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The paper is dedicated to the robustness analysis of scalar multi-agent dynamical systems. The open problem we aim to address is the one related to the impact of additive disturbances. Set-theoretic methods are used to achieve the main results in terms of positive invariance and admissible bounds on the disturbances.

Due to the increasing trend of using renewable energy, the development of an energy storage system (ESS) attracts great research interest. A zinc–air battery (ZAB) is a promising ESS due to its high capacity, low cost and high potential to support circular economy principles. However, despite ZABs' technological advancements, a generic dynamic model for a ZAB, which is a key component for effective battery management and monitoring, is still lacking. ZABs show nonlinear behaviour where the steady-state gain is strongly dependent on operating conditions. The present study aims to develop a dynamic model, being capable of predicting the nonlinear dynamic behaviour of a refuellable ZAB, using a linear parameter-varying (LPV) technique. The LPV model is constructed from a family of linear time-invariant models, where the discharge current level is used as a scheduling parameter. The developed LPV model is benchmarked against linear and nonlinear model counterparts. Herein, the LPV model performs remarkably well in capturing the nonlinear behaviour of a ZAB. It significantly outperforms the linear model. Overall, the LPV approach provides a systematic way to construct a robust dynamic model which well represents the nonlinear behaviour of a ZAB.

This paper proposes an invariant-set based minimal detectable fault (MDF) computation method based on the set-separation condition between the healthy and faulty residual sets for discrete-time linear parameter varying (LPV) systems with bounded uncertainties. First, a novel invariant-set computation method for discrete-time LPV systems is developed exclusively based on a sequence of convex-set operations. Notably, this method does not need to satisfy the existence condition of a common quadratic Lyapunov function for all the vertices of the parametric uncertainty compared with the traditional invariant-set computation methods. Based on asymptotic stability assumptions, a family of robust positively invariant (RPI) outer-approximations of minimal robust positively invariant (mRPI) set are obtained by using a shrinking procedure. Based on the mRPI set, the healthy and faulty residual sets can be obtained. Then, by considering the dual case of the set-separation constraint regarding the healthy and faulty residual sets, we transform the guaranteed MDF problem based on the set-separation constraint into a simple linear programming (LP) problem to compute the magnitude of MDF. Since the proposed MDF computation method is robust regardless of the value of scheduling variables in a given convex set, fault detection (FD) can be guaranteed whenever the magnitude of fault is larger than that of the MDF. At the end of the paper, a practical vehicle model is used to illustrate the effectiveness of the proposed method.

In this paper, a new power control strategy based on a model predictive power control for the grid-tie three-level neutral point clamped inverter is presented. A dynamical model based on the orientation of grid voltage is used to predict the performance of control variables required for the system. A cost function that includes the tracking power ability, the neutral-point voltage balancing and switching frequency reduction is used to achieve the optimal switching state. A proposed selection scheme of control input is introduced to comprehend the stability of the closed-loop system and reduce the computational cost. At each sampling time, only candidate switching state inputs that guarantee the stability condition through a control Lyapunov function is evaluated in the cost function of the MPC algorithm. Thus, the execution time is remarkably decreased by 26% in comparison with traditional model predictive control. Moreover, the dead-time effect is compensated by incorporating its influence in the proposed prediction model. Simulation and experimental results compared with the traditional model predictive control are used to confirm the effectiveness of the proposed scheme.

The calculation of piecewise quadratic (PWQ) Lyapunov functions is addressed in view of stability analysis of uncertain piecewise linear dynamics. As main contribution, the linear matrix inequality (LMI) approach proposed in (Johansson and Rantzer, 1998) for the stability analysis of PWL and PWA dynamics is extended to account for parametric uncertainty based on a improved relaxation technique. The results are applied for the analysis of a Phase Locked Loop (PLL) benchmark and the ability to guarantee a stability region in the parameter space well beyond the state of the art is demonstrated.

Dynamic Light Scattering is a technique currently used to assess the particle size and size distribution by processing the scattered light intensity. Typically, the particles to be investigated are suspended in a liquid solvent. An analysis of the particular conditions required to perform a light scattering experiment on particles in air is presented in detail, together with a simple experimental setup and the data processing procedure. The results reveal that such an experiment is possible and using the setup and the procedure, both simplified to extreme, enables the design of an advanced sensor for particles and fumes that can output the average size of the particles in air.

This work aims at analyzing an integrated system of a zinc-air flow battery with a zinc electrolyzer for energy storage application. For efficient utilization of inherently intermittent renewable energy sources, safe and cost-effective energy storage systems are required. A zinc-air flow battery integrated with a zinc electrolyzer shows great promise as an electricity storage system due to its high specific energy density at low cost. A mathematical model of the system was developed. The model was implemented in MATLAB and validated against experimental results. The validation of the model was verified by the agreement between the simulation and experimental polarization characteristic. The behavior and performance of the system were then examined as a function of different operating parameters: the flow rate of the electrolyte, the initial concentration of potassium hydroxide (KOH) and the initial concentration of zincate ion. These parameters significantly affected the performance of the system. The influence of the hydrogen evolution reaction (HER) on the performance of the system was investigated and discussed as it significantly affected the coulombic efficiencies of both the zinc-air flow battery and the zinc electrolyzer. Optimal KOH concentration was found to be about 6–7 M. Whilst increased KOH concentration enhanced the discharge energy of the battery, it also increased HER of both the battery and the electrolyzer. However, higher initial concentration of zincate ion reduced HER and improved the coulombic efficiency of the system. Besides, a higher flow rate of electrolyte enhanced the performance of the system especially at a high charge/discharge current by maintaining the concentration of active species in the cell. Nevertheless, the battery suffered from a higher rate of HER at a high flow rate. It was noted that the model-based analysis provided better insight into the behavioral characteristics of the system leading to an improved design and operation of the integrated system of zinc-air flow battery with the zinc electrolyzer.

Explicit MPC of constrained linear systems is known to result in a piecewise affine controller and therefore also piecewise affine closed loop dynamics. The complexity of such analytic formulations of the control law can grow exponentially with the prediction horizon. The suboptimal solutions offer a trade-off in terms of complexity and several approaches can be found in the literature for the construction of approximate MPC laws. In the present paper a piecewise quadratic (PWQ) Lyapunov function is used for the stability verification of an of approximate explicit Model Predictive Control (MPC). A novel relaxation method is proposed for the LMI criteria on the Lyapunov function design. This relaxation is applicable to the design of PWQ Lyapunov functions for discrete-time piecewise affine systems in general.