Decentralised Control of Interconnected Systems: An Interpolation Based Approach

Scialanga, S. and Ampountolas, K. (2017) Decentralised Control of Interconnected Systems: An Interpolation Based Approach. INdAM Workshop on Transport Modeling and Management, Rome, Italy, 6-10 Mar 2017.

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In this work, we present a new framework for the decentralised control problem of largescale interconnected traffic systems with local constraints. The advantages of employing a decentralised control approach are dimensionality and well-structured decoupled information constraints. To this end, we extend an Interpolating based Control (IC) approach for the constrained decentralised control problem of large-scale interconnected systems. IC is a novel approach that incorporates the state and control constraints in the optimal control problem formulation and significantly reduces the computational effort compared to optimisation-based schemes such as Model Predictive Control (MPC). The main idea behind IC is to blend a global low-gain feedback controller that satisfies the control and state constraints with a user-chosen local high-gain controller that has its positively invariant set satisfying the constraints. The advantage here is that both low- and high-gain controllers can be determined off-line while the interpolation between them is performed on-line. For the interpolation a low dimensional Linear Programming (LP) problem is solved on-line at each time step. Proofs of recursive feasibility and asymptotic stability for the case of IC for interconnected systems are given. To investigate the performance of distributed IC, we compare the proposed decentralised control with centralised control for simple systems as well as large-scale interconnected traffic systems.

Item Type:Conference or Workshop Item
Keywords:Decentralised control, interpolating control, invariant sets, linear programming.
Glasgow Author(s) Enlighten ID:Ampountolas, Dr Konstantinos and Scialanga, Sheila
Authors: Scialanga, S., and Ampountolas, K.
College/School:College of Science and Engineering > School of Engineering > Infrastructure and Environment
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