Ionela Prodan

Grenoble Institute of Technology | Grenoble INP · LCIS Laboratory

This work pertains to the generation and use of harmonic functions for obstacle avoidance and target tracking. For each cell of a polyhedral complex, we generate a harmonic potential surface from a Dirichlet-type condition on its boundary. The condition is expressed as a smooth cardinal B-spline curve, thus allowing an efficient computation of the...

This paper shows that the classical conjugate impedance matching used in the UHF RFID is not optimal anymore with new chips that have high sensitivity. The optimal matching allowing to maximize the read range of an RFID system (reader and tag) is introduced. The principle relies on finding the optimal trade-off between the power received by the tag...

In this paper, we introduce the novel concept of economic ports, allowing modular and distributed optimal operation of networked microgrids. Firstly, we design a novel price-based controller for optimal operation of a single microgrid and show asymptotic stability. Secondly, we define novel physical and economic interconnection ports for the microg...

Modern power systems are characterized by low inertia and fast voltage dynamics due to the increase of sources connecting via power electronics and the removal of large traditional thermal generators. Power electronics are commonly equipped with fast controllers that are able to reach a desired voltage setpoint within seconds. In this paper, we pro...

This article proposes a fully distributed energy management algorithm for dc microgrids, resilient to different faults. Specifically, we employ distributed model-predictive control to deal with the uncertainty that characterizes the microgrid operation. The optimization problem is solved at each time step through a distributed optimization algorith...

This paper proposes a Control by Interconnection design, for a class of constrained Port-Hamiltonian systems, which is based on an associated Model Predictive Control optimization problem. This associated optimization problem allows to consider both state and input constraints simultaneously. Based on the first order Karush–Kuhn–Tucker optimality c...

This paper proposes a resilient distributed energy management algorithm able to cope with different types of faults in a DC microgrid system. A distributed optimization method allows to solve the energy management problem without sharing any private data with the network and reducing the computational cost for each agent, with respect to the centra...

We revisit and enhance previous work pertaining to the use of polyhedral potential fields for motion planning in a receding horizon framework. We adapt the standard vertex-based mixed-integer (MI) representations of piecewise affine functions and propose three equivalent formulations which balance the complexity of the geometric representation with...

In this work we present a novel distributed MPC method for microgrid energy management based on distributed optimization. In order to cope with uncertainty in prices and renewable energy production, we adopt a robust min-max approach that optimizes at each time step the worst case scenario of the objective function. Combining the advantages of MPC...

In this paper, a meshed DC microgrid control architecture whose goal is to manage load balancing and efficient power distribution is introduced. A novel combination of port-Hamiltonian (PH) modeling with differential flatness and B-splines parametrization is introduced and shown to improve the microgrid's performance. A three layer supervision stru...

This paper considers a discrete-time scheduling method for the power balancing of a continuous-time DC microgrid system. A high-order dynamics and a resistor network are used for modelling the electrical storage unit and the DC bus of the centralized microgrid system, respectively. A PH (Port-Hamiltonian) formulation on graphs is employed to explic...

This paper deals with the problem of trajectory planning and tracking of a quadcopter system based on the property of differential flatness. Firstly, B-splines characterizations of the flat output allow for optimal trajectory generation subject to waypoints constraints, thrust and angles constraints while minimizing the trajectory length. Secondly,...

This paper extends some previous works on the dissipated energy minimization for an elevator system of a DC microgrid using a combination between differential flatness for the reference generation and predictive control for the reference tracking. The contribution of the present work resides in the validation of constraints at all times thanks to t...

This paper considers the problem of power balancing in a DC microgrid. A PH (port Hamiltonian) formalism is used to describe the system components and interconnections. Energy and power conservation are kept for the discretized model. An economic model predictive controller is used for scheduling the microgrid power management. The proposed approac...

This paper deals with the trajectory tracking problem of a quadcopter system through a two-layer optimization-based control strategy. The top layer controller employs the MPC (Model Predictive Control) method making use of the linearized translation dynamics in order to achieve the thrust and the sets of the reference angles. The lower control laye...

This paper investigates the regulatory control of large-scale irrigation systems under a Distributed Cooperative Model Predictive Control (DCMPC) framework. We first address the challenging issue of providing a mathematical model for an irrigation system with an inherent complex dynamics using the Lattice Boltzmann (LB) method. Next, we discuss dif...

This paper addresses a novel combination between mixed-integer representations and potential field constructions for typical multi-agent marine control problems. First, we prove that for any kind of repulsive functions applied over a function which we denote as sum function, the feasible domain is piece-wise affine (PWA). Next, concepts like hyperp...

This paper considers the problem of modeling a multi-source lift system where power balancing - realized through a power DC bus - should be optimally controlled. The system includes the mechanical part, a Salient Permanent Magnet Synchronous Machine (SPMSM), a battery energy storage unit, a super-capacitor, a solar panel (PV) generation unit as wel...

This paper addresses the challenging energy management problem of a DC-microgrid elevator system using a coherent combination between port-Hamiltonian approach for physical system modeling, differential flatness for profiles generation and predictive control for taking into account constraints, optimization costs and reference profiles. The microgr...

We present an extension of a model predictive control approach for microgrid energy management. We take into account electricity costs, power consumption, generation profiles and power and energy constraints. Uncertainty due to variations in the environment (wind speed), failures and subsequent repairs of the generator, as well as battery lifespan...

Inspired by some practical applications concerning collision avoidance topics, this paper focuses on the optimal control of linear dynamical systems in the presence of a set of adversary constraints. In our opinion, one of the novelties is the type of constraints introduced in the receding horizon optimization problem. These constraints can be cons...

The goal of this thesis is to propose solutions for the optimal control of multi-agent dynamical systems under constraints. Elements from control theory and optimization are merged together in order to provide useful tools which are further applied to different problems involving multi-agent formations. The thesis considers the challenging case of...

This paper addresses a predictive control strategy for Unmanned Air Vehicles in the presence of bounded disturbances. The goal is to guarantee tracking capabilities with respect to a reference trajectory which is pre-specified using the differential flatness formalism. Furthermore, an off-line linearization strategy of the nonlinear model of the ve...

This paper addresses the optimal control of multiple linear agents in the presence of a set of adversary constraints. This type of constraints makes the convergence of the agents' dynamics towards the "natural" equilibrium position, impossible to fulfill. Therefore, this default equilibrium point has to be replaced by a set of equilibrium points or...