Electrical and Electronic Engineering - Research Publications
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ItemModel Predictive Control for Lithium-Ion Battery Optimal Charging(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2018-04)Charging time and lifetime are important performances for lithium-ion (Li-ion) batteries, but are often competing objectives for charging operations. Model-based charging controls are challenging due to the complicated battery system structure that is composed of nonlinear partial differential equations and exhibits multiple time-scales. This paper proposes a new methodology for battery charging control enabling an optimal tradeoff between the charging time and battery state-of-health (SOH). Using recently developed model reduction approaches, a physics-based low-order battery model is first proposed and used to formulate a model-based charging strategy. The optimal fast charging problem is formulated in the framework of tracking model predictive control (MPC). This directly considers the tracking performance for provided state-of-charge and SOH references, and explicitly addresses constraints imposed on input current and battery internal state. The capability of this proposed charging strategy is demonstrated via simulations to be effective in tracking the desirable SOH trajectories. By comparing with the constant-current constant-voltage charging protocol, the MPC-based charging appears promising in terms of both the charging time and SOH. In addition, this obtained charging strategy is practical for real-time implementation.
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ItemOptimization Methods on Riemannian Manifolds via Extremum Seeking Algorithms(Society for Industrial and Applied Mathematics, 2018)This paper formulates the problem of extremum seeking for optimization of cost function defined on Riemannian manifolds. We extend the conventional extremum seeking algorithms for optimization problems in Euclidean spaces to optimization of cost functions defined on smooth Riemannian manifolds. This problem falls within the category of online optimization methods. We introduce the notion of geodesic dithers, which is a perturbation of the optimizing trajectory in the tangent bundle of the ambient state manifolds, and obtain the extremum seeking closed loop as a perturbation of the averaged gradient system. The main results are obtained by applying closeness of solutions and averaging theory on Riemannian manifolds. The main results are further extended for optimization on Lie groups. Numerical examples on the Stiefel manifold V3;2 and the Lie group SEp3q are presented at the end of the paper.
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ItemPeriodic event-triggered control of nonlinear systems using overapproximation techniques(PERGAMON-ELSEVIER SCIENCE LTD, 2018-08)In event-triggered control, the control task consisting of sampling the plant's output and updating the control input is executed whenever a certain event function exceeds a given threshold. The event function typically needs to be monitored continuously, which is difficult to realize in digital implementations. This has led to the development of periodic event-triggered control (PETC), in which the event function is only evaluated periodically. In this paper, we consider general nonlinear continuous event-triggered control (CETC) systems, and present a method to transform the CETC system into a PETC system. In particular, we provide an explicit sampling period at which the event function is evaluated and we present a constructive procedure to redesign the triggering condition. The latter is obtained by upper-bounding the evolution of the event function of the CETC system between two successive sampling instants by a linear time-invariant system and then by using convex overapproximation techniques. Using this approach, we are able to preserve the control performance guarantees (e.g., asymptotic stability with a certain decay rate) of the original CETC system.
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ItemConcepts for improved availability and computational power in automated driving(SPRINGER WIEN, 2018-08)Automated vehicles are required to operate on highways and in complex urban scenarios. To safely handle these complex environmental influences, sophisticated automated driving functions demand a high availability of all involved components in combination with increased computational power. Particular multi-core platforms are deployed to cope with these demands. To achieve higher system availability for SAE level 3 and higher, fail operational concepts from system level down to Microcontroller Unit (MCU) level are needed. These concepts include hardware as well as software requirements and are discussed in this paper. For an increased computing performance, the idea and further the model of a parallel computation method for driving functions and their control algorithms is introduced. For that a stabilizing controller is implemented on different cores of the multi-core processor. Finally, this resulting closed-loop system is modeled as a hybrid system which will serve as an input for further stability analysis.
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ItemStability analysis of networked linear control systems with direct-feedthrough terms(PERGAMON-ELSEVIER SCIENCE LTD, 2018-10)We consider networked control systems (NCSs) composed of a linear plant and a linear controller interconnected by packet-based communication channels with communication constraints. We are interested in the setup where direct-feedthrough terms are present in the plant and/or in the controller, a case that is largely ignored in the literature due to its inherent complexity and counterintuitive results in the analysis despite its relevance for important classes of controllers including Proportional–Integral (PI) regulators. This setup calls for a novel stability analysis, for which we take a renewed look at the concept of uniformly globally exponentially stable (UGES) scheduling protocols that turned out to be instrumental in earlier approaches. We provide a generalization of the UGES property, called (DP,DC)-UGES with DP∕DC being the direct-feedthrough matrices of the plant/controller, respectively, and we present generic conditions on these direct-feedthrough terms DP∕DC such that the classical UGES property of scheduling protocols implies (DP,DC)-UGES. This allows us to derive conditions leading to a maximally allowable transmission interval (MATI) such that stability of the overall NCS is guaranteed. In addition, it is shown that it is possible to get more tailored results for the well-known sampled-data (SD), round-robin (RR), and try-once-discard (TOD) protocols leading to less conservative conditions on the direct-feedthrough terms than the generic ones. We also introduce new (DP,DC)-UGES scheduling protocols, designed to handle the direct-feedthrough terms in a more effective way than existing protocols. Our results are illustrated using the example of a batch reactor.
