Discrete-time drift counteraction stochastic optimal control: Theory and application-motivated examples

Kolmanovsky, Ilya; Lezhnev, L. Yu.; Maizenberg, T.L.

doi:10.1016/j.automatica.2007.06.002

Cited by 29 publications

(40 citation statements)

References 6 publications

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“…The proposed results build upon the previous work [25], where a DP was investigated for a similar class of stochastic systems. Compared to that of [25], the proposed DP can handle systems with additional random disturbances in the continuous state-space. Another contribution is an application of the RL to building control problems with occupant interactions based on the developed DP.…”

Section: Statement Of Contributionsmentioning

confidence: 78%

“…A convergence result of DP for MDP, where continuous and discrete state-spaces coexist and interact with each other, was addressed in [25, Theorem 2,Theorem 3]. However, the proof in [25] cannot be directly applied to our case because for the system in (1), the MDP has stochastic disturbances in continuous state spaces.…”

Section: Remarkmentioning

confidence: 86%

“…For simplicity, we also assume that once the state exists X, it never comes back. In [25], a similar cost function was used, where a constraint set is used instead of the entire state space X. The DP in [25] tried to maximize the exit time by incorporating it into the cost function.…”

Section: Remarkmentioning

confidence: 99%

“…In [25], a similar cost function was used, where a constraint set is used instead of the entire state space X. The DP in [25] tried to maximize the exit time by incorporating it into the cost function. In this paper, even though the constraint is not considered, the exit time regarding X is still required.…”

Section: Remarkmentioning

confidence: 99%

“…For instance, the scenario-based control design schemes are problematic in this case. Such cases arise in many applications, for example, hybrid electric vehicle powertrain management problems [25,26]. One possible approach to solve such complex optimal control problems is to use ADP.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Approximate Dynamic Programming for Building Control Problems with Occupant Interactions

Lee

Karava

et al. 2018

2018 Annual American Control Conference (ACC)

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The goal of this paper is to study potential applicability and performance of approximate dynamic programming (ADP) for building control problems. It is well known that occupants' stochastic behavior affects the thermal dynamics of building spaces. Incorporating occupant interactions in building control system designs is the main focus of this work. We apply ADP to stochastic optimal control designs for illustrative scenarios of occupant-building interactions and demonstrate its validity through a simulation study.

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Section: Statement Of Contributionsmentioning

confidence: 78%

Section: Remarkmentioning

confidence: 86%

Section: Remarkmentioning

confidence: 99%

Section: Remarkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Approximate Dynamic Programming for Building Control Problems with Occupant Interactions

Lee

Karava

et al. 2018

2018 Annual American Control Conference (ACC)

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A novel real‐time energy management strategy for plug‐in hybrid electric vehicles based on equivalence factor dynamic optimization method

2020

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The universal adaptive equivalent consumption minimization strategy (A-ECMS) has the potential of being implemented in real-time for plug-in hybrid electric vehicles (PHEVs). However, the imprecise prediction of a longterm future driving cycle and biggish computation burdens remain the barriers for further real vehicle application. Thus, it is of great significance to develop a real-time optimal energy management strategy for PHEVs by weakening the influence of future driving cycle to the control accuracy and improving its computation efficiency. In this paper, a novel real-time energy management strategy for PHEVs based on equivalence factor (EF) dynamic optimization method is proposed. Firstly, a novel proportional plus integral adaption law for calculating the dynamic optimal EF is established for A-ECMS using only instantaneous information of current vehicle speed and battery state of charge. Second, three key coefficients are obtained and converted into a threedimensional look up tables, so as to determine the dynamic optimal EF. Finally, the method of fast searching the optimal engine torque is proposed, which significantly enhances the computational efficiency. Compared with A-ECMS, the computational time of A-ECMS2 is decreased near 94.8% and the deviation of fuel consumption is controlled within 4.4%. Both the numerical results and hardware-in-loop results prove that the proposed novel energy management strategy A-ECMS2 has better real-time performance and less computing burden than the general A-ECMS.

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Drift counteraction optimal control for deterministic systems and enhancing convergence of value iteration

Zidek

Kolmanovsky

2017

Automatica

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Discrete-time drift counteraction stochastic optimal control: Theory and application-motivated examples

Cited by 29 publications

References 6 publications

Approximate Dynamic Programming for Building Control Problems with Occupant Interactions

Approximate Dynamic Programming for Building Control Problems with Occupant Interactions

A novel real‐time energy management strategy for plug‐in hybrid electric vehicles based on equivalence factor dynamic optimization method

Drift counteraction optimal control for deterministic systems and enhancing convergence of value iteration

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