Design of Robust Controllers for Active Vehicle Suspension Using the Mixed � Synthesis

Gáspár, Péter; Szászi, István; Bokor, József

doi:10.1076/vesd.40.2.193.16541

Cited by 66 publications

(23 citation statements)

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“…From (9), (13), and (15), one can see that vehicle velocity v 0 influences the values of time frequency internal ω 0 and disturbance exosystem (14). Thus, as the velocity changes, road excitation would change too, and it is important that the OVC should change accordingly.…”

Section: Road Excitation Modelingmentioning

confidence: 97%

“…which denotes the mass uncertainty and the spring uncertainties that are caused by the neglected dynamics, high-order modes, uncertain components, inadequate knowledge of the components (Chen and Huang, 2005;Choi and Han, 2003;and Gaspar et al, 2003).…”

Section: Suspension System Descriptionmentioning

confidence: 99%

“…By using the minimum principle and the dynamical programming, the following result is obtained: Theorem 1. Consider the optimal vibration control problem described by the active suspension system (1) under disturbance (14) with respect to the average quadratic performance index (16). The optimal vibration control is given by…”

Section: Approximative Optimal Vibration Controller Designmentioning

confidence: 99%

See 2 more Smart Citations

Neural Network-Based Supervisory Control for Quarter-Car Suspension with Nonlinearity and Uncertainty

Lei

Guo

2015

Integrated Ferroelectrics

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This paper addresses a neural network (NN)-based vibration control problem for aquarter-car suspension model with nonlinearity and uncertainty. First, combining the state system and the disturbance exosystem, an augmented system is constructed. Thus, an optimal regulator problem of the augmented system is built. After using Pontryagin minimum principle and the dynamic programming approach, an approximative optimal vibration control (OVC) is obtained, which is derived from a Riccati equation and two vector differential equations. A feedforward compensator is designed to suppress the vibration. And through defining the adjoint vectors, the nonlinearity and uncertainty are compensated and the physical realization problem of the disturbance compensation term can be solved. Therefore, supervised by the designed OVC and trained by the designed update rule, the Neural Network-based optimal vibration control (NNOVC) is constructed. Consequentially, the NNOVC enables making the system satisfy performance requirements easily. The related proof is given. Moreover, some numerical simulations are made. It is verified that the NNOVC can replace OVC to control the suspension effectively in face of road excitation and vehicle velocity changes. The effectiveness, flexibility, and the intelligence of NNOVC are illustrated.

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Section: Road Excitation Modelingmentioning

confidence: 97%

Section: Suspension System Descriptionmentioning

confidence: 99%

Section: Approximative Optimal Vibration Controller Designmentioning

confidence: 99%

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Neural Network-Based Supervisory Control for Quarter-Car Suspension with Nonlinearity and Uncertainty

Lei

Guo

2015

Integrated Ferroelectrics

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“…In addition, Ref. [22] proposed a 1-order function c sþw 1 sþw 2 that exerted greater control force in low frequency range than high frequency range. In this paper, however, these weighting functions would be tentatively applied to determine whether it is suitable or not for H1 control of DC-motor-based suspension.…”

Section: H1 Control Strategymentioning

confidence: 98%

Design of active and energy-regenerative controllers for DC-motor-based suspension

Zhang

Cao

2012

Mechatronics

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“…In reference [10] the authors used a robust controller for a full vehicle linear active suspension system using the mixed parameter synthesis. A sliding mode technique is designed for a linear full vehicle active suspension system [11].…”

mentioning

confidence: 99%

Design an Intelligent Controller for Full Vehicle Nonlinear Active Suspension Systems

Aldair

Wang

2011

International Journal on Smart Sensing and Intelligent Systems

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Design of Robust Controllers for Active Vehicle Suspension Using the Mixed � Synthesis

Cited by 66 publications

References 0 publications

Neural Network-Based Supervisory Control for Quarter-Car Suspension with Nonlinearity and Uncertainty

Neural Network-Based Supervisory Control for Quarter-Car Suspension with Nonlinearity and Uncertainty

Design of active and energy-regenerative controllers for DC-motor-based suspension

Design an Intelligent Controller for Full Vehicle Nonlinear Active Suspension Systems

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