In this paper, we propose a method to establish a networked control system that maintains its stability in the presence of certain undesirable incidents on local controllers. We call such networked control systems weakly resilient. We first derive a necessary and sufficient condition for the weak resilience of networked systems. Networked systems do not generally satisfy this condition. Therefore, we provide a method for designing a compensator which ensures the weak resilience of the compensated system. Finally, we illustrate the efficiency of the proposed method by a power system example based on the IEEE 14-bus test system.

This paper proposes feedback control strategies for the mitigation of torsional stick-slip oscillations in drilling systems using drag bits. Herein, we employ a model for the coupled axial-torsional drill-string dynamics in combination with a rate-independent bit-rock interaction law including both cutting and frictional effects. Using a singular perturbation and averaging approach, we show that the dynamics of this model generate an apparent velocity-weakening effect in the torque-on-bit, explaining the onset of torsional stick-slip vibrations. Based on this dynamic analysis, the (decoupled) torsional dynamics can be described by a delay-differential equation with a state-dependent delay. Using this model, we propose both state-and output-feedback control strategies for the mitigation of torsional stick-slip oscillations, where the latter strategy uses surface measurements only. The effectiveness of the proposed approaches is shown in a simulation study.

The model reduction problem for networks of interconnected dynamical systems is studied in this paper. In particular, networks of identical passive subsystems, which are coupled according to a tree topology, are considered. For such networked systems, reduction is performed by clustering subsystems that show similar behavior and subsequently aggregating their states, leading to a reduced-order networked system that allows for an insightful physical interpretation. The clusters are chosen on the basis of the analysis of controllability and observability properties of associated edge systems, representing the importance of the couplings and providing ameasure of the similarity of the behavior of neighboring subsystems. This reduction procedure is shown to preserve synchronization properties (i.e., the convergence of the subsystem trajectories to each other) and allows for the a priori computation of a bound on the reduction error with respect to external inputs and outputs. The method is illustrated by means of an example of a thermal model of a building.

The operation of groups of heavy-duty vehicles (HDVs) at a small inter-vehicular distance (known as platoon) allows to lower the overall aerodynamic drag and, therefore, to reduce fuel consumption and greenhouse gas emissions. However, due to the large mass and limited engine power of HDVs, slopes have a significant impact on the feasible and optimal speed profiles that each vehicle can and should follow. Therefore maintaining a short inter-vehicular distance as required by platooning without coordination between vehicles can often result in inefficient or even unfeasible trajectories. In this paper we propose a two-layer control architecture for HDV platooning aimed to safely and fuel-efficiently coordinate the vehicles in the platoon. Here, the layers are responsible for the inclusion of preview information on road topography and the real-time control of the vehicles, respectively. Within this architecture, dynamic programming is used to compute the fuel-optimal speed profile for the entire platoon and a distributed model predictive control framework is developed for the real-time control of the vehicles. The effectiveness of the proposed controller is analyzed by means of simulations of several realistic scenarios that suggest a possible fuel saving of up to 12% for the follower vehicles compared to the use of standard platoon controllers.

Freight transportation is of outmost importance in our society and is continuously increasing. At the same time, transporting goods on roads accounts for about 26% of the total energy consumption and 18% of all greenhouse gas emissions in the European Union. Despite the influence the transportation system has on our energy consumption and the environment, road transportation is mainly done by individual long-haulage trucks with no real-time coordination or global optimization. In this paper, we review how modern information and communication technology supports a cyber-physical transportation system architecture with an integrated logistic system coordinating fleets of trucks traveling together in vehicle platoons. From the reduced air drag, platooning trucks traveling close together can save about 10% of their fuel consumption. Utilizing road grade information and vehicle-to-vehicle communication, a safe and fuel-optimized cooperative look-ahead control strategy is implemented on top of the existing cruise controller. By optimizing the interaction between vehicles and platoons of vehicles, it is shown that significant improvements can be achieved. An integrated transport planning and vehicle routing in the fleet management system allows both small and large fleet owners to benefit from the collaboration. A realistic case study with 200 heavy-duty vehicles performing transportation tasks in Sweden is described. Simulations show overall fuel savings at more than 5% thanks to coordinated platoon planning. It is also illustrated how well the proposed cooperative look-ahead controller for heavy-duty vehicle platoons manages to optimize the velocity profiles of the vehicles over a hilly segment of the considered road network.

In this paper, a structure-preserving model reduction approach for a class of nonlinear delay differential equations with time-varying delays is proposed. Benefits of this approach are, firstly, the fact that the delay nature of the system is preserved after reduction, secondly, that input-output stability properties are preserved and, thirdly, that a computable error bound reflecting the accuracy of the reduction is provided. These results are also applicable to large-scale linear delay differential equations with constant delays. The effectiveness of the results is evidenced by means of an illustrative example involving the nonlinear delayed dynamics of the turning process.

Freight transport is of major importance for the European economy and is growing thanks to increasing global trade. About three quarters of inland freight transport in the European Union is on roads. It has the potential to go through a dramatic change over the next decades thanks to the recent development of technologies such as wireless communication, cloud computing, sensor devices, and vehicle electronics. They enable a new integrated goods transport system based on optimized logistics, real-time traffic information, vehicular communications, collaborative driving, and autonomous vehicles. In this paper, we discuss challenges in creating a more efficient and sustainable goods road transportation system and how some of them can be tackled with a networked control approach. In particular, we discuss a method to improve the efficiency of the transportation system by minimizing the number of empty transports needed to fulfill the assignments on a given road network. Assignments with overlapping route segments might lead to further improvements, as the formation of vehicle platoons yields reduced fuel consumption. For realistic scenarios, it is shown that such collaboration opportunities arise already with relatively few vehicles. The fuel-efficient formation and control of platoons is also discussed. Some of the presented methods have been tested on real vehicles in traffic. The paper shows experimental results on automatic formation of vehicle platoons on a Swedish highway. The influence of traffic density on the merge maneuver is illustrated. The results indicate that platoon coordination could be improved by support from appropriate traffic monitoring technologies.

In this paper, we consider designing locally stabilizing controllers, each of which stabilizes each disconnected subsystem, in a distributed manner for large-scale networked linear systems. To this end, we design a low-dimensional hierarchical distributed compensator such that the L-2-performance of the closed-loop system improves as long as that of the locally stabilizing controllers improves. We solve a controller reduction problem where the approximation error of the low-dimensional compensator gets better as long as the performance of the locally stabilizing controllers improves, while preserving the hierarchical distributed structure of the original compensator. Finally, we demonstrate the efficiency of the proposed method through a numerical example of a power network.

The formation of groups of closely-spaced heavy-duty vehicles, known as platoons, reduces the overall aerodynamic drag and therefore leads to reduced fuel consumption and reduced greenhouse gas emissions. This paper focuses on the optimal control of merging maneuvers for the formation of a growing platoon. Hereto, the merging problem is formulated as a hybrid optimal control problem and an algorithm for the computation of optimal merging times and corresponding optimal vehicle trajectories is developed by exploiting an extension of Pontryagin's maximum principle. Moreover, a model predictive control approach on the basis of this algorithm is presented that makes the merging maneuvers robust to modelling uncertainties and external disturbances. The results are illustrated by evaluating a scenario involving three vehicles, which indicates fuel savings of up to 13% with respect to the vehicles driving alone.