On multi-input chattering-free second-order sliding mode control

Bartolini, G.; Ferrara, Antonella; Usai, Elio; Utkin, Vadim I.

doi:10.1109/9.880629

Cited by 322 publications

(188 citation statements)

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“…One of the most effective consists in artificially increasing the relative degree of the system and designing Higher Order Sliding Mode (HOSM) control laws (Dinuzzo and Ferrara, 2009;Levant, 2003;Shtessel, Edwards, Fridman, and Levant, 2014;Shtessel, Fridman, and Zinober, 2008). Among the HOSM control laws, those of the second order (SOSM control laws) (see, for instance Bartolini, Ferrara, and Usai (1998c); Bartolini, Ferrara, Usai, and Utkin (2000)) are particularly suitable to be applied to microgrids in grid-connected mode since the original relative degree of the microgrid model is 1. Another source of uncertainty in microgrids is the fact that only the nominal values of the parameters of the grid and of the load are typically assumed perfectly known, and their variation could be unpredictable, making the definition of the bounds on the uncertain terms impracticable.…”

Section: Introductionmentioning

confidence: 99%

Adaptive suboptimal second-order sliding mode control for microgrids

Incremona

Cucuzzella

Ferrara

2016

International Journal of Control

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International Journal of Control ASSOSM˙Microgrids˙manuscriptThis paper deals with the design of adaptive suboptimal second order sliding mode (ASSOSM) control laws for grid-connected microgrids. Due to the presence of the inverter, of unpredicted load changes, of switching among different renewable energy sources, and of electrical parameters variations, the microgrid model is usually affected by uncertain terms which are bounded, but with unknown upper bounds. To theoretically frame the control problem, the class of second order systems in Brunovsky canonical form, characterized by the presence of matched uncertain terms with unknown bounds, is first considered. Four adaptive strategies are designed, analyzed and compared to select the most effective ones to be applied to the microgrid case study. In the first two strategies the control amplitude is continuously adjusted, so as to arrive at dominating the effect of the uncertainty on the controlled system. When a suitable control amplitude is attained, the origin of the state-space of the auxiliary system becomes attractive.In the other two strategies a suitable blend between two components, one mainly working during the reaching phase, the other being the predominant one in a vicinity of the sliding manifold, is generated, so as to reduce the control amplitude in steady-state. The microgrid system in grid-connected operation mode, controlled via the selected ASSOSM control strategies, exhibits appreciable stability properties, as proved theoretically and shown in simulation.

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Section: Introductionmentioning

confidence: 99%

Adaptive suboptimal second-order sliding mode control for microgrids

Incremona

Cucuzzella

Ferrara

2016

International Journal of Control

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“…In either case, the method always produces a dynamic controller, contrary to the work by Lu and Spurgeon (1998) and SiraRamirez (1993). The proposed method combines elements from Sira-Ramirez (1993) and Lu and Spurgeon (1998) together with Chang (1990) and Bartolini et. al (2000) and is applicable to a wide class of systems which are not necessarily affine in the control.…”

Section: Supported By Epsrc Grant Reference Gr/m94021mentioning

confidence: 99%

Second Order Sliding Mode Control of Coupled Tanks

Khan

Spurgeon

2005

IFAC Proceedings Volumes

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A second order sliding mode control algorithm is presented for robust control of the liquid level in a pair of interconnected tanks. The controller is implemented on a laboratory rig. The implementation results show robustness to parameter variations such as tank area, the admittance coefficients of various pipes, leakage in the tanks and uncertainty in the pump dynamics. The potential of second order sliding modes for multivariable control is demonstrated.

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“…The main drawback of SMC is the so-called chattering phenomenon, i.e., oscillations of the controlled variable due to the discontinuity of the control input [Boiko et al, 2007;Levant, 2010]. The most effective solution to alleviate this phenomenon is the generation of higher order sliding modes (HOSM), which are able to reduce the chattering effect while maintaining good stability properties [Bartolini et al, 1998[Bartolini et al, , 2000Levant, 2003;Dinuzzo and Ferrara, 2009;Ferrara et al, 2014b].…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Model Predictive/Sliding Mode Control of Nonlinear Constrained Uncertain Systems

2015

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Abstract-This paper presents an overview of some hierarchical control schemes composed by a high level Model Predictive Control (MPC) and a low level Sliding Mode Control (SMC). The latter is realized by using the so-called Integral Sliding Mode (ISM) control approach and is meant to reject the matched disturbances affecting the plant, thus providing a system with reduced uncertainty for the MPC design. Both continuous and discrete-time solutions are discussed in the paper. Moreover, assuming the presence of a network in the control loop, a networked version of the control scheme is presented. It is a model-based event-triggered MPC/ISM control scheme aimed at minimizing the packets transmission. The input-to-state (practical) stability properties of the proposed approaches are also addressed in the paper.

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On multi-input chattering-free second-order sliding mode control

Cited by 322 publications

References 10 publications

Adaptive suboptimal second-order sliding mode control for microgrids

Adaptive suboptimal second-order sliding mode control for microgrids

Second Order Sliding Mode Control of Coupled Tanks

Hierarchical Model Predictive/Sliding Mode Control of Nonlinear Constrained Uncertain Systems

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