Optimal fuzzy adaptive robust PID control for an active suspension system

Mahmoodabadi, Mohammad Javad; Nejadkourki, N.

doi:10.1080/14484846.2020.1734154

Cited by 41 publications

(19 citation statements)

References 44 publications

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“…used a fuzzy controller to control the seven-degree-of-freedom suspension system, which reduced the body displacement and acceleration magnitude, eliminated the body-induced resonance peaks, and ensured the smoothness of the body. To make the vehicle achieve more stringent comfort, Mahmoodabadi et al [207,208] proposed an optimal adaptive fuzzy controller based on a gravity search algorithm. The gravitational search algorithm optimizes the control parameters to reduce the acceleration of the body, the relative displacement between the tires and the sprung mass.…”

Section: Fuzzy Controlmentioning

confidence: 99%

A Review of Electromagnetic Energy Regenerative Suspension System & Key Technologies

Fu¹,

Lu²,

Ge³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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The active suspension has undoubtedly improved the performance of the vehicle, however, the trend of "lowcarbonization, intelligence, and informationization" in the automotive industry has put forward higher and more urgent requirements for the suspension system. The automotive industry and researchers favor active energy regeneration suspension technology with safety, comfort, and high energy regenerative efficiency. In this paper, we review the research progress of the structure form, optimization method, and control strategy of electromagnetic energy regenerative suspension. Specifically, comparing the pros and cons of the existing technology in solving the contradiction between dynamic performance and energy regeneration. In addition, the development trend of electromagnetic energy regenerative suspension in the field of structure form, optimization method, and control technology prospects.

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Section: Fuzzy Controlmentioning

confidence: 99%

A Review of Electromagnetic Energy Regenerative Suspension System & Key Technologies

Fu¹,

Lu²,

Ge³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

View full text Add to dashboard Cite

show abstract

“…Xubin Dong et al 29 proposed a fractional air disaster eradication method based on the adaptive clonal algorithm for active suspension, which reduces the requirement of model accuracy. The optimum mode and self-adaptive PID control for active suspension are presented by Nonlinear Dyn et al The optimum mode and self-adaptive PID control for active suspension are presented by M. J. Mahmoodabadi et al 30 Based on the design of self-adaptive rules, the parameters of the system are adjusted by means of the mode and system, so that the system has a small overshoot and greatly reduces the vibration.…”

Section: Current Status Of Air Suspension Researchmentioning

confidence: 99%

Research on nonlinear model and fuzzy fractional order PI^λD^μ control of air suspension system

Wang

et al. 2021

Journal of Low Frequency Noise, Vibration and Active Control

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To improve the ride comfort of wheeled armored vehicles, air springs are used. To describe the vehicle motion more accurately, a nine-degree-of-freedom air suspension system for the whole vehicle was established, and its equations of motion were derived. Through theoretical analysis of the stiffness characteristics and forces on the air springs, the nonlinear restoring force was obtained as a cubic polynomial of the air spring displacement. The simulation results obtained by fitting the polynomial and radial basis function curves with MATLAB/Simulink software are consistent with the actual test results, thus verifying the correctness of the nonlinear air spring polynomial model. Finally, a fuzzy fractional order PIλDμ controller is designed and simulated for the vehicle-seat-body model in terms of wheel dynamic load, suspension dynamic deflection, body acceleration, and other indicators. The simulation results show that the fuzzy fractional order PIλDμ Proportion Integral Differential (PID) control strategy has better overall performance than the PID control strategy, fuzzy control strategy, and fuzzy PID control strategy.

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“…[19][20][21] Besides, many other intelligent algorithms have been used to search for the controller's parameters optimally. [22][23][24] The PID controller can only be applied to systems that have an object. If the system has many objects to be controlled, using multiple PID controllers is a suitable alternative.…”

Section: Introductionmentioning

confidence: 99%

Design a new control algorithm AFSP (Adaptive Fuzzy – Sliding Mode – Proportional – Integral) for automotive suspension system

Nguyen

2023

Advances in Mechanical Engineering

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When a vehicle is driving, the most significant source of oscillations is the irregularities in the surface of the road. An active suspension is utilized to enhance the vehicle’s stability and ride comfort. In this work, the dynamic model with multi variables is considered to simulate vehicle oscillations based on four excitation cases from the road surface. In addition, this research also established the AFSP complex control solution for an active suspension system. This is a completely novel algorithm with many outstanding advantages. The final control signal of the system is synthesized from the signals of the linear controller PI (Proportional – Integral) and the nonlinear controller SMC (Sliding Mode Control). The controller’s parameters will change continuously depending on the established fuzzy rule. According to simulation outcomes, the vehicle body displacement and acceleration dramatically declined when the AFSP algorithm directed an active suspension. The values of acceleration and displacement do not exceed 80% and 20%, compared to the scenario in which the vehicle just utilized the typical passive suspension system. Besides, a phenomenon of “chattering” also does not appear when combining the controllers. Overall, the efficiency of this algorithm is high. This algorithm can be applied to more complex models.

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Optimal fuzzy adaptive robust PID control for an active suspension system

Cited by 41 publications

References 44 publications

A Review of Electromagnetic Energy Regenerative Suspension System & Key Technologies

A Review of Electromagnetic Energy Regenerative Suspension System & Key Technologies

Research on nonlinear model and fuzzy fractional order PI^λD^μ control of air suspension system

Design a new control algorithm AFSP (Adaptive Fuzzy – Sliding Mode – Proportional – Integral) for automotive suspension system

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Optimal fuzzy adaptive robust PID control for an active suspension system

Cited by 41 publications

References 44 publications

A Review of Electromagnetic Energy Regenerative Suspension System & Key Technologies

A Review of Electromagnetic Energy Regenerative Suspension System & Key Technologies

Research on nonlinear model and fuzzy fractional order PIλDμ control of air suspension system

Design a new control algorithm AFSP (Adaptive Fuzzy – Sliding Mode – Proportional – Integral) for automotive suspension system

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Product

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Research on nonlinear model and fuzzy fractional order PI^λD^μ control of air suspension system