EFFECTIVE DEVELOPMENT OF FUZZY-LOGIC RULES FOR REAL-TIME CONTROL OF AUTONOMOUS VEHICLES

Author(s):  
S.K. Tso ◽  
Y.H. Fung
2018 ◽  
Vol 15 (2) ◽  
pp. 192-204 ◽  
Author(s):  
Arpit Jain ◽  
Satya Sheel ◽  
Piyush Kuchhal

Purpose The purpose of this paper is to study the application of entropy based optimized fuzzy logic control for a real-time non-linear system. Optimization of the fuzzy membership function (MF) is one of the most explored areas for performance improvement of the fuzzy logic controllers (FLC). Conversely, majority of previous works are motivated on choosing an optimized shape for the MF, while on the other hand the support of fuzzy set is not accounted. Design/methodology/approach The proposed investigation provides the optimal support for predefined MFs by using genetic algorithms-based optimization of fuzzy entropy-based objective function. Findings The experimental results obtained indicate an improvement in the performance of the controller which includes improvement in error indices, transient and steady-state parameters. The applicability of proposed algorithm has been verified through real-time control of the twin rotor multiple-input, multiple-output system (TRMS). Research limitations/implications The proposed algorithm has been used for the optimization of triangular sets, and can also be used for the optimization of other fussy sets, such as Gaussian, s-function, etc. Practical implications The proposed optimization can be combined with other algorithms which optimize the mathematical function (shape), and a potent optimization tool for designing of the FLC can be formulated. Originality/value This paper presents the application of a new optimized FLC which is tested for control of pitch and yaw angles in a TRMS. The performance of the proposed optimized FLC shows significant improvement when compared with standard references.


1997 ◽  
Vol 30 (23) ◽  
pp. 9-14
Author(s):  
A. Fernández ◽  
M. Marcos ◽  
F. Artaza ◽  
N. Iriondo ◽  
D. Orive

2019 ◽  
Vol 22 (2) ◽  
pp. 281-295 ◽  
Author(s):  
S. R. Mounce ◽  
W. Shepherd ◽  
S. Ostojin ◽  
M. Abdel-Aal ◽  
A. N. A. Schellart ◽  
...  

Abstract Urban flooding damages properties, causes economic losses and can seriously threaten public health. An innovative, fuzzy logic (FL)-based, local autonomous real-time control (RTC) approach for mitigating this hazard utilising the existing spare capacity in urban drainage networks has been developed. The default parameters for the control algorithm, which uses water level-based data, were derived based on domain expert knowledge and optimised by linking the control algorithm programmatically to a hydrodynamic sewer network model. This paper describes a novel genetic algorithm (GA) optimisation of the FL membership functions (MFs) for the developed control algorithm. In order to provide the GA with strong training and test scenarios, the compiled rainfall time series based on recorded rainfall and incorporating multiple events were used in the optimisation. Both decimal and integer GA optimisations were carried out. The integer optimisation was shown to perform better on unseen events than the decimal version with considerably reduced computational run time. The optimised FL MFs result in an average 25% decrease in the flood volume compared to those selected by experts for unseen rainfall events. This distributed, autonomous control using GA optimisation offers significant benefits over traditional RTC approaches for flood risk management.


1997 ◽  
Vol 36 (8-9) ◽  
pp. 343-347 ◽  
Author(s):  
L. Fuchs ◽  
T. Beeneken ◽  
P. Spönemann ◽  
C. Scheffer

This paper describes the use of the sewer model HYSTEM-EXTRAN in combination with a rule based control device using fuzzy-logic to simulate the real-time control of a sewer system. The rules for the control of the system were set up with the help of optimization procedures. The advantage of the procedure is proved by comparing the uncontrolled versus the controlled state in a simulated mode for an existing sewer system. The final system was installed and tested within the sewer system.


Robotica ◽  
2003 ◽  
Vol 21 (3) ◽  
pp. 271-281 ◽  
Author(s):  
Urbano Nunes ◽  
José Alberto Fonseca ◽  
Luís Almeida ◽  
Rui Araújo ◽  
Rodrigo Maia

In this paper distributed architectures for autonomous vehicles are addressed, with a special emphasis on its real-time control requirements. The interconnection of the distributed intelligent subsystems is a key factor in the overall performance of the system. To better understand the interconnection requirements, the main techniques and modules of a global navigation system are described. A special focus on fieldbuses properties and major characteristics is made in order to point out some potentialities, which make them attractive in autonomous vehicles real-time applications, either in terms of reliability as in terms of real-time restrictions.


2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
R. Lasri ◽  
I. Rojas ◽  
H. Pomares ◽  
O. Valenzuela

The main objective of this paper is to prove the great advantage that brings our novel approach to the intelligent control area. A set of various types of intelligent controllers have been designed to control the temperature of a room in a real-time control process in order to compare the obtained results with each other. Through a training board that allows us to control the temperature, all the used algorithms should present their best performances in this control process; therefore, our self-organized and online adaptive fuzzy logic controller (FLC) will be required to present great improvements in the control task and a real high control performance. Simulation results can show clearly that the new approach presented and tested in this work is very efficient. Thus, our adaptive and self-organizing FLC presents the best accuracy compared with the remaining used controllers, and, besides that, it can guarantee an important reduction of the power consumption during the control process.


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