Design of and Research into a Multiple-Fuzzy PID Suspension Control System Based on Road Recognition

Ding, Xinkai; Li, Ruichuan; Cheng, Yi; Liu, Qi; Liu, Jilu

doi:10.3390/pr9122190

Cited by 21 publications

(15 citation statements)

References 23 publications

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“…where k p is the proportional constant, k i is the integrating constant, k d is the differentiating constant, λ is the fractional order of the integrating action, and µ is the fractional order of the differentiating action. By comparison with the conventional PID controller [45], fractional-order controllers have in addition two other parameters noted λ and µ, which present the order of integration and derivation, respectively. Depending on the variation of these two parameters, we can distinguish different possibilities of fractional order controller [44].…”

Section: Fractional Order Pid Controllermentioning

confidence: 99%

Fractional Order PID Design for a Proton Exchange Membrane Fuel Cell System Using an Extended Grey Wolf Optimizer

et al. 2022

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This paper presents a comparison of optimizers for tuning a fractional-order proportional-integral-derivative (FOPID) and proportional-integral-derivative (PID) controllers, which were applied to a DC/DC boost converter. Grey wolf optimizer (GWO) and extended grey wolf optimizer (EGWO) have been chosen to achieve suitable parameters. This strategy aims to improve and optimize a proton exchange membrane fuel cell (PEMFC) output power quality through its link with the boost converter. The model and controllers have been implemented in a MATLAB/SIMULINK environment. This study has been conducted to compare the effectiveness of the proposed controllers in the transient, accuracy in tracking the reference current, steady-state, dynamic responses, overshoots, and response time. Results showed that the combination EGWO-FOPID had significant advantages over the rest of the optimized controllers.

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Section: Fractional Order Pid Controllermentioning

confidence: 99%

Fractional Order PID Design for a Proton Exchange Membrane Fuel Cell System Using an Extended Grey Wolf Optimizer

et al. 2022

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“…The values of these parameters can also be changed continuously thanks to the use of a Fuzzy-PID hybrid controller. If the fuzzy rule is properly constructed, this change is very positive 16 – 18 . If the system has many objects to be considered, that is, a MIMO system, the LQR control algorithm is the suitable alternative 19 .…”

Section: Introductionmentioning

confidence: 99%

Evaluate the stability of the vehicle when using the active suspension system with a hydraulic actuator controlled by the OSMC algorithm

Nguyen

2022

Sci Rep

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The ride comfort is controlled by the suspension system. In this article, an active suspension system is used to control vehicle vibration. Vehicle oscillations are simulated by a quarter-dynamic model with five state variables. This model includes the influence of the hydraulic actuator in the form of linear differential equations. This is a completely novel model. Besides, the OSMC algorithm is proposed to control the operation of the active suspension system. The controller parameters are optimized by the in-loop algorithm. According to the results of the study, under normal oscillation situations, the maximum and average values of the sprung mass were significantly reduced when the OSMC algorithm was applied. In dangerous situations, the wheel is completely separated from the road surface if the vehicle uses only the passive suspension system or active suspension system with a conventional linear control algorithm. In contrast, the interaction between the wheel and the road surface is always guaranteed when the OSMC algorithm is used to control the operation of the active suspension system. The efficiency that this algorithm brings is very high.

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“…Among them, the PID method is simple in design, stable in performance, and the most widely used. However, due to its Processes 2022, 10, 562 2 of 20 slow dynamic response speed and low steady-state accuracy, it is difficult to adapt to the situation where the target volume becomes smaller, and the maneuverability becomes stronger in the current environment [9].…”

Section: Introductionmentioning

confidence: 99%

Dynamic High-Type Interval Type-2 Fuzzy Logic Control for Photoelectric Tracking System

Qin

Zhang²,

Zhao³

et al. 2022

Processes

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This paper proposes a dynamic high-type control (DHTC) method based on an interval type-2 fuzzy logic controller (IT2FLC), which is used in the photoelectric tracking system to improve the steady-state accuracy and response speed. Adding integrators to the traditional multi-loop feedback control loop can increase the system type, thereby speeding up the response speed and improving the steady-state accuracy, but there is a risk of integral saturation. Switching the type dynamically according to the system state can avoid integral saturation while retaining the advantages of the high-type. Fuzzy logic control (FLC) can dynamically change the output value according to the input change and has the advantages of fast response speed and strong ability to handle uncertainties. Therefore, in this paper, the FLC is introduced into the high-type control system, and the output of the FLC is used as the gain of the integrator to control the on-off to achieve the goal of dynamic switching type, which is successfully verified in the experiment. IT2FLC introduces a three-dimensional membership function, which further improves the FLC’s ability to handle uncertainties. From the experimental results, compared with T1FLC, IT2FLC’s ability to handle uncertainties is significantly improved. In addition, in order to speed up the calculation speed of IT2FLC, this paper proposes an improved type-reduction algorithm, which is called weighted-trapezoidal Nie-Tan (WTNT). Compared with the traditional type-reduction algorithm, WTNT has faster calculation speed and better steady-state accuracy, and has been successfully applied to real-time control systems, which has good engineering application value. Finally, in order to reduce the interference of human factors and improve the automation level of the system, a multi-population genetic algorithm (MPGA) is used to iteratively optimize the parameters of the FLC, which improves the output accuracy. On the experimental platform of the flexible fast steering mirror (FFSM), the control effects of the traditional controller, T1FLC and IT2FLC are compared, which proves that the IT2FLC-DHTC system has a faster response performance, higher steady-state accuracy, and stronger ability to handle uncertainties.

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Design of and Research into a Multiple-Fuzzy PID Suspension Control System Based on Road Recognition

Cited by 21 publications

References 23 publications

Fractional Order PID Design for a Proton Exchange Membrane Fuel Cell System Using an Extended Grey Wolf Optimizer

Fractional Order PID Design for a Proton Exchange Membrane Fuel Cell System Using an Extended Grey Wolf Optimizer

Evaluate the stability of the vehicle when using the active suspension system with a hydraulic actuator controlled by the OSMC algorithm

Dynamic High-Type Interval Type-2 Fuzzy Logic Control for Photoelectric Tracking System

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