Sampled-Data Reduction of Nonlinear Input-Delayed Dynamics

Mattioni, Mattia; Monaco, Salvatore; Normand‐Cyrot, D.

doi:10.1109/lcsys.2017.2710118

Cited by 13 publications

(4 citation statements)

References 22 publications

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“…Assuming the problem solvable in case of no delay, an IDA-PBC feedback has been constructed based on reduction. Future works concern the extension of this approach to nonlinear Hamiltonian systems, possibly, under sampling using the concepts introduced in [22], [23].…”

Section: Discussionmentioning

confidence: 99%

IDA-PBC for LTI Dynamics Under Input Delays: A Reduction Approach

Mattioni

Monaco

Normand‐Cyrot

2021

IEEE Control Syst. Lett.

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Section: Discussionmentioning

confidence: 99%

IDA-PBC for LTI Dynamics Under Input Delays: A Reduction Approach

Mattioni

Monaco

Normand‐Cyrot

2021

IEEE Control Syst. Lett.

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“…As for future work, the authors will investigate the ability of conducting a digital control design instead of the classical emulation control for this application. Regarding the control theory, the work in [68,69] could help in analyzing the targeted problem. Acknowledgments: This search was conducted while the first author was studying her phd under the supervision of professor Salvator Monaco from Sapienza University of Rome.…”

Section: Discussionmentioning

confidence: 99%

Asymptotic Output Tracked Artificial Immunity Controller for Eco-Maximum Power Point Tracking of Wind Turbine Driven by Doubly Fed Induction Generator

et al. 2018

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This paper aims to design a controller for a Doubly Fed Induction Generator (DFIG) targeting the Eco-Maximum Power Point Tracking (EMPPT) for environmental aspects. The proposed controller consists of two clusters, which are the novel Artificial Immunity sensorless Eco-Maximum Power Point Tracking (AI EMPPT) and the asymptotic non-linear control techniques. The main target of the AI EMPPT is to reduce the carbon dioxide emission by generating the maximum possible power from the renewable electrical energy resource, which is wind electrical power generation to replace the fossil-fuel conventional generation. To build the AI EMPPT, an Artificial Immunity System Estimator (AISE) based on artificial immunity technique and a Model Reference Adaptive System (MRAS) are used to estimate the DFIG rotor speed. Then, the AI EMPPT is applied to provide the reference electromagnetic torque signal. Subsequently, the reference electromagnetic torque interacts with the estimated generator speed, determined by the wind mechanical power, to supply the wind electrical power. The second cluster is the asymptotic non-linear control technique which proposes the reference signal tracking of the rotor direct and quadratic current, respectively. Thus, assigning specific zeros through feedback ensures the reproduction of an output that converges asymptotically to a required reference rotor current. For online operation, the Artificial Immunity Technique (AIT) is utilized to deal with the generated control reference signal. A proposal hardware implementation on Field Programmed Gate Array (FPGA) is also presented. The introduced approach was applied to a wind turbine generator driving a 3.7 kW load. MATLAB program was used to simulate and test the performance of the proposed control methods. The results to show the effectiveness of the proposed technique. The reduction in CO 2 emission was calculated.

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“…4 • denotes the composition of operators and functions. posed in [21] while an alternative solution relying on the concept of reduction has been discussed in [22].…”

Section: Equivalent Sampled-data State Representationsmentioning

confidence: 99%

“…with suitably defined gain matrix |L δ (x)| < 1 is needed. The approximate feedback (22) achieves, at least locally, asymptotic stabilization of the equilibrium with improved robustness performances with respect to uncertainties on the delay length or discarded higher order components in the predictor dynamics. As a matter of fact, I&I introduces a feedback over the prediction error while prediction-based feedback usually work in open-loop (see [19] for a more complete discussion).…”

Section: Iandi Stabilization With Input Delaysmentioning

confidence: 99%