Sliding mode control using only output information

Edwards, Christopher; Cortes, R.; Spurgeon, Sarah K.

doi:10.1049/ic:19971294

Cited by 4 publications

(4 citation statements)

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“…Strong

{}^{\ast }

detectability is also necessary and sufficient for the existence of first order sliding mode observers, see Reference 18, Chapter 6. The advantage of such observers compared to linear ones is that they can also provide estimates of the unknown input via an equivalent control approach.…”

Section: Introductionmentioning

confidence: 99%

Unknown input observer design for linear time‐invariant systems—A unifying framework

Tranninger

Niederwieser

Seeber

et al. 2022

Intl J Robust & Nonlinear

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This article presents a new observer design approach for linear time invariant multivariable systems subject to unknown inputs. The design is based on a transformation to the so‐called special coordinate basis (SCB). This form reveals important system properties like invertability or the finite and infinite zero structure. Depending on the system's strong observability properties, the SCB allows for a straightforward unknown input observer design utilizing linear or nonlinear observers design techniques. The chosen observer design technique does not only depend on the system properties, but also on the desired convergence behavior of the observer. Hence, the proposed design procedure can be seen as a unifying framework for unknown input observer design.

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“…Strong

{}^{\ast }

Section: Introductionmentioning

confidence: 99%

Unknown input observer design for linear time‐invariant systems—A unifying framework

Tranninger

Niederwieser

Seeber

et al. 2022

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…Continuous-time variable structure and sliding mode control systems have been a topic of extensive research since their introduction about 60 years ago [1,2]. Thanks to their computational efficiency and robustness [3], they have gained many advocates in the control engineering community [4][5][6][7]. Several years later, discrete time sliding mode control systems have also been introduced [8,9] and researched in numerous significant studies .…”

Section: Introductionmentioning

confidence: 99%

Discrete time sliding mode control with reduced switching – a new reaching law approach

Bartoszewicz

Latosiński

2014

Intl J Robust & Nonlinear

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Summary In this paper, a novel reaching law for discrete‐time variable structure systems is proposed. It ensures that the representative point (state) of the controlled plant approaches the switching plane in finite time and then crosses it in every subsequent step. Moreover, the proposed reaching law ensures that for the nominal plant the absolute value of the sliding variable asymptotically decreases to zero, and for the perturbed plant, it converges to a smaller interval around zero than with the application of previously proposed reaching laws. The control method proposed in this paper guarantees asymptotic stability of the nominal system and uniform ultimate boundedness of the perturbed one. Furthermore, the method ensures that the sliding variable rate of change (i.e. the difference between its values at any two subsequent sampling instants) is bounded by design parameters, which do not depend on the system initial conditions. This is a highly desirable property, as it results in a priori specified, ‘almost’ constant convergence rate of the sliding variable when the system state is far off the switching plane and helps enforce state constraints in the system. Copyright © 2014 John Wiley & Sons, Ltd.

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“…Buck DC/DC converter is switching non‐linear system and linear control theory is insufficient to obtain precise and dynamic output response [73]. SM control offers robustness and stability against parameter uncertainties and is therefore motivating choice of nonlinear control system design including Buck converter [74]. SM enforces Buck converter dynamics to follow desired or expected trajectory by continuously switching between continuous structures as per internal state variables.…”

Section: Control System Design and Model Integrationmentioning

confidence: 99%

Artificial neural network assisted robust droop control of autonomous microgrid

Kanwal

Rauf

Khan

et al. 2023

IET Renewable Power Gen

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Electric grid is vulnerable to power imbalance and inertia is the grid's response to overcome such disturbance. Augmentation of power electronic converter based renewable energy technologies like Photovoltaic Generators (PVG) and batteries in utility grid significantly reduces inertia. Inertia degradation is indicated by sharp Rate of Change of Frequency (ROCOF) events due to any grid component failure or imbalance. Fixed gain feedback Proportional Integral Derivative (PID) control is insufficient to deal with varying ROCOF events. This work proposes Sliding Mode (SM) robust droop control scheme assisted by Artificial Neural Network (ANN) algorithm for an islanded PVG integrated microgrid. Droop response is governed by swing equation that uses PVG Maximum Power Point (MPP) forecasted by ANN. ANN forecast is compared with optimized Gaussian process regression algorithm based on mean squared error and speed of training as key performance indicator. The algorithms are trained and validated based on climate dataset of Islamabad, Pakistan. SM control performance is compared with various PID gain settings and qualified as the most suitable against variable source, load and ROCOF scenarios. Finally, significance of accurate MPP forecast for droop control is established by comparing the ANN and deterministic forecaster assisted droop response in a microgrid case study.

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Sliding mode control using only output information

Cited by 4 publications

References 0 publications

Unknown input observer design for linear time‐invariant systems—A unifying framework

Unknown input observer design for linear time‐invariant systems—A unifying framework

Discrete time sliding mode control with reduced switching – a new reaching law approach

Artificial neural network assisted robust droop control of autonomous microgrid

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