Active damping of engine speed oscillations based on learning control

Zaremba, A.T.; Burkov, Ilya V.; Stuntz, R.M.

doi:10.1109/acc.1998.703006

Cited by 22 publications

(10 citation statements)

References 11 publications

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“…In [14], an adaptive sliding neuro-fuzzy approach is suggested and in [15] sliding mode and force dynamics are considered. Active damping based on learning control is presented in [16]. In [4] the main target is to reduce the torsional vibrations of a crankshaft by adjusting the fuel injection duration by minimizing a cost function.…”

Section: Motivationmentioning

confidence: 99%

Active control of speed fluctuations in rotating machines using feedback linearization

Holm

Ballesteros

Beitler

et al. 2012

Proceedings of 2012 UKACC International Conference on Control

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This paper presents a method for actively controlling torsional vibrations in rotating machines caused by angledependent parameters. The work is motivated by rotating machines with crank or cam gear mechanisms that cause fluctuations in the angular speed when the machine is driven by a constant load torque or when the speed is controlled with conventional controllers. A very general model for such a system is introduced and used to derive a control law by feedback linearization. With this control law, the speed fluctuations are completely eliminated and desired linear dynamics can be prescribed for the system. The method is tested in a simulation study with a model of a real industrial machine. Although the proposed method works well, the study is preliminary in the sense that the method has not been applied experimentally and its robustness has not been assessed.

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Section: Motivationmentioning

confidence: 99%

Active control of speed fluctuations in rotating machines using feedback linearization

Holm

Ballesteros

Beitler

et al. 2012

Proceedings of 2012 UKACC International Conference on Control

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“…Remark 1: The Assumption 2 is true in many engineering problems such as in a rolling mill [1], a satellite [19], the shear force between two rotation bodies, orbit/trail systems, a roller-coaster, and a engine crankshaft [16].…”

Section: Preliminary Definitions and Assumptionsmentioning

confidence: 99%

“…position-dependent or velocity-dependent disturbances) exist in various engineering problems. For example, in [16,17], the engine crankshaft speed pulsation was expressed as a Fourier series expansion as a function of position; in [18] it was shown that the network congestion intensity can be a function of the transmission rate; in [19], the external disturbance of the satellite was modelled as a function of the position; in [20], the tyre/ road contact friction was represented as a function of the system state variable; and in [21 -24], cogging forces have been described as position dependent periodic disturbances because of the slotted nature of the primary core. Generally, a cogging force is modelled as a Fourier expansion of the state parameter x.…”

Section: Introductionmentioning

confidence: 99%

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State-dependent periodic adaptive disturbance compensation

Ahn

Chen

2007

IET Control Theory &Amp; Applications

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The state-dependent nonlinear external disturbance compensation problem is considered. No prior information about the disturbance is assumed except the periodicity of the disturbance with respect to a state variable, which is termed a 'state-dependent periodic disturbance.' The key idea of the proposed new adaptive compensation method is to make use of this known state-dependent periodicity. In the first period, an adaptive compensator is designed to guarantee the L 2-stability of the overall system. From the second period and onwards, a stateperiodic adaptive compensator is designed to stabilise the system by using the information stored in the previous period. The Lyapunov stability analysis is performed on the evolution along the trajectory axis. The validity of the proposed state-periodic adaptive control method is illustrated through a simulation example.

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“…The neural network gives interesting results, but it is controlled as a black box, There is no physical meanings and it is difficult to make the adaptation of the parameters. Also, simulations show that a learning control provides adequate active damping of engine crankshaft ripple and high robustness with respect to system parameter variations, especially flywheel inertia [11]. However, the actuator dynamics effects and sensor noise on learning control performance need to be evaluated.…”

Section: Introductionmentioning

confidence: 97%

Torque harmonic reduction in hybrid vehicles

Njeh

Cauët

Coirault

et al. 2010

Proceedings of the 2010 American Control Conference

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In this paper, the authors propose a novel control strategy of torque ripple reduction in hybrid vehicles. The Internal Combustion Engine (ICE) ripples are reduced by an active filter and a Permanent Magnet Synchronous Machine (PMSM). This electric motor is mounted on the crankshaft in order to generate a torque sequence opposing ripple torque. The control strategy is based on a static output feedback synthesis. The problem is reformulated in the time domain with regard to the main order of the fluctuations. An hybrid propulsion complete modeling is achieved from an experimental benchmark. The model is performed at low speed (900rpm). In fact, at this speed, the ripple is very restrictive. Simulation results highlight the control approach interest.

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Active damping of engine speed oscillations based on learning control

Cited by 22 publications

References 11 publications

Active control of speed fluctuations in rotating machines using feedback linearization

Active control of speed fluctuations in rotating machines using feedback linearization

State-dependent periodic adaptive disturbance compensation

Torque harmonic reduction in hybrid vehicles

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