Robust Adaptive Sliding Mode PI Control for Active Vehicle Seat Suspension Systems

Li, Weihua; Du, Haiping; Ning, Donghong

doi:10.1109/ccdc.2019.8832368

Cited by 8 publications

(7 citation statements)

References 24 publications

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“…Even the active suspension system controlled by the Robust controller has been used on many current electric vehicle models [40]. In the studies [41,42], the theories of H2 and Hꝏ optimization were also clearly analysed. In contrast, the Adaptive control method can generate control signals suitable to the vehicle's moving conditions [43].…”

Section: Literature Reviewmentioning

confidence: 99%

LQR Control with the New Triple In-Loops Algorithm for Optimization of the Tuning Parameters

Nguyen¹,

Nguyen²,

Dang³

et al. 2022

MMEP

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The suspension system plays a role in ensuring the stability of the vehicle when traveling on the road. On many modern vehicles, the active suspension system has been proposed to replace the conventional passive suspension system. The performance of the controller for the active suspension system depends on its control method. In this paper, a half dynamics model of the vehicle is established. Besides, the LQR control method is also used. The parameters of the control matrix are calculated through the triple in-loop optimization algorithm, which has been shown in the research. This is a completely novel algorithm. This algorithm helps to choose the most optimal parameters. Thus, it ensures the efficiency and stability of the controller. The calculation and comparison process are done automatically. When the loop ends, the optimal parameters are explicitly indicated. The simulation process is done in the MATLAB-Simulink environment. The results of the research showed that when the LQR controller, which was optimized through the triple in-loop algorithm used, the vehicle's oscillation was significantly reduced. In the three survey situations, the values of the roll angle and the angular acceleration of the sprung mass are guaranteed to be stable. Besides, when using this controller, the phenomenon of “chattering” after the excitation ends does not appear. This topic can be further developed in the future.

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Section: Literature Reviewmentioning

confidence: 99%

LQR Control with the New Triple In-Loops Algorithm for Optimization of the Tuning Parameters

Nguyen¹,

Nguyen²,

Dang³

et al. 2022

MMEP

View full text Add to dashboard Cite

show abstract

“…Table 3 presents a comparative analysis with respect to settling time (s), peak overshoot (m), peak undershoot (m), noise (%), and steady state error e ss . The effect of road impact in the oscillation of the suspension system applying different control approaches such as PID, fuzzy, NF, LQR, H∞ and SM is also presented in Table 3 based on the references [6,11,17,18,20,23] respectively. Similar working conditions are followed with the same level of actuator and sensor noise in all control techniques application for comparison.…”

Section: Comparative Studymentioning

confidence: 99%

“…However, the optimal gain parameter setting, a lesser range of robust control and need of change of gain setting with varying conditions are the major limitations to limit the real time application of these controllers. Among other projected robust control algorithms applied for limiting the oscillation and velocity of the VS system are fuzzy-logic control [8][9][10][11][12][13], fuzzy-PID control [14], genetic algorithm [15], neural network [16], neuro-fuzzy (NF) control [17], linear quadratic regulator (LQR) [18], H-infinity (H∞) control [19,20], and sliding mode (SM) control [21][22][23]. However, even if these control techniques are implemented effectively by absorbing the shocks due to the rough and bumpy road in case of VS system with enhanced accuracy and damping of oscillation, still fail to handle various constraints and random change found in a suspension environment.…”

Section: Introductionmentioning

confidence: 99%

Backstepping LQG controller design for stabilizing and trajectory tracking of vehicle suspension system

Patra

2020

SN Appl. Sci.

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The aim of this paper is to design a backstepping linear quadratic Gaussian controller (BLQGC) for a vehicle suspension (VS) system to improve the ride comfort by absorbing the shocks due to a rough and uneven road. For designing of the BLQGC, a forth order linearized model of the VS system is considered. In this control strategy, the conventional linear quadratic regulator is re-formulated with a state estimator based on the backstepping control approach to improve the control performance. The validation of improved control performance of BLQGC is established by comparative result investigation with other published control algorithms. The comparative results clearly reveal the better performance of the proposed approach to control the oscillation of the VS system within a stable range in terms of accuracy, robustness and handling uncertainties.

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“…According to [49], Lin et al have also come up with their integrated controller for the active suspension system. Various ideas for the integrated controller have also been worked out [50][51][52][53]. Based on the stated ideas, this paper focuses on the introduction, design, and evaluation of the double-integrated controller for the active suspension system.…”

Section: Introductionmentioning

confidence: 99%

Improving the Comfort of the Vehicle Based on Using the Active Suspension System Controlled by the Double-Integrated Controller

Nguyen

2021

Shock and Vibration

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When the vehicle moves on the road, many external factors affect the vehicle. These effects can cause oscillation and instability for the vehicle. The oscillation of the vehicle directly affects the safety and comfort of passengers. The suspension system is used to control and extinguish these oscillations. However, the conventional passive suspension system is unable to fully meet the vehicle’s requirements for stability and comfort. To improve these problems, these are much modern suspension system models that have been used in the vehicle to replace the passive suspension system. The modern suspension systems are used as the air suspension system, semiactive suspension system, and active suspension system. These systems which are controlled automatically by the controller were established based on the control methods. There are a lot of control methods which are used to control the operation of the active suspension system. These methods have their advantages and disadvantages. Almost, conventional control methods such as PID, LQR, or SMC are commonly used. However, they do not provide optimal efficiency in improving a vehicle’s oscillation. Therefore, it is necessary to establish a novel solution for the active suspension system control to improve the vehicle’s oscillation. In this paper, the method of using the double-integrated controller is proposed to solve the above problem. The double-integrated controller consists of two hydraulic actuators which are controlled completely separately. This is a completely novel and original method that can provide positive effects. This research focuses on establishing, simulating, and evaluating the novel control method (the double-integrated control) for the active suspension system. The results of the research have shown that when the vehicle is equipped with the active suspension system which is controlled by the double-integrated controller, the maximum values of displacement and acceleration of the sprung mass are significantly reduced. They reach only 6.25% and 9.10% (case 1) and 6.00% and 6.12% (case 2) compared to the conventional passive suspension system. Besides, its average values which are calculated by RMS are only about 3.91% and 4.67% (case 1) and 4.48% and 4.77% (case 2) compared to the above case. Therefore, the comfort and stability of the vehicle have been improved. This paper provides new concepts and knowledge about the double-integrated control method which will become the trend to be used in the next time for the systems of the vehicle. In the future, experimental procedures also need to be conducted to be able to more accurately evaluate the results of this research.

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Robust Adaptive Sliding Mode PI Control for Active Vehicle Seat Suspension Systems

Cited by 8 publications

References 24 publications

LQR Control with the New Triple In-Loops Algorithm for Optimization of the Tuning Parameters

LQR Control with the New Triple In-Loops Algorithm for Optimization of the Tuning Parameters

Backstepping LQG controller design for stabilizing and trajectory tracking of vehicle suspension system

Improving the Comfort of the Vehicle Based on Using the Active Suspension System Controlled by the Double-Integrated Controller

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