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ItemSingularly Perturbed Networked Control Systems(Elsevier BV, 2018-01-01)We study networked control systems (NCSs) where the controller is given by a state-feedback law and the plant is modeled by a dynamical system evolving on two time-scales, representing a characterization by some slow and fast dynamics. When using the stability analysis frameworks for NCSs from the literature, this time-scale separation is ignored and, as a result, the slow dynamics are in general updated at the same rate as the fast dynamics, leading to many redundant transmissions of the slow dynamics. Therefore, we assume in this paper that the slow dynamics and fast dynamics can be transmitted separately over the network, allowing us to use techniques inspired by singular perturbation methods in the stability analysis. That is, we show by means of a Lyapunov-based proof how to obtain conditions on the transmission rates (expressed in maximal allowable transmission intervals (MATIs)) for the slow and fast dynamics separately such that stability of the NCS is guaranteed, based only on approximated models of the slow and the fast dynamics.
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ItemOvercoming overshoot performance limitations of linear systems with reset control(PERGAMON-ELSEVIER SCIENCE LTD, 2019-03)It is well-known that for a class of minimum-phase relative degree one linear-time-invariant (LTI) systems, with a unit feedback control structure, overshoot necessarily happens if the plant transfer function has poles at origin or unstable poles. This work aims to overcome this overshoot performance limitation (OPL) by using a novel reset controller, which has a generalized first order reset element (GFORE) structure. By tuning parameters of this reset controller carefully, the non-overshoot performance can be ensured. Furthermore, the implementation of the proposed reset controller with a high-pass filter is provided. Parameter tuning guidelines are also provided and, finally, the proposed design is verified with a simulation example.
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ItemCo-design of output feedback laws and event-triggering conditions for the L-2-stabilization of linear systems(Elsevier, 2018-01-01)We investigate the L2-stabilization of linear systems using output feedback event-triggered controllers. In particular, we are interested in the scenario where the plant output and the control input are transmitted to the controller and to the actuators, respectively, over two different digital channels, which have their own sampling rule. The plant dynamics is affected by external disturbances and the output measurement and the control input are corrupted by noises. We present a co-design procedure to simultaneously synthesize dynamic output feedback laws and event-triggering conditions such that the closed-loop system is L2 -stable with a given upper-bound on the L2-gain. The required conditions are formulated in terms of the feasibility of linear matrix inequalities (LMIs). Then, we exploit these LMIs to maximize the guaranteed minimum time between two transmissions of the plant output and/or of the control input. We also present a heuristic method to reduce the amount of transmissions for each channel. The developed technique encompasses time-driven (and so periodic) sampling as a particular case and the result is also new in this context. The effectiveness of the proposed methods is illustrated on a numerical example.
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ItemEnlarging the basin of attraction by a uniting output feedback controller(Elsevier, 2018-04-01)We consider a system for which two predesigned stabilizing output feedback controllers with bounded domains of attraction are known. One renders the system asymptotically stable with some desired performance, and the other provides ultimate boundedness with larger domain of attraction. Assuming that two subsets of the domains of attraction are known, one larger than the other, this work states the problem of combining both controllers with the goal of guaranteeing asymptotic stability properties in the largest subset while the desired performance is locally achieved. We design a switching logic between the controllers that solves the problem, based on the existence of a local tunable observer. The resulting control law is defined by a hybrid output feedback controller. The effectiveness of the proposed solution is illustrated by a numerical example.
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ItemOpen Multi-Agent Systems with Discrete States and Stochastic Interactions(IEEE, 2018-07-01)We consider a multi-agent system in which agents arrive and depart from a network randomly as a Bernoulli process. Each agent that is active in the network must decide between two actions represented by 0 or 1. Each active agent then observes the action of a random neighbour and updates its preference towards a certain action. New agents that arrive into the network are activated with a random preference and action. This means that the notion of consensus in the standard sense can no longer be applied and instead, we provide conditions under which majority action preservation occurs when the number of agents is arbitrarily large. This property will imply that a large fraction of the active agent population will retain their action almost surely.