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Interconnection between communication and suboptimality for distributed control systems
|Other Titles:||Zusammenhang zwischen Kommunikation und Suboptimalität für verteilte Regelungssysteme||Authors:||Sprodowski, Tobias||Supervisor:||Frese, Udo||1. Expert:||Frese, Udo||2. Expert:||Pannek, Jürgen||Abstract:||
Distributed systems are present in every day's life: For example, distributed systems occur in the form of the internet, system architectures utilising edge computing, robotic scenarios in manufacturing processes, or the upcoming spreading of autonomous, connected vehicles.
Distributed systems require a coordination or communication mechanism and an appropriate choice of control methods. Here, the Distributed Model Predictive Control scheme was applied in various application fields such as process control, robotic scenarios and traffic scenarios. As these robotic or traffic scenarios as examples for distributed systems encounter a high changing dynamic, the chosen coordination and communication mechanism should be efficient due to necessary synchronisation between the subsystems.
A non-cooperative setting is examined, where each subsystem follows an individual target and has to exchange information steadily to ensure first and foremost collision avoidance. With utilisation of wireless communication resources and their finite bandwidth, this work present methods to attenuate the communication effort between the subsystems. Based on a quantisation implemented on the communication exchange between the subsystems, it is shown that each subsystems achieves their assigned target, i.e. the overall system still converge. The improvements for the communication load is presented and for a robotic scenario convergence is shown utilising a weaker assumption than terminal constraints. Additionally, to improve convergence, dynamic priority rules are introduced, which calculate an dynamic optimisation order for the subsystems, where different schemes are utilised: While the first is based on a simple sort based on a priority criterion in every time instant, the latter prevents deadlocks and examine additionally concurrent execution of the subsystems. We close with an overview of possible applications and transformation to other scenarios and give an outlook on further developments.
|Keywords:||Distributed Model Predictive Control; Optimal Control; Distributed Systems; Quantization; Priority rules; Convergence||Issue Date:||18-Mar-2021||Type:||Dissertation||DOI:||10.26092/elib/506||URN:||urn:nbn:de:gbv:46-elib47093||Institution:||Universität Bremen||Faculty:||Fachbereich 03: Mathematik/Informatik (FB 03)|
|Appears in Collections:||Dissertationen|
checked on May 24, 2022
checked on May 24, 2022
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