A Backlash Compensator for Drivability Improvement Via Real-Time Model Predictive Control

Rostiti, Cristian; Liu, Yuxing; Canova, Marcello; Stockar, Stephanie; Chen, Gang; Dourra, Hussein; Prucka, Michael

doi:10.1115/1.4039562

Cited by 18 publications

(5 citation statements)

References 18 publications

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“…27 To address undesired oscillations due to backlash, the online MPC, which is a quadratic form-defined optimal control in a receding horizon, has been implemented. 28 In the literatures, 29,30 switching strategies for multiple predictive controllers have addressed the nonlinearity in a powertrain. The MPC controller can produce ideal responses including little error states such as excessive jerks and transient oscillations.…”

Section: Introductionmentioning

confidence: 99%

Experimental verification of active oscillation controller for vehicle drivetrain with backlash nonlinearity based on norm-limited SPSA

Yonezawa,

Kajiwara

2024

Proceedings of the Institution of Mechanical Engineers, Part K:

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To address vehicle drivetrain vibrations that cause discomfort and poor drivability, this study proposes a new active damping strategy with simple backlash compensation based on the simultaneous perturbation stochastic approximation (SPSA) with norm-limited update vector. First, an experimental device developed for a simplified drivetrain mechanism is demonstrated. A mechanism for reproducing both the contact mode and the backlash mode is included in the device. For the contact mode, a model-based [Formula: see text] controller is employed as the baseline damping strategy. Further, to mitigate the backlash effect, a simple algorithm based on mode-switching-based compensation is used with the [Formula: see text] controller. In particular, for the critical controller parameters, this article presents a systematic design approach to search for their optimal values. The key parameters, which are needed for the backlash and contact mode controllers, are simultaneously auto-tuned using norm-limited update vector-based SPSA, which ensures the stability in the iterative tuning. The novelty of this study is that both the backlash mode controller and the contact mode controller are simultaneously optimized by the improved version of SPSA, thus realizing a comprehensive auto-tuning design of an active drivetrain damping system. Finally, the active controller is experimentally verified using the actual test device. Comparative studies show that the proposed approach significantly reduces drivetrain vibrations and is robust against fluctuations in the backlash.

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Section: Introductionmentioning

confidence: 99%

Experimental verification of active oscillation controller for vehicle drivetrain with backlash nonlinearity based on norm-limited SPSA

Yonezawa,

Kajiwara

2024

Proceedings of the Institution of Mechanical Engineers, Part K:

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“…Using predictive controller, a multitude of Kalman filters were employed in order to estimate backlash size in [11]. Moreover, Rostiti et al [12] presented a novel backlash compensator which compensated torque fluctuations for drivetrain, realizing predictive control via real-time model. A state estimator is required in predictive control.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, Rostiti et al. [12] presented a novel backlash compensator which compensated torque fluctuations for drivetrain, realizing predictive control via real‐time model. A state estimator is required in predictive control.…”

Section: Introductionmentioning

confidence: 99%

Variable gain switching exact differential observer‐based compensation control for servo system with backlash

Sun

Wang

et al. 2021

IET Control Theory & Appl

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This paper proposes a novel variable gain switching exact differential observer (SEDO) to deal with the state estimation of mechanical servo system with unknown backlash. In order to compensate unknown non-linear backlash accurately, a switching backlash torque mathematic model is constructed to describe the input-output relationships of backlash. Then, based on the switching backlash torque mathematic model, a novel SEDO with variable gain strategy is implemented to compensate the influence of backlash and estimate system states accurately in terms of the change of real operation conditions . Moreover, the designed controller further alleviates the computational burden by conducting a feedforward compensation strategy, part of which is shared by the observer. It is proven that all the signals in the closed-loop system are bounded, observation error and tracking error are convergent to a small compact set of the origin. Two simulations and two different motor servo test rigs are established to further illustrate the effectiveness of the proposed approach.

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“…3,4 With the development of advanced control algorithm, model-based control has been a hot topic in the area of vehicle low-frequency longitudinal vibration control. 5–8 Templin and Egardt 9 proposed to equate the torsional oscillation of the transmission system to the fluctuated half-shaft torque, and then, tried to eliminate the oscillation by regulating the derivative of the half-shaft torque to zero. This controller is robust to the change of vehicle mass, half-shaft damping and stiffness; and Linear Quadratic Regulator (LQR) weighting coefficients selection is also studied.…”

Section: Introductionmentioning

confidence: 99%

Model reference adaptive LQT control for anti-jerk utilizing tire-road interaction characteristics

Yue

Huang

Hao

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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Sudden vehicle propulsion torque change under tip-in/out maneuver often leads to low-frequency longitudinal vibration due to the flexibility in the half-shaft and tire slip, which greatly affects vehicle drivability. Note that the vibration frequency is between 1 and 10 Hz and is difficult to be absorbed by the vehicle mechanical system. To optimize the vehicle drivability under tip-in maneuver, an Adaptive Linear Quadratic Tracking (ALQT) anti-jerk traction controller is proposed in this paper. Based on the experimental data, a Carsim-Simulink co-simulation model is developed for assessing control performance. A control-oriented model, considering the nonlinear characteristics of the tire-road friction coefficient and slip ratio, is then proposed. A reference model with rigid axle is used to provide the equilibrium points and reference velocity trajectory. Jacobi linearization method is then used to linearize the model along the desired trajectory and a linear deviation model based on equilibrium points is obtained. Finally, the deviation compensation receding horizon LQT controller is designed along with the Kalman state estimation. The effectiveness of the designed controller is assessed via simulation studies under different road surfaces and compared with PID and LQR controllers. The LQT controller is able to track the desired velocity profile with minimum jerk while increasing road safety. Furthermore, the effect of LQT weighting coefficients under different road surfaces are discussed. Simulation results show that the ALQT controller is able to optimize vehicle drivability under different road surfaces and the weighting matrices shall be selected based on the road condition for optimal drivability.

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A Backlash Compensator for Drivability Improvement Via Real-Time Model Predictive Control

Cited by 18 publications

References 18 publications

Experimental verification of active oscillation controller for vehicle drivetrain with backlash nonlinearity based on norm-limited SPSA

Experimental verification of active oscillation controller for vehicle drivetrain with backlash nonlinearity based on norm-limited SPSA

Variable gain switching exact differential observer‐based compensation control for servo system with backlash

Model reference adaptive LQT control for anti-jerk utilizing tire-road interaction characteristics

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