Browsing by Author "Olaru S."

Now showing 1 - 4 of 4
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    Distributed Model Predictive Control of Time-Delay Systems
    (2022-11-01) Grancharova A.; Olaru S.
    In this paper, a new approach to distributed MPC of linear interconnected time-delay systems is proposed. The general case of time-delay in both the states and the control inputs is considered. The approach includes representation of the interconnected time-delay dynamics in the augmented state space and reformulation of the centralized MPC problem into a Quadratic Programming framework. The latter this is solved distributedly by using the dual gradient method for optimization. The suggested approach would be appropriate for embedded distributed MPC and is illustrated on a simulation example of two interconnected time-delay systems.
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    Dual-mode distributed Model Predictive Control of a quadruple-tank system
    (2018-01-01) Grancharova A.; Johansen T.A.; Olaru S.
    In this paper, a dual-mode distributed Model Predictive Control (MPC) approach is proposed in order to reduce the on-line computational complexity of the distributed optimal control of nonlinear interconnected systems. It consists in using a nonlinear distributed MPC approach when the state variables of the overall system are far from the origin and applying a linear distributed MPC method in a neighborhood of the origin. The nonlinear distributed approach is based on first-principles (nonlinear) models of the interconnected systems dynamics. It includes a sequential linearization of these models and finding distributedly a suboptimal solution of the resulting quadratic programming problem. In order to apply the linear distributed MPC method, it is necessary first to obtain a linearized model of the overall nonlinear system in a neighborhood of the origin. The benefit of the suggested dual-mode distributed MPC approach is the reduced complexity of the on-line computations in comparison to the entirely nonlinear approach when the current overall system state is in a neighborhood of the origin. The proposed method is illustrated with simulations on the model of a quadruple-tank system.
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    Fault tolerant predictive control for multi-agent dynamical systems: Formation reconfiguration using set-theoretic approach
    (2014-12-23) Nguyen M.T.; Maniu C.S.; Olaru S.; Grancharova A.
    This paper deals with the task assignment problem, which represents a major issue in dynamical formation control. The formation is defined in terms of a group of homogeneous dynamical agents. The position of each agent in the formation is predetermined by pre-imposing the distance between each pair of agents. Recently by using set-theoretic methods, the task assignment has been formulated in terms of an optimization problem allowing to keep the agents in a tight formation in real-time. In this paper we revisit these results and propose a new algorithm for the task assignment formulation in view of real-time control by including fault detection and isolation capabilities. The proposed methods will be illustrated by means of a numerical example.
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    Low Complexity Distributed Model Predictive Control by Using Contractive Sets
    (2017-07-01) Grancharova A.; Olaru S.
    In this paper, an approach to low complexity distributed MPC of linear interconnected systems with coupled dynamics subject to both state and input constraints is proposed. The suggested approach is based on the idea of introducing a contractive set constraint in the centralized MPC problem formulation, which would guarantee the closed-loop system stability when using a small prediction horizon. Then, a dual accelerated gradient method is applied to obtain distributedly a suboptimal solution of the resulting Quadratic Programming problem. The suggested approach would be appropriate for embedded distributed MPC since it will reduce the complexity of the on-line MPC computations, simplify the software implementation, and reduce the requirements for available memory.