2009
DOI: 10.1016/j.automatica.2008.12.011
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Event-driven optimization-based control of hybrid systems with integral continuous-time dynamics

Abstract: In this paper we introduce a class of continuous-time hybrid dynamical systems called integral continuous-time hybrid automata (icHA) for which we propose an event-driven optimization-based control strategy. Events include both external actions applied to the system and changes of continuous dynamics (mode switches). The icHA formalism subsumes a number of hybrid dynamical systems with practical interest, e.g., linear hybrid automata. Different cost functions, including minimum-time and minimum-effort criteria… Show more

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Cited by 25 publications
(21 citation statements)
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“…Proposition Consider the event‐driven MPC scheme applied to a THPN where the cost function is the minimum‐time criterion , and where the terminal constraint is applied on the desired target marking truem̃. If the problem is feasible at time τ 0 with finite cost, then it is recursively feasible and the desired marking is reached in finite time, that is, m(τ) MathClass-rel= truem̃ for τ < ∞ . Proof The result follows from the convergence of the eMLD scheme proved in . Because at time τ 0 problem (19) is feasible with finite cost, due to terminal constraint and minimum‐time criterion, the command sequence μ * ( τ 0 ) brings the marking to the target in finite time J * ( τ 0 ).…”
Section: Event‐driven Control Of Timed Hybrid Petri Net Systemsmentioning
confidence: 96%
See 3 more Smart Citations
“…Proposition Consider the event‐driven MPC scheme applied to a THPN where the cost function is the minimum‐time criterion , and where the terminal constraint is applied on the desired target marking truem̃. If the problem is feasible at time τ 0 with finite cost, then it is recursively feasible and the desired marking is reached in finite time, that is, m(τ) MathClass-rel= truem̃ for τ < ∞ . Proof The result follows from the convergence of the eMLD scheme proved in . Because at time τ 0 problem (19) is feasible with finite cost, due to terminal constraint and minimum‐time criterion, the command sequence μ * ( τ 0 ) brings the marking to the target in finite time J * ( τ 0 ).…”
Section: Event‐driven Control Of Timed Hybrid Petri Net Systemsmentioning
confidence: 96%
“…In , the authors have proposed an event‐driven MLD model (eMLD), leftalignrightalign-oddχMathClass-open(k + 1MathClass-close) align-even = χMathClass-open(kMathClass-close) + B1μMathClass-open(kMathClass-close) + B2δMathClass-open(kMathClass-close) + B3zMathClass-open(kMathClass-close) + B4 rightalign-label(4a) leftalignrightalign-oddyMathClass-open(kMathClass-close) align-even = MathClass-open(kMathClass-close) + D1uMathClass-open(kMathClass-close) + D2δMathClass-open(kMathClass-close) + D3zMathClass-open(kMathClass-close) + D4 rightalign-label(4b) leftalignrightalign-oddE1μMathClass-open(kMathClass-close) + E5xMathClass-open(kMathClass-close) align-even E2δMathClass-open(kMathClass-close) + E3zMathClass-open(kMathClass-close) + E4, rightalign-label(4c) where χ ( k ) = [ x ( k ) ′ τ ( k )] ′ , q MathClass-rel∈ double-struckR0MathClass-bin+, μ ( k ) = [ v ( k ) ′ u d ( k ) ′ q ( k )] ′ . In the eMLD , the counter k represents the number of events, the additional sta...…”
Section: Event‐driven Representationmentioning
confidence: 99%
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“…This produces a Mixed Integer Linear Programming Problem (MILP) whose objective function represents the pursued control goal, e.g., minimum-time, minimum-effort, minimum-displacement, etc, and whose solution contains the control actions that optimize the objective function (Di Cairano et al 2009). Let us exemplify the event-driven control through the net in Fig.…”
Section: Control Under Finite Server Semanticsmentioning
confidence: 99%