Interval Type-2 Fuzzy Control System Integrated with Neural Network-Predictive Control for Air Suspension System to Improve Both Ride and Braking Characteristics 2022-01-5053
In this paper, the performance of a controlled air suspension system is integrated with the controlled braking system. In order to improve both ride comfort and dynamic stability, the neural network (NN)-predictive control is designed as a system controller for the air suspension system to minimize vertical, pitch, and roll motions. The rate of controlled force generated by the air suspension system is changed according to external excitation transmitted from road roughness to the vehicle body. PID controller is designed for the antilock braking system (ABS) to improve braking performance. Interval type-2 fuzzy control system (IT-2FCS) is also designed as an integrated controller to generate desired paths for both the NN-predictive controller and PID controller. Desired paths are achieved based on tuned dynamic responses of the vehicle suspension system and the relative skid ratio. Pneumatic suspension system with tuned desired paths is compared with both pneumatic suspension system without tuned and passive suspension system. The influence of the desired path on the controlled air suspension system is described based on the main performance criteria analyzed under bump road in the time domain and random excitation in the frequency domain. The influence of the desired path on the controlled ABS is also described based on reduction of both stopping distance and stopping time with minimized fluctuation of wheel hop under different conditions. The effect of wheel hop on vehicle longitudinal stability is described based on integrated model including the suspension model, magic formula tire model, and ABS model. The simulation results reveal that tuned desired paths of the IT-2FCS for both controlled pneumatic suspension system and controlled braking system are capable of achieveing ride comfort and safety higher than other proposed systems. Also, tire-ground contact point and braking efficiency based on the dynamic tire load as an integrated performance are improved significantly.
Citation: Shehata Gad, A., "Interval Type-2 Fuzzy Control System Integrated with Neural Network-Predictive Control for Air Suspension System to Improve Both Ride and Braking Characteristics," SAE Technical Paper 2022-01-5053, 2022, https://doi.org/10.4271/2022-01-5053. Download Citation
Author(s):
Ahmed Shehata Gad
Affiliated:
Guidance, Navigation & Control, Sensible 4
Pages: 29
Event:
Automotive Technical Papers
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Anti-lock braking
Passive suspension systems
Suspension systems
Fuzzy logic
Control systems
Braking systems
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