Piecewise affine convex liftings prove to be versatile tools for the analysis and implementation of piecewise affine control systems. This paper contributes to the theory of convex lifting of polyhedral partitions, by introducing a more efficient approach to the treatment of convexly non-liftable partitions or subpartitions. The main contribution is a new algorithmic procedure to refine polyhedral partitions that do not admit a convex lifting, into convexly liftable ones. This proves the potential computational advantages of a precise, local focus on the problematic regions while preserving the internal boundaries of the original partition to be lifted.Additionally, an algorithm to identify those problematic regions is also introduced and some operations with convexly liftable partitions are discussed.

This paper presents a solution to an on-ramp merging trajectory planning problem within a multiple target vehicles environment by employing model predictive control principles. The shrinking horizon MPC (SHMPC) scheme is used to guarantee that the optimal trajectories are selected among the available gaps into which the ego vehicle can merge. For each trajectory, a time-varying terminal set is used to ensure recursive feasibility and to fulfill the safety and obstacle avoidance constraints. To enhance computational efficiency, a procedure is proposed for defining the terminal set to be as large as possible, derived from the offline-calculated maximum controlled invariant set. We present a simple decision mechanism, accounting for safety, comfort, and efficiency. Then, we demonstrate the effectiveness of the proposed solution by applying it to two different scenarios.

The paper describes a novel, publicly available toolbox for piecewise-affine (PWA) convex-lifting. The main goal is to provide a tool for efficient partitions of sets in finite-dimensional spaces with applications in navigation and control design. This objective is achieved by employing a lift-and-project philosophy that relies on performant linear programming optimization and polyhedra manipulation. Once a PWA lifting is constructed, the related polyhedral partition provides an interconnection graph that can be used for path planning, which is considered here as the main application. The paper provides the main theoretical elements of the technique's foundation and describes the toolbox's structure along with the numerical artifacts used for its implementation. Illustrative examples for the practical problems are provided, supporting the claims of efficiency and versatility.

The paper is dedicated to the modeling of the dynamical behavior of a Zinc-Air battery. The main goal is to construct a model-based prediction mechanism for the output voltage of the battery cell as a function of the discharge current profile. There are several difficulties behind this construction, mainly related to the nonlinear behavior, the high influence of the cell geometrical configuration, and ultimately the impact of the measurements in the transitory. The current work goes a step forward with respect to the constant current models developed in the previous studies and enhances a series of modeling hypotheses through the analysis of a piece-wise constant discharge profile. The important advantage of the results presented in the current work is related to the real-data measurements accompanied by the detailed pre-treatment procedures and, finally, to the construction of the model and the comparison with the existing alternative approaches.

The paper analyzes the decentralized deployment policies for scalar multi-agent systems subject to delays. As a main contribution we obtain explicit conditions on the local feedback gains at the level of subsystems, which ensure safe deployment independent of the delays on the measurement of the positions of the neighboring agents. From the theoretic point of view, positive invariance of sets is used as a main concept for the proofs of the results.

The present paper deals with an optimization approach for long-lived transuranic isotopes transmutation carrying out in Accelerator Driven System (ADS). The proposed methods consider the distributions of actinides nuclear concentration in the charged fuel as optimization arguments. The time-evolution of isotopes nuclear concentration fits in a system of ordinary differential equations (ODE), that is considered as dynamical constraints. A gradient-based optimization algorithm is constructed for this system so that the overall reactivity is minimized. Moreover, constraints on robustness and value of effective multiplication factor are incorporated during numerical optimization. Initial nuclear concentration values giving the best results for transuranic isotopes burn-up are computed based on this approach. The paper includes calculation results of actinides nuclear concentration and percentage ratio change, as well as effective multiplication factor and accelerator current dynamics for such initial fuel charge.

The paper presents the control of a doubly fed induction generator (DFIG) connected with a three-level neutral point clamped (3L-NPC) inverter. Model Predictive Direct Power Control (MPDPC) is used using a dynamical model of the DFIG and 3L-NPC inverter. The principle of the proposed control scheme is to use the dynamical model to calculate predictions of the future values of the stator flux, rotor current and DC-link capacitor voltages for all possible configurations of voltage vectors. The active and reactive power can be estimated based on the stator flux and the rotor current. A cost function will be used to obtain the predicted profile which minimizes the error between the active, reactive powers and their references, balance the DC-link capacitor voltage and reduce the switching frequency and common-mode voltage. The optimal switching state that minimizes the cost function is selected and applied to the inverter. Simulation results under different conditions of wind speed are presented and compared with Deadbeat power control and Space Vector Modulation (DPC-SVM). The obtained results show the improved performances of the proposed control method.

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.

The paper deals with the predictive control synthesis for a Pantograph-Catenary (PAC) system. The main difficulty of the control design resides in the time-varying characteristics of the dynamics modeled by a chain of spring-mass elements.

The present work deals with the reference tracking problem for processes with linear dynamics and multi-sensor information which is subjected to delays or communication packets missing. It is shown that fault tolerance can be achieved through the separation between the invariant sets characterizing the closed-loop system with the communication channels with or without defect. For this purpose, a reference governor scheme is designed using a receding horizon technique in order to provide fault detection and isolation (FDI)-compliant reference signals to practically guarantee the sufficient detection conditions in real time.

The presence of a communication network in a control loop induces many imperfections such as varying transmission delays, varying sampling/transmission intervals and packet loss, which can degrade the control performance significantly and can even lead to instability. Various techniques have been proposed in the literature for stability analysis and controller design for these so-called networked control systems (NCSs). The goal of this paper is to survey a particular class of techniques using discrete-time models that are based on polytopic overapproximations of the uncertain NCS model and lead to stability conditions in terms of linear matrix inequalities (LMIs). We discuss the advantages and disadvantages of the existing techniques in both qualitative and quantitative manners. In particular, we apply all methods to a benchmark example providing a numerical comparison of the methods with respect to conservatism as well as numerical complexity.