Investigation of Steering Wheel Control of an Electric Buggy Car for Designing Fuzzy Controller

Halin, Hafiz; Khairunizam, Wan; Ikram, K.; Haris, Hasri; Bakar, Shahriman Abu; Razlan, Z. M.; Zunaidi, I.; Hazry, D.

doi:10.1007/978-981-10-8788-2_41

Cited by 18 publications

(2 citation statements)

References 12 publications

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“…Savings are achieved through film thickness tolerance control; trigger accuracy will also be directly related to many other savings. In our previous research, we have design and develop an intelligent system related to autonomous robotic application such as the design and development of an intelligent prosthesis (Ibrahim et al, 2008), path planning based on geographical features information for an autonomous mobile robot (Zunaidi et al, 2006), complex background subtraction for biometric identification (Khalifa et al, 2007), fuzzy multi-layer SVM classification (Hariraj et al, 2018) and also fuzzy wheel controller design (Halin et al, 2018;Mustafa et al, 2018). In this research, we will evaluate and optimize the best parameter settings for ASPS and using the above research finding to develop an intelligent autonomous height control system for ASPS in the future.…”

Section: Literature Reviewmentioning

confidence: 99%

Parameter Settings for an Automated Gantry-Robot Painting System using a 3-Gun Atomization Spray Method for an Anti- Static Coating Process

Zunaidi¹,

Rahim²,

Ariffadillah³

et al. 2019

American Journal of Engineering and Applied Sciences

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Dry film thickness and appearance are the main quality improvements that can be achieved by an automated painting system in the manufacturing process. This study presents the spray coating process for aircraft parts using a gantry robot with an automated spray-painting gun to control the spray path, thus achieving the desired coating layer thickness. The experimental results show that the 3-gun atomization spray method, with high capacity airflow and outstanding atomization characteristics, poses the challenge of achieving an even thickness of the overlapping spray pattern from three separate guns, minimizing the paint material consumption and controlling the dry film thickness within the given specification and standard. The optimization was performed to control the spray path and material consumption with a 3-gun spray method to achieve the optimum setting for the spray nozzle to workpiece height to obtain the target thickness. The results show that replacing the manual process with the automated painting process can increase the speed by up to 30-40%, reduce the setup time and increase the capacity of the painting booth. The development of this system can achieve the desired thickness specification, increase productivity and provide safer, more effective and ergonomic working conditions.

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Section: Literature Reviewmentioning

confidence: 99%

Parameter Settings for an Automated Gantry-Robot Painting System using a 3-Gun Atomization Spray Method for an Anti- Static Coating Process

Zunaidi¹,

Rahim²,

Ariffadillah³

et al. 2019

American Journal of Engineering and Applied Sciences

Self Cite

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“…In this regard, Wu and Li [74] introduced a fuzzy-neural network-based variable steering control for self-driving vehicles to improve the control unit of the steer-by-wire AVs. Halin et al [75] have proposed GPS-fuzzy logic-based controller for navigation and path tracking in the unmanned ground vehicles. e proposed system defines the path through the GPS module and a fuzzy inference engine has been devised to control the lateral motion of the steering wheels.…”

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confidence: 99%

Are Self-Driving Vehicles Ready to Launch? An Insight into Steering Control in Autonomous Self-Driving Vehicles

Rasib

Butt

Khalid

et al. 2021

Mathematical Problems in Engineering

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In the last couple of years, academia-industry collaboration has demonstrated rapid advancements in the development of self-driving vehicles. Since it is evident that self-driving vehicles are going to reshape the traditional transportation systems in near future through enhancement in safe and smart mobility, motion control in self-driving vehicles while performing driving tasks in a dynamic road environment is still a challenging task. In this regard, we present a comprehensive study considering the evolution of steering control methods for self-driving vehicles. Initially, we discussed an insight into the traditional steering systems of the vehicles. To the best of our knowledge, currently, there is no taxonomy available, which elaborates steering control methods for self-driving vehicles. In this paper, we present a novel taxonomy including different steering control methods which are categorized into deterministic and heuristic steering control methods. Concurrently, the abovementioned techniques are critically reviewed elaborating their strengths and limitations. Based on the analysis, key challenges/research gaps in existing steering control methods along with the possible solutions have been briefly discussed to improve the effectiveness of the steering system of self-driving vehicles.

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Path Tracking Simulation of the Buggy Car by Using Fuzzy Information of the Steering Wheel

Halin

Khairunizam

Haris³

et al. 2019

Lecture Notes in Mechanical Engineering

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Investigation of Steering Wheel Control of an Electric Buggy Car for Designing Fuzzy Controller

Cited by 18 publications

References 12 publications

Parameter Settings for an Automated Gantry-Robot Painting System using a 3-Gun Atomization Spray Method for an Anti- Static Coating Process

Parameter Settings for an Automated Gantry-Robot Painting System using a 3-Gun Atomization Spray Method for an Anti- Static Coating Process

Are Self-Driving Vehicles Ready to Launch? An Insight into Steering Control in Autonomous Self-Driving Vehicles

Path Tracking Simulation of the Buggy Car by Using Fuzzy Information of the Steering Wheel

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