Daniel Görges

Energy Management for Smart Grids With Electric Vehicles Based on Hierarchical MPC

This paper presents an energy management system for smart grids with electric vehicles based on hierarchical model predictive control (HiMPC). The energy management system realizes load-frequency control (LFC), an economic operation and an electric vehicle integration into the smart grid. The main component is the HiMPC, which allows covering different time scales, regarding constraints (e.g. power ratings) and predictions (e.g. on renewable generation), as well as rejecting disturbances (e.g. due to fluctuating renewable generation) based on a systematic model- and optimization-based design. For the electric vehicle integration, an aggregator is proposed as link between HiMPC and individual vehicle. The aggregator in particular provides predictions to the HiMPC on the availability of electric vehicles for LFC based on the current mobility demand and the statistical mobility behavior of the vehicle users. Throughout the paper, the energy management system is evaluated for the smart grid of an intermediate city.

Integrated current control, energy control and energy balancing of Modular Multilevel Converters

Modular Multilevel Converters (MMCs) are a new circuit topology to realize multilevel converters. Major advantages of MMCs in comparison to other multilevel converters or standard Voltage Source Converters (VSCs) are lower costs and a modular design for high voltage applications, higher reliability and longer maintenance intervals. However, modular multilevel topologies generally require advanced strategies for controlling and balancing energies since many energy storages are distributed all over the converter. This paper presents a novel integrated strategy for current control, energy control and energy balancing of MMCs. The MMC is modeled as a periodic bilinear time-varying system respecting all currents and energies. Furthermore, a control structure is proposed combining a periodic linear quadratic regulator (PLQR) with an extended and least squares (LS) estimator to determine the currents and energies. Finally, simulation results for converter energizing and transmission startup as well as a phase-to-ground fault are given to illustrate the effectiveness of the strategy.

Suboptimal Event-Triggered Control for Time-Delayed Linear Systems

This technical note considers event-triggering conditions and controller synthesis approaches for delayed linear systems. Optimization problems for minimizing the upper bound of quadratic cost functions are formulated in the form of linear matrix inequalities (LMIs). By solving the optimization problems a unique control gain can be obtained. The performance considered in this technical note includes a linear quadratic cost function for quantifying the control performance and average event times at which the control input must be updated for quantifying the transmission reductions. Comparisons with other approaches in the literature are given to demonstrate the advantages with respect to the two performance indices. Furthermore, an experimental implementation of the proposed methods in an inverted pendulum system shows the applicability and effectiveness in real world.

Event-based networked control and scheduling codesign with guaranteed performance

Besides a fair distribution of limited resources among competing plants in a networked embedded control system (NECS) an efficient utilization of such scarce resources is crucial. Therefore, a novel event-based codesign concept for NECSs with limited communication bandwidth and computation capacity is presented in this paper. The codesign concept involves a joint design of an event-based controller and scheduler (EBCS) for improving the control performance provided that the limited resources are used efficiently. The NECS with a set of interacting continuous-time LTI plants is modeled as a discrete-time switched linear system. The EBCS codesign problem is then formulated as a linear matrix inequality (LMI) optimization problem minimizing an associated quadratic cost function. The EBCS strategy is then evaluated and compared with existing codesign strategies in literature for a simulation study involving a simultaneous stabilization of two mechanically coupled inverted pendulums. It should be remarked finally that the proposed EBCS strategy is generally applicable to discrete-time switched linear systems.

Optimal control and scheduling of networked control systems

This paper addresses optimal control and scheduling of networked control systems (NCSs) where controllers and actuators are connected via a shared communication medium. The NCS is modeled as a discrete-time switched linear system. The control and scheduling strategy are then optimized jointly. Therefor, a receding-horizon control and scheduling (RHCS) problem with a quadratic performance criterion is formulated and solved by (relaxed) dynamic programming. The resulting RHCS strategy can be expressed explicitly as a piecewise linear state feedback control law defined over regions implied by quadratic forms. Closed-loop stability is not guaranteed inherently for the RHCS design. Therefore, an a posteriori stability criterion based on piecewise quadratic Lyapunov functions is given. The effectiveness of the RHCS strategy is evaluated for networked control of an active suspension system.

