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Implementable distributed model predictive control with guaranteed performance properties | IEEE Conference Publication | IEEE Xplore

Implementable distributed model predictive control with guaranteed performance properties


Abstract:

This article describes an implementable distributed MPC framework with guaranteed nominal stability and performance properties. The proposed distributed MPC framework con...Show More

Abstract:

This article describes an implementable distributed MPC framework with guaranteed nominal stability and performance properties. The proposed distributed MPC framework consists of three main components (i) distributed estimator (ii) centralized/distributed target calculation (iii) distributed regulator. State estimation for distributed MPC is addressed using the well established Kalman filtering framework. Disturbance models are employed to eliminate steady-state offset due to modeling errors/unmeasured disturbances. Algorithms with well defined properties are advanced for distributed target calculation and distributed regulation. Incorporation of the proposed distributed MPC framework provides a means to achieve optimal systemwide control performance employing subsystem-based MPCs
Date of Conference: 14-16 June 2006
Date Added to IEEE Xplore: 24 July 2006
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Conference Location: Minneapolis, MN, USA

References

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