Adaptive Tracking Control of a Common Rail Injection System for Gasoline Engines: A Discrete-Time Integral Minimal Control Synthesis Approach

Montanaro, Umberto; Gaeta, Alessandro di; Giglio, Veniero

doi:10.1109/tcst.2012.2220772

Cited by 15 publications

(32 citation statements)

References 11 publications

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“…Indeed, it is shown that the DTMCSI-PP performs better than the continuous-time MCSI [37] discretized with a Tustin method. Moreover, the novel algorithm yields residual errors that are comparable to the DTMCSI strategy [26], but with the adaptive gains always evolving in a bounded preassigned set.…”

Section: Introductionmentioning

confidence: 99%

“…In more detail, an unbounded drift of adaptive gains may arise when the plant is affected by unmodeled dynamics or disturbances even though they are matched (see, for example, [2,41] and references therein). Such a behavior is occasionally encountered by MCS practitioners, as for example in two relevant plants in the context of the automotive engineering, i.e., the Electronic Throttle Body and the Common Rail [8,26]. However, neither the MCSI algorithm nor the method proposed in [34] solve the gain locking problem systematically, and only slower gain drifting can be achieved.…”

Section: Introductionmentioning

confidence: 99%

“…Since its appearance, MCS controllers have been used in a number of applications as, for example, synchronization of chaotic systems [39], shaking tables in civil engineering [40], active engine mounts [22], hydraulic test rigs [21], cantilever beams [31], electronic throttle valves [11,9], common rail systems [26,25] and electromechanical valve actuators for future camless engines [17]. Moreover, the theoretical body of the MCS has been enhanced with several extensions to the original algorithms for continuous-time and discrete-time systems.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, discrete-time MCS algorithms including integral action (DTMCSI) and integral plus switching action have been proposed in [26,27], respectively.…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, we enhance the Discrete-Time MCS strategy with Integral action (DTMCSI) proposed in [26] by including a Parameter Projection (PP)-based gain locking method. The control aim is to solve the MRAC control problem for discrete-time LTI systems when plant parameters are affected by uncertainties and plant dynamics are subjected to an additive, square-integrable unknown disturbance, while ensuring boundedness of adaptive gains in a given set.…”

Section: Introductionmentioning

confidence: 99%

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Discrete-time integral MRAC with minimal controller synthesis and parameter projection

Montanaro

Olm

2015

Journal of the Franklin Institute

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Model reference adaptive controllers with Minimal Control Synthesis are effective control algorithms to guarantee asymptotic convergence of the tracking error to zero not only for disturbance-free uncertain linear systems, but also for highly nonlinear plants with unknown parameters, unmodeled dynamics and subject to perturbations. However, an apparent drift in adaptive gains may occasionally arise, which can eventually lead to closed-loop instability. In this article, we address this key issue for discrete-time systems under L 2 disturbances using a parameter projection algorithm. A consistent proof of stability of all the closed-loop signals is provided, while tracking error is shown to asymptotically converge to zero. We also show the applicability of the adaptive algorithm for digitally controlled continuous-time plants. The proposed algorithm is numerically validated taking into account a discrete-time LTI system subject to parameter uncertainty, parameter variations and L 2 disturbances. Finally, as a possible engineering application of this novel adaptive strategy, the control of a highly nonlinear electromechanical actuator is considered.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Recently, discrete-time MCS algorithms including integral action (DTMCSI) and integral plus switching action have been proposed in [26,27], respectively.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Discrete-time integral MRAC with minimal controller synthesis and parameter projection

Montanaro

Olm

2015

Journal of the Franklin Institute

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Cycle‐by‐Cycle Adaptive Force Compensation for the Soft‐Landing Control of an Electro‐Mechanical Engine Valve Actuator

Gaeta¹,

Velasco²,

Montanaro³

2014

Asian Journal of Control

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Electro-mechanical valve actuators (EMVA) are a solution for implementing variable valve actuation in internal combustion engines. Their use can increase engine power, reduce fuel consumption and pollutant emissions, while significantly improving engine efficiency. The control of this actuator is a complex task since non-smooth nonlinearities, parameter variations and external forces strongly affect plant dynamics. In addition, the impact of the valve at its end-strokes translates into mechanical wear and unacceptable noise, and in the worst case the electromagnet may also fail to catch the valve, causing system failure. The design of effective control strategies to ensure valve capture with low impact velocities is therefore essential for the correct functioning of such a mechatronic device. In this paper, the control problem of reducing the impact velocity at "landing" known in the literature as soft landing control, is tackled via novel cycle-by-cycle adaptive force compensation control algorithms. Two schemes are presented: a discrete adaptive proportional integral controller to regulate landing velocity to a preassigned set-point, and a gradient descent method based controller to automatically achieve the minimum admissible impact velocity. The effectiveness of both methods in limiting landing velocities is shown numerically using a high predictive simulator of the EMVA system, when considering unknown varying environmental conditions, such as internal friction and external gas pressure forces.

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GPIO Based Sliding Mode Control for Diesel Engine High Pressure Common Rail System

Yuan

Dai

Sun

et al. 2023

Int.J Automot. Technol.

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Adaptive Tracking Control of a Common Rail Injection System for Gasoline Engines: A Discrete-Time Integral Minimal Control Synthesis Approach

Cited by 15 publications

References 11 publications

Discrete-time integral MRAC with minimal controller synthesis and parameter projection

Discrete-time integral MRAC with minimal controller synthesis and parameter projection

Cycle‐by‐Cycle Adaptive Force Compensation for the Soft‐Landing Control of an Electro‐Mechanical Engine Valve Actuator

GPIO Based Sliding Mode Control for Diesel Engine High Pressure Common Rail System

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