Optimal control of systems with resource constraints

In this paper optimal control of systems with constrained computation and communication resources is studied. The timing of real-time scheduling algorithms like rate monotonic scheduling and earliest deadline first scheduling is analyzed. It is shown that these scheduling algorithms lead to periodically varying sampling periods and time delays. Modeling of the resulting periodically time-varying systems is described and based on this, the design of a periodic linear quadratic regulator is presented. Applying the lifting technique, a time-invariant reformulation of the design problem is obtained. The regulator gains result from solving algebraic Riccati equations. To further improve control performance, a method which combines offline-scheduling and periodic control is proposed. The methods are illustrated by an example.

Event-Based Control and Scheduling Codesign: Stochastic and Robust Approaches

With the advent of networked embedded control systems (NECSs) new opportunities and challenges have arisen. Among others, the challenges result mostly from variable communication delays, access constraints, and resource constraints. An event-based control and scheduling (EBCS) codesign strategy for NECSs involving a set of continuous-time LTI plants is proposed in this paper addressing all aforementioned challenges. A novel representation of the network-induced delay as an uncertain variable belonging to a finite set of different bounded intervals is further proposed. The transition from one bounded interval to another can be arbitrary or according to a stochastic process. Regarding the type of the transition and the resulting discrete-time switched polytopic system of the NECS, two versions of the EBCS problem are introduced: A robust EBCS problem under arbitrary transition and a stochastic EBCS problem under stochastic transition. Global uniform practical stability with guaranteed performance (measured by a quadratic cost function) is guaranteed for both versions after formulating them as LMI optimization problems. The effectiveness of the proposed EBCS strategy is illustrated along with a comparison between its versions for a set of mobile robots. Notably, the EBCS strategy is generally applicable to discrete-time switched polytopic systems.

Event-based control and scheduling codesign of networked embedded control systems

For networked embedded control systems (NECSs) besides control performance an efficient usage of computation and communication resources is crucial. This paper presents a novel event-based codesign concept for NECSs. The codesign concept involves a joint design of a control law, a scheduler, and an event generator. The control law serves for improving control performance, the scheduler and the event generator for an efficient usage of the limited resources. The codesign problem is formulated as a linear matrix inequality (LMI) problem which can be solved efficiently. The developed theory is evaluated through a simulation for networked embedded control of a set of inverted pendulums. Noteworthy, the codesign concept is generally applicable to discrete-time switched linear systems.

Robust control and scheduling codesign for networked embedded control systems

Robust control and scheduling for networked embedded control systems (NECS) with uncertain but interval-bounded time-varying computation and transmission delay is addressed in this paper. The NECS is described by a set of continuous-time plant models and associated quadratic cost functions. Since the uncertainty of the computation and transmission delay affects the discretized plant models and cost functions in a nonlinear manner, a polytopic overapproximation of the uncertainty utilizing a Taylor series expansion is considered. For the resulting discrete-time switched system model with polytopic uncertainty, a periodic control and online scheduling (PCSon) strategy is proposed to guarantee stability and performance of the resulting controlled system. The design is based on a periodic parameter-dependent Lyapunov function and exhaustive search. Furthermore, a method for reducing the online complexity of the PCSon strategy is presented. The effectiveness of modeling and design is evaluated for networked embedded control of a set of inverted pendulums.

Eco-driving assistance system for electric vehicles based on speed profile optimization

In this paper an eco-driving assistance system for reducing the energy consumption in electric vehcles is proposed. An accurate electric vehicle model is developed and an optimal control problem is formulated. The optimal control problem is solved based on dynamic programming. As a result an energy-optimal speed profile is obtained. This speed profile is displayed to the driver for eco-drving assistance. Experiments indicate that the speed profile can be tracked well by the driver and that the energy consumption can be reduced substantially.