2018
DOI: 10.14419/ijet.v7i4.16700
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Design fuzzy neural petri net controller for trajectory tracking control of mobile robot

Abstract: In this paper, a Fuzzy Neural Petri Net (FNPN) controller has been designed established on Particle Swarm Optimization (PSO) for controlling the path tracking of Wheeled Mobile Robot (WMR). The path planning controller problem has been solved using two FNPN controllers to get the desired velocity and azimuth. The PSO method has used to detection the optimal values parameters of FNPN controllers. The overall models of wheeled mobile robot for path tracking control created on PSO algorithm are implemented in Sim… Show more

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Cited by 6 publications
(7 citation statements)
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“…The popular performance standards based on the error condition are integrated absolute error (IAE), integrated of time weight square error (ITSE), and integrated of square error (ISE) that can be estimated theoretically in the frequency domain [31,32,36]. In this chapter, multiobjective functions are utilized based on the integral of the squared error (ISE) criterion and overshoot (M p Þ criterion as follow [37,38]: ei ðÞ¼Di ðÞÀyi ðÞ (12) where y(i) is the system output and D(i) is the desired output, while n is the actual speed and n ref is the desired speed.…”
Section: Particle Swarm Optimization Algorithmmentioning
confidence: 99%
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“…The popular performance standards based on the error condition are integrated absolute error (IAE), integrated of time weight square error (ITSE), and integrated of square error (ISE) that can be estimated theoretically in the frequency domain [31,32,36]. In this chapter, multiobjective functions are utilized based on the integral of the squared error (ISE) criterion and overshoot (M p Þ criterion as follow [37,38]: ei ðÞ¼Di ðÞÀyi ðÞ (12) where y(i) is the system output and D(i) is the desired output, while n is the actual speed and n ref is the desired speed.…”
Section: Particle Swarm Optimization Algorithmmentioning
confidence: 99%
“…The WNN-PID controller based on PSO is proposed in this section, which combines the ability of the artificial neural networks for learning with the ability of wavelet for identification, control of dynamic system, and also having the capability of self-learning and adapting [10,11,19,37]. Two types of wavelet network are modified in this section, feedforward WNN and proposed recurrent WNN with online tuning optimization using PSO algorithm [22][23][24].…”
Section: Speed Control Of Bldc Motor Based On Wavelet Neural Networkmentioning
confidence: 99%
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“…More specifically, following product manufacture, chemical firms commonly utilize liquid filling machines to package their goods in drums. The liquid filling machine to automate in various size packaging industries has been the subject of multiple studies (Abubakar et al, 2022;Solanki et al, 2015;Baoyun & Daniel, 2016;Saleh et al, 2017). In industrial automation, programmable logic controllers, or PLCs, are widely utilized.…”
Section: Introductionmentioning
confidence: 99%
“…In industrial automation, programmable logic controllers, or PLCs, are widely utilized. Researchers studied the design and implementation of a PLC-controlled water filling machine system for varying bottle sizes, as well as an automatic liquid filling unit (Suramwar et al, 2022;Saleh et al, 2017). The other study describes how PLC-Supervisory control and data acquisition (SCADA) systems were used in the design and implementation of an intelligent automated bottle-filling enterprise.…”
Section: Introductionmentioning
confidence: 99%