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Item type:Publication, Access status: without files , Local turnpike properties in finite horizon optimal controlIn optimal control, it is well known that near-optimal trajectories exhibit a turnpike property if the system is strictly dissipative at the considered equilibrium and additional technical conditions are satisfied. In this paper we extend this result to a system which is merely locally strictly dissipative. For the special case of locally positive definite stage costs we show that there exists upper and lower bounds on the optimization horizon for which a local turnpike property becomes visible. For locally strictly dissipative costs we show that the same holds under a condition on the leaving arc of the local turnpike property. Our theoretical findings are illustrated by numerical examples.Publicationtype: Conference Paper6 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A Distributed Linear Quadratic Discrete-Time Game Approach to Formation Control with Collision AvoidanceFormation control problems can be expressed as linear quadratic discrete-time games (LQDTG) for which Nash equilibrium solutions are sought. However, solving such problems requires solving coupled Riccati equations, which cannot be done in a distributed manner. A recent study showed that a distributed implementation is possible for a consensus problem when fictitious agents are associated with edges in the network graph rather than nodes. This paper proposes an extension of this approach to formation control with collision avoidance, where collision is precluded by including appropriate penalty terms on the edges. To address the problem, a state-dependent Riccati equation needs to be solved since the collision avoidance term in the cost function leads to a state-dependent weight matrix. This solution provides relative control inputs associated with the edges of the network graph. These relative inputs then need to be mapped to the physical control inputs applied at the nodes; this can be done in a distributed manner by iterating over a gradient descent search between neighbors in each sampling interval. Unlike inter-sample iteration frequently used in distributed MPC, only a matrix-vector multiplication is needed for each iteration step here, instead of an optimization problem to be solved. This approach can be implemented in a receding horizon manner, this is demonstrated through a numerical example.Publicationtype: Conference Paper17 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , On Stability Analysis of Predictive Flocking Using N-PathsMost publications in the field of model predictive flocking (MPF) present frameworks without providing stability analyses for the proposed schemes. In those providing stability results, one specific line of reasoning is based on the geometric properties of the optimal state sequences, so-called NN -paths. This method is used in several publications to show stability for centralized and distributed MPF schemes. In this paper, we critically discuss this line of reasoning and point out several errors in the NN -path-based analysis. As incorrect statements in assumptions and lemmas cause the lines of reasoning to break, this raises the question of whether the N-path-based line of reasoning is suitable for the MPF stability analysis in general.Publicationtype: Conference Paper34 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A Scalable Approach for Analysing Multi-Agent Systems with Heterogeneous Stochastic Packet LossAn important aspect in jointly analysing networked control systems and their communication is to model the networking in a sufficiently rich but at the same time mathematically tractable way. As such, this paper improves on a recently proposed scalable approach for analysing multi-agent systems with stochastic packet loss by allowing for heterogeneous transmission probabilities and temporal correlation in the communication model. The key idea is to consider the transmission probabilities as uncertain, which facilitates the use of tools from robust control. Due to being formulated in terms of linear matrix inequalities that grow linearly with the number of agents, the result is applicable to very large multi-agent systems, which is demonstrated by numerical simulations with up to 10000 agents.Publicationtype: Conference Paper9