Synthesis and Experimental Validation of the Novel LQ-NEMCSI Adaptive Strategy on an Electronic Throttle Valve

Bernardo, Mario di; Gaeta, Alessandro di; Montanaro, Umberto; Santini, Stefania

doi:10.1109/tcst.2009.2037610

Cited by 41 publications

(39 citation statements)

References 30 publications

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“…i) The parameter projection method consists of using the parameter projection functions (13) for the computation of the integral part of the adaptive gains (11).…”

Section: Remarkmentioning

confidence: 99%

“…Moreover, manufacturing tolerances, variable operating conditions and mechanical wear often cause uncertainty in system parameter values. The reader is referred to [30,11] for further details.…”

Section: Dtmcsi-pp Control Of An Automotive Actuatormentioning

confidence: 99%

“…Due to its challenging control features, the ETB has often been chosen as an ideal case study to investigate the performance and robustness of adaptive control schemes in the face of model uncertainties and disturbances as discussed, for example, in [11], [1], [3], [28], [7], [18]. Furthermore, when MRAC algorithms are used to tame the ETB dynamics, the presence of unmodeled terms can induce an unbounded drift of the adaptive gains [2], which are undesirable for safety reasons.…”

Section: Dtmcsi-pp Control Of An Automotive Actuatormentioning

confidence: 99%

“…From a modeling viewpoint, it has been show in [11,27] that, by choosing as state variables the position and velocity of the valve and as control input the armature voltage to the DC motor embedded in the system, the ETB dynamics can be approximated as a second order LTI system in control canonical form subjected to nonlinear disturbances, which is required by the DTMCSI-PP algorithm. For all those reasons, the ETB is an excellent device to test the adaptive law presented in Section 2.…”

Section: Dtmcsi-pp Control Of An Automotive Actuatormentioning

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%

See 4 more Smart Citations

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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“…i) The parameter projection method consists of using the parameter projection functions (13) for the computation of the integral part of the adaptive gains (11).…”

Section: Remarkmentioning

confidence: 99%

Section: Dtmcsi-pp Control Of An Automotive Actuatormentioning

confidence: 99%

Section: Dtmcsi-pp Control Of An Automotive Actuatormentioning

confidence: 99%

Section: Dtmcsi-pp Control Of An Automotive Actuatormentioning

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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Stability analysis of a combined direct variable structure adaptive control – the discrete‐time case

Stefanello

Gründling

2016

Adaptive Control & Signal

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This paper presents the proofs of robust stability of a discrete-time robust model reference controller combined with variable structure in an adaptive framework. All the proofs of robust stability are derived for the discrete-time case and are similar to those already existing for the conventional non-combined case. The controller is applied to a SISO LTI plant with unmodeled dynamics of multiplicative and additive types. It is shown that the combined controller can arbitrarily improve the convergence of the error while maintaining the robustness if compared with the non-combined case. Simulation results illustrate the performance of the proposed control strategy.

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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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Synthesis and Experimental Validation of the Novel LQ-NEMCSI Adaptive Strategy on an Electronic Throttle Valve

Cited by 41 publications

References 30 publications

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

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

Stability analysis of a combined direct variable structure adaptive control – the discrete‐time case

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

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