Adaptive neural network control for active suspension system with actuator saturation

Zhao, Feng; Ge, Shuzhi Sam; Tu, Fangwen; Qin, Yechen; Dong, Ming

doi:10.1049/iet-cta.2015.1317

Cited by 122 publications

(74 citation statements)

References 55 publications

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“…Generally speaking, active seat suspensions have the best performance among the three types of seat suspensions, because an additional control force device (actuator) can make suspension systems always stay in optimum vibration reduction state [11]. There have been many control methods used to improve driving comfort for active seat suspension systems, such as robust control [12], fuzzy control [13], sliding mode control [14], adaptive control [15,16], neural network control [17], etc. Since 1950s, adaptive control was invented to deal with uncertain or unknown parameters problems in some control systems [18], which can modify its own characteristics to adapt the dynamics of the plant and disturbance's variability.…”

Section: Semi-active Seat Suspensions Have Simple Structures Lowmentioning

confidence: 99%

“…Block diagram of the ARSMPIC schemeSubstituting the RASMPIC(17) and the projecting adaptive algorithm(14) into(16), we have ̇2 = − 2 − | | + ≤ − 2 ≤ 0 (18) The inequality(18) is similar with the inequality (9), so converges to zero when → ∞ . Therefore, the active vehicle seat suspension system with the RASMPIC(17)is stable and the convergence rate depends on the value of .…”

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confidence: 99%

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

Ning

2019

2019 Chinese Control and Decision Conference (CCDC)

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In this paper, a robust adaptive sliding mode proportional integral control (RASMPIC) method is proposed for an active vehicle seat suspension system, where the driver's mass is supposed as an unknown parameter with boundaries. A dynamic active seat suspension system is established at first. Then a sliding mode controller (SMC) is designed to achieve the required ride comfort performance based on the driver's mass estimated by utilizing an adaptive law where a projecting adaptive algorithm is used to prevent the estimated parameters from surpassing their boundaries to enhance the robustness of the seat suspension system. Also, a proportional and integral (PI) control for driver's acceleration is added into the controller as RASMPIC for the stabilization of the proposed suspension system. In simulations, sinusoidal vibrations are used to test the controllers and the results show the RASMPIC has a better control performance to reduce driver's acceleration and improve the driving comfort than SMC and RASMC.Abstract: In this paper, a robust adaptive sliding mode proportional integral control (RASMPIC) method is proposed for an active vehicle seat suspension system, where the driver's mass is supposed as an unknown parameter with boundaries. A dynamic active seat suspension system is established at first. Then a sliding mode controller (SMC) is designed to achieve the required ride comfort performance based on the driver's mass estimated by utilizing an adaptive law where a projecting adaptive algorithm is used to prevent the estimated parameters from surpassing their boundaries to enhance the robustness of the seat suspension system. Also, a proportional and integral (PI) control for driver's acceleration is added into the controller as RASMPIC for the stabilization of the proposed suspension system. In simulations, sinusoidal vibrations are used to test the controllers and the results show the RASMPIC has a better control performance to reduce driver's acceleration and improve the driving comfort than SMC and RASMC.

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Section: Semi-active Seat Suspensions Have Simple Structures Lowmentioning

confidence: 99%

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confidence: 99%

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

Ning

2019

2019 Chinese Control and Decision Conference (CCDC)

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“…In the recent studies, various approaches were proposed to improve the ride comfort and avert the fatigue risks associated to the human body. Some researchers have improved the vehicle suspension system to reduce the input vibration into the human body [10][11][12], while others focus on enhancing the vehicle seat suspension design [13]. Similarly, few studies integrated both the vehicle suspension system and seat suspension system to isolate vibration transmitted to human body [14,15].…”

Section: Introductionmentioning

confidence: 99%

A Systematic Literature Review of Various Control Techniques for Active Seat Suspension Systems

Al-Ashmori

Wang

2020

Applied Sciences

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Drivers of heavy trucks are exposed to large amounts of vibration which can lead to serious health risks. Many suspension systems/methods can be used to isolate these transmitted vibrations, such as vehicle suspension systems, cabin suspension systems and seating suspension systems. The central idea of the work is to identify the research gaps and raise our future research questions in this specific area. The novelty of this paper is proposing a model predictive controller for active vibration control of seating suspension systems. A systematic literature review of the existing work of the vibration control of seating suspension systems has been conducted. Various control techniques that are used in the seating suspension systems have been summarized and evaluated. This paper focusses on the biodynamic model of the driver and seat for the first step needed in the design of the seating suspension system. Then, it illustrates the different types of the system vibration controls and their performance evaluation methods. At the end, the paper details several active seating suspension systems including their actuation system structures and control algorithms which are used in the heavy vehicle trucks.

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“…An adaptive control of a class of nonlinear systems has been presented in [15] and the robustness of the closed-loop system has been proven. In [36], neural network based adaptive control has been extended to the active suspension system with actuator saturation. Adaptive neural control of nonlinear systems with nonsmooth actuator nonlinearity has been considered in [37] and a stable neural network observer has been developed in [1].…”

Section: Introductionmentioning

confidence: 99%

A hierarchical Lyapunov-based cascade adaptive control scheme for lower-limb exoskeleton

Zhang

Jiang

Li³

et al. 2019

European Journal of Control

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This paper proposes a hierarchical Lyapunov-based adaptive cascade control scheme for a lower-limb exoskeleton with control saturation. The proposed approach is composed by two control levels with cascade structure. At the higher layer of the structure, a Lyapunov-based back-stepping regulator including adaptive estimation of uncertain parameters and friction force is designed for the leg dynamics, to minimize the deviation of the joint position and its reference value. At the lower layer, a Lyapunov-based neural network adaptive controller is in charge of computing control action for the hydraulic servo system, to follow the force reference computed at the high level, also to compensate for model uncertainty, nonlinearity, and control saturation. The proposed approach shows to be capable in minimizing the interaction torque between machine and human, and suitable for possible imprecise models. The robustness of the closed-loop system is discussed under input constraint. Simulation experiments are reported, which shows that the proposed scheme is effective in imposing smaller interaction torque with respect to PD controller, and in control of models with uncertainty and nonlinearity.

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Adaptive neural network control for active suspension system with actuator saturation

Cited by 122 publications

References 55 publications

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

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

A Systematic Literature Review of Various Control Techniques for Active Seat Suspension Systems

A hierarchical Lyapunov-based cascade adaptive control scheme for lower-limb exoskeleton

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