LPV modeling and game-theoretic control synthesis to design energy–motion regulators for electric scooters

Hong, Boe-Shong; Su, Wen-Jui; Chou, Chia-Yu

doi:10.1016/j.automatica.2014.02.018

Cited by 4 publications

(4 citation statements)

References 19 publications

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“…Game theory has been widely applied to energy systems (Du et al, 2015;Hong et al, 2014). In previous researches on game theoretic policy for energy systems, fundamental games are usually played between two individual users (Xiao 6 This paper was not presented at any IFAC meeting.…”

Section: Introductionmentioning

confidence: 99%

Evolutionary game theoretic demand-side management and control for a class of networked smart grid

Zhu

Xia

2016

Automatica

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In this paper, a new demand-side management problem of networked smart grid is formulated and solved based on evolutionary game theory. The objective is to minimize the overall cost of the smart grid, where individual communities can switch between grid power and local power according to strategies of their neighbors. The distinctive feature of the proposed formulation is that, a small portion of the communities are cooperative, while others pursue their own benefits. This formulation can be categorized as control networked evolutionary game, which can be solved systematically by using semi-tensor product. A new binary optimal control algorithm is applied to optimize transient performances of the networked evolutionary game.

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Section: Introductionmentioning

confidence: 99%

Evolutionary game theoretic demand-side management and control for a class of networked smart grid

Zhu

Xia

2016

Automatica

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“…Any regular plant ought to be transformed to the canonical form in advance. Compared with the DGKF controllers in [11], this synthesis no longer assumes the Kalman-filtering structure that will otherwise arouse larger conservatism for more 2 L -gain objectives, or result in infeasibility for unobservable state-space realizations. Instead, the feasible set of Luenberger gains is convexly formulated into the LMIs with a slack variable to remove the structural conservatism.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective LPV L2-gain control with game-theoretic synthesis

Hong

2015

2015 10th Asian Control Conference (ASCC)

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It was proved that the DGKF ∞ H -control is still an observer-based control, but the embedded Kalman-filtering has been calibrated by the maximum disturber from the Nash-game perspective. Following such a game-theoretic synthesis, this paper furthers the DGKF ∞ H -control for quadratic regulation of multiple 2 L -gain objectives, which is beyond the capability of the mainstreamed syntheses that counts mostly on sophisticate LMIs algebra. Two aspects of improvement are made: (1) instead of assuming Kalman-filtering, the feasible set of Luenberger gains is formulated into LMIs by a slack variable to remove structural conservatism; and (2) in case of LPV systems, a finite-element method is provided for numerically solving the differential LMIs therefrom.

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“…It is worth noting that the system is always under tracking of throttle commands and disturbances of gravity, so the energy-motion regulation is not specified by the mixed  H / 2 H objective [31][32][33][34], which, in the last decade, has been more popular than double 2 L -gain objective. Here the double-objective LPV 2 L -gain feedback design is improved from the previous game-theoretic control in [23], such that the embedded observer is free of structure conservatism to yield much more excellent performance on energy-motion regulation. Therein, a feasible set of Luenberger gains is allowed, which are formulated into differential linear matrix inequalities (LMIs) by a slack variable, rather than being assumed with the structure of Kalman-filtering.…”

Section: Introductionmentioning

confidence: 99%

“…In types (a), (b) and (c), energy management is focused on batteries and power converters, in which additional components are needed for the fulfillment of efficient energy. However, in type (d), a set of dynamic rules is programmed into the controller, an already existing component, to boost energetic economy [20][21][22][23], with the advantage of no additional hardware. This paper discusses type (d).…”

Section: Introductionmentioning

confidence: 99%

Online Energy Management of City Cars with Multi-Objective Linear Parameter-Varying L2-Gain Control

Hong

2015

Energies

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Abstract:This work aims at online regulating transient current out of the batteries of small-sized electric cars that transport people and goods around cities. In a city with heavy traffic, transient current dominates the energy economy and propulsion capability, which are in opposition to each other. In order to manage the trade-off between energy consumption per distance and propulsion capability in transience, the authors improve on previous work on multi-objective linear parameter-varying (LPV) L2-gain control. The observer embedded into this multi-objective controller no longer assumes Kalman-filtering structure, and structural conservatism is thus removed. A full-spectrum set of experiments is performed. The results reveal that the feedback design significantly improves energy-motion management.

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LPV modeling and game-theoretic control synthesis to design energy–motion regulators for electric scooters

Cited by 4 publications

References 19 publications

Evolutionary game theoretic demand-side management and control for a class of networked smart grid

Evolutionary game theoretic demand-side management and control for a class of networked smart grid

Multi-objective LPV L2-gain control with game-theoretic synthesis

Online Energy Management of City Cars with Multi-Objective Linear Parameter-Varying L2-Gain Control

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