Combined ANFIS method with FA, PSO, and ICA as Steering Control Optimization on Electric Car

Ali, Machrus and Muhlasin, - and Nurohmah, Hidayatul and Raikhani, Agus and Kadaryono, - and Sutantra, Nyoman (2018) Combined ANFIS method with FA, PSO, and ICA as Steering Control Optimization on Electric Car. 2018 Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS) IEEE. ISSN -

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Abstract

An Adaptive Neuro-Fuzzy Inference System (ANFIS)
is a kind of Artificial Neural Network that is based on Takagi–Sugeno
Fuzzy Inference System. Since it integrates both neural networks and
fuzzy logic principles, it has potential to capture the benefits of both
in a single framework. ANFIS can be used to control and optimize
the system automatically. Optimization of steer movement is
necessary for steer movement with the vehicle. Faulty movement
leads the car will generate errors position of the car on the vehicle
line. Several studies have been developed in fully automated steer by
cabling systems, including those devoted to input paths, using GPS
technology and trajectories. In this study steering system using PID
controller Use of Artificial Intelligence (AI) is very helpful in
accelerating and optimizing the process of controlling PID and
ANFIS. In this research, we will develop Fully Automatic Steer By
Wire System model using 10 Degree Of Freedom (DOF) which
consists of 7-DOF Vehicle Ride Model and 3-DOF Vehicle Handling
Model. The method already used is the PID that is tuned using AI.
This research combines ANFIS method with Firefly Algorithm (FA),
Particle Swarm Optimization (PSO) and Imperialist Competitive
Algorithm (ICA). Then compare the result with the FA-PID, PSOPID, ICA-PID, FA-ANFIS, PSO-ANFIS, and ICA-ANFIS.
Furthermore, this method is used to design a real electric car. At a
standard speed of 13.8 km/h, the ICA-ANFIS method has the smallest
error of 0.005070 m. If the speed of the vehicle is changed change is
able to maintain stay on track only up to speed 62.1 km/h. But the
ICA-PID method can keep it on track to speeds of 69.0 km/h. The
result of this simulation is the ideal condition of the vehicle. Further
research may be followed by a real vehicle conditions.
Keywords— ANFIS, Artificial Intelligence, PID, steering
control, vehicle

Item Type: Article
Subjects: University Structure > YEAR > 2018
University Structure > YEAR > 2018
T Technology > TJ Mechanical engineering and machinery
University Structure > Fakultas Teknik > Teknik Elektro
University Structure > Fakultas Teknik > Teknik Elektro
Divisions: Fakultas Teknik > Teknik Elektro
Depositing User: undar undar undar
Date Deposited: 05 Jul 2020 06:04
Last Modified: 05 Jul 2020 06:05
URI: http://repository.undar.ac.id/id/eprint/22

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