Vibration control of vehicle active suspension system using a new robust neural network control system

Eski, İkbal; Yıldırım, Şahin

doi:10.1016/j.simpat.2009.01.004

Cited by 137 publications

(66 citation statements)

References 15 publications

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“…In this regard, a remarkable number of studies in the literature are dedicated to the efficient energy management of hybrid power systems, including several alternative techniques such as intelligent approaches (ANN, fuzzy logic), optimal control approaches [14], model-based predictive controllers [15], and nonlinear flatness-based control methods [16]. In this study, the ANN approach is chosen due to the effective performance of the ANN method for the control of complex systems [17]. The ANN method is based on the modeling of the human information processing capability that develops itself from learning the example behaviors in different conditions in order to provide a more effective response in case of facing a similar condition.…”

Section: Energy Flow Managementmentioning

confidence: 99%

Role of Energy Management in Hybrid Renewable Energy Systems: Case Study Based Analysis Considering Varying Seasonal Conditions

Yumurtacı¹

2013

Turk J Elec Eng & Comp Sci

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Abstract:The recent popularity of alternative energy technologies is mainly promoted by the increasing awareness of environmental concerns as well as the economic impacts of the depleting fossil fuel reserves. Among several alternative technologies, wind-and solar-based energy have been given specific importance with government-based support for providing a cost-effective structure to realize better penetration of such environmentally friendly sources in the energy market. Even these sources are advantageous over the conventional means of energy production from many aspects, a main drawback being the total dependence on the meteorological conditions (wind speed, solar radiation, temperature, etc.) of the wind and solar systems, as they are not fully reliable to satisfy a particular load demand variation at each instant. Thus, some form of backup is always required that will shift the use of the energy from the moments of renewable-based nondispatchable production to the load demand-based dispatchable production. In this study, to ensure the supply of the load in all of the cases, an electrolyzer-fuel cell-based 'hydrogen regenerative' system is applied as main backup, together with a small-sized battery group to pick up transients. Thus, a hybrid structure including wind, solar, and hydrogen energy technologies is provided. The artificial neural network controller approach is selected for the hybrid system's energy management and its performance is examined and evaluated during different case studies that reflect the variations of the meteorological conditions in different seasons. It is aimed with this study to provide constructive suggestions to upcoming researchers interested in the energy management issue in hybrid systems.

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Section: Energy Flow Managementmentioning

confidence: 99%

Role of Energy Management in Hybrid Renewable Energy Systems: Case Study Based Analysis Considering Varying Seasonal Conditions

Yumurtacı¹

2013

Turk J Elec Eng & Comp Sci

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“…The utilization of direct position feedback control [2,43,55,76,79] and velocity feedback control [27,28,61,81,100] is common and used extensively in experimental AVC applications. Proportional integrating derivative (PID) controllers have proved their worth over the years in numerous industrial applications, and due to the simplicity of the strategy and the analogy with position, velocity and acceleration feedback [34] have also found their place in vibration control [3,18,29,35,36]. These are very well established, albeit somewhat limited control strategies for the modern active vibration applications integrated in high-tech products.…”

Section: The Choice Of Strategy In Active Vibration Controlmentioning

confidence: 99%

Introduction

Takács¹,

Rohal’-Ilkiv²

2012

Model Predictive Vibration Control

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“…An adaptive sliding-mode control is proposed in [9], which uses sprung and unsprung masses variation uncertainties and actuator dynamics for the control of active suspension. A robust artificial neural network control scheme with seven degrees of freedom is proposed in [10]. It is used to control the vibration of active suspension system.…”

Section: Introductionmentioning

confidence: 99%

NeuroFuzzy Adaptive Control for Full-Car Nonlinear Active Suspension with Onboard Antilock Braking System

Riaz

Khan

2015

Arab J Sci Eng

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In this paper, the dynamic behavior of the nonlinear full-car model having active suspensions with nine degrees of freedom including driver, passenger seats and antilock braking system (ABS) is analyzed. The comfort analysis of a driver and passengers of the full car with active suspension model including all forms of nonlinearities is very rare in the literature. The literature also lacks the comfort analysis of the driver and passengers, while the car accelerates and decelerates during cornering. The nonlinearities in the proposed model include the dry friction nonlinearities of the suspension dampers and the geometric nonlinearities of the four corners of the car chassis. Modified adaptive NeuroFuzzy Takagi-Sugeno-Kang (NFTSK) control strategies are presented for the vehicle active suspension control to improve the ride quality, road holding capability and vehicle stability. Separate control strategy is used for ABS to avoid wheel locking and slipping for providing better roadwheel contact. The paper also investigates the coordination of active suspensions and ABS to further enhance the performance of the ABS control. To validate the performance of the proposed intelligent control strategies, the response of the vehicle nonlinear model due to road irregularities is evaluated using various performance indexes. The results are then compared with passive control to verify the performance of modified adaptive NFTSK control.

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Vibration control of vehicle active suspension system using a new robust neural network control system

Cited by 137 publications

References 15 publications

Role of Energy Management in Hybrid Renewable Energy Systems: Case Study Based Analysis Considering Varying Seasonal Conditions

Role of Energy Management in Hybrid Renewable Energy Systems: Case Study Based Analysis Considering Varying Seasonal Conditions

Introduction

NeuroFuzzy Adaptive Control for Full-Car Nonlinear Active Suspension with Onboard Antilock Braking System

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