2020
DOI: 10.1109/access.2020.2964116
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Semi-Active Suspension Control Based on Deep Reinforcement Learning

Abstract: The performance of vehicle body vibration and ride comfort of active or semi-active suspension with proper control is better than that with passive suspension. The key to achieve good control effect is that the suspension control system should have strong real-time learning ability according to changes in the road surface and suspension parameters. In the control strategies adopted by previous researchers, the classical neural network controller has some learning ability, but it is mainly based on offline lear… Show more

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Cited by 56 publications
(31 citation statements)
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“…The main idea in order to find matrices is arranging the Equation (11) according to state vector components, performance vector components and the measured signal. Then, results are arranged according to Equation (14). and coefficient of the x, w, u are clarified.…”
Section: Modeling and Control Synthesis Of The Suspension Systemmentioning
confidence: 99%
See 2 more Smart Citations
“…The main idea in order to find matrices is arranging the Equation (11) according to state vector components, performance vector components and the measured signal. Then, results are arranged according to Equation (14). and coefficient of the x, w, u are clarified.…”
Section: Modeling and Control Synthesis Of The Suspension Systemmentioning
confidence: 99%
“…The presented high-level controller is founded on a weighting strategy formulated through a closed-loop architecture shown in Figure 4. Here, G expresses the quarter-car control-oriented model defined in (14), K denotes the designed Linear Parameter Varying (LPV) controller characterized with the scheduling variable ρ responsible for control reconfiguration, u is the control input, y is the measured output, n is the measurement noise, z represents the performance outputs and w is the road disturbance.…”
Section: Modeling and Control Synthesis Of The Suspension Systemmentioning
confidence: 99%
See 1 more Smart Citation
“…There are numerous publications related to design of semi-active suspension control ( [2], [3], [4], [5]) which are safety-oriented problems ( [6], [7]) and comfort-oriented problems( [8], [9]), while most of them don't consider velocity design and several road distortions. This study proposes Rue des Mathématiques, 38402 Grenoble, France.…”
Section: Introductionmentioning
confidence: 99%
“…12 Nevertheless, an enhanced handling of the forthcoming road conditions may require various information sources and the handling of more dynamical motions, which may require nonconventional control solutions, for example, the forthcoming road section is assumed to be reached from LiDAR information, which can use deep-learning-based algorithms for the determination of road roughness. [13][14][15] Although there are several solutions to the control design of semiactive suspension systems (eg, Skyhook, 16  ∞ , gain scheduling, 1 and predictive methods 12 ), the proposed control structure has the advantage of the capability of the preview and the possibility of using increased number of external signals. Thus, the contribution of the article from the side of the application is a semiactive suspension control design framework with which the minimization of the vertical acceleration is improved.…”
Section: Introductionmentioning
confidence: 99%