydraulic Drive ◽

Operation Time ◽

Variable Load ◽

Mechanical Structure ◽

Load Characteristics ◽

Common Problems ◽

And Control

SUMMARY In this paper, mathematical models of kinematics, statics and inverse dynamics are derived firstly according to the mechanical structure of leg hydraulic drive system (LHDS). Then, all the above models are integrated with MATLAB/Simulink to build the LHDS simulation model, the model not only considers influence of leg dynamic characteristics on hydraulic system but also takes into account nonlinearity, variable load characteristics and other common problems brought by hydraulic system, and solves compatibility and operation time which brought by using multiple software simultaneously. The experimental results show the simulation model built in this paper can accurately express characteristics of the system.

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Momentum exchange impact damper design methodology for object-wall-collision problems

Journal of Vibration and Control ◽

10.1177/1077546317703202 ◽

2017 ◽

Vol 24 (14) ◽

pp. 3206-3218

Author(s):

Yohei Kushida ◽

Hiroaki Umehara ◽

Susumu Hara ◽

Keisuke Yamada

Keyword(s):

Optimal Design ◽

Design Methodology ◽

Design Parameters ◽

Momentum Exchange ◽

Impact Damper ◽

One Dimensional ◽

Practical Design ◽

Wall Collision ◽

Damper Design ◽

And Control

Momentum exchange impact dampers (MEIDs) were proposed to control the shock responses of mechanical structures. They were applied to reduce floor shock vibrations and control lunar/planetary exploration spacecraft landings. MEIDs are required to control an object’s velocity and displacement, especially for applications involving spacecraft landing. Previous studies verified numerous MEID performances through various types of simulations and experiments. However, previous studies discussing the optimal design methodology for MEIDs are limited. This study explicitly derived the optimal design parameters of MEIDs, which control the controlled object’s displacement and velocity to zero in one-dimensional motion. In addition, the study derived sub-optimal design parameters to control the controlled object’s velocity within a reasonable approximation to derive a practical design methodology for MEIDs. The derived sub-optimal design methodology could also be applied to MEIDs in two-dimensional motion. Furthermore, simulations conducted in the study verified the performances of MEIDs with optimal/sub-optimal design parameters.

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