On the ergodic control of ensembles
Copyright policy )On the ergodic control of ensembles
Across smart-grid and smart-city application domains, there are many problems where an ensemble of agents is to be controlled such that both the aggregate behaviour and individual-level perception of the system's performance are acceptable. In many applications, traditional PI control is used to regulate aggregate ensemble performance. Our principal contribution in this note is to demonstrate that PI control may not be always suitable for this purpose, and in some situations may lead to a loss of ergodicity for closed-loop systems. Building on this observation, a theoretical framework is proposed to both analyse and design control systems for the regulation of large scale ensembles of agents with a probabilistic intent. Examples are given to illustrate our results.
Journal version of Fioravanti et al. [arXiv:1703.07308, CDC 2017]
- State University of Campinas Brazil
- IBM (United States) United States
- University College Dublin Ireland
- IBM Research - Ireland Ireland
- IBM (Ireland) Ireland
Technology, DEMAND, Transportation, Systems and Control (eess.SY), output regulation, Electrical Engineering and Systems Science - Systems and Control, 09 Engineering, 510, Electric power systems, Automation & Control Systems, Engineering, ITERATED FUNCTION SYSTEMS, PID control, FOS: Mathematics, FOS: Electrical engineering, electronic engineering, information engineering, THEOREM, Nonlinear systems in control theory, stochastic control, Stochastic systems in control theory (general), Mathematics - Optimization and Control, Stochastic modelling, 01 Mathematical Sciences, transportation, INVARIANT-MEASURES, Science & Technology, math.OC, Multi-agent systems, cs.SY, Output regulation, Industrial Engineering & Automation, Linear systems in control theory, Optimization and Control (math.OC), Stochastic control, Electrical & Electronic, electric power systems, 08 Information and Computing Sciences, stochastic modelling
Technology, DEMAND, Transportation, Systems and Control (eess.SY), output regulation, Electrical Engineering and Systems Science - Systems and Control, 09 Engineering, 510, Electric power systems, Automation & Control Systems, Engineering, ITERATED FUNCTION SYSTEMS, PID control, FOS: Mathematics, FOS: Electrical engineering, electronic engineering, information engineering, THEOREM, Nonlinear systems in control theory, stochastic control, Stochastic systems in control theory (general), Mathematics - Optimization and Control, Stochastic modelling, 01 Mathematical Sciences, transportation, INVARIANT-MEASURES, Science & Technology, math.OC, Multi-agent systems, cs.SY, Output regulation, Industrial Engineering & Automation, Linear systems in control theory, Optimization and Control (math.OC), Stochastic control, Electrical & Electronic, electric power systems, 08 Information and Computing Sciences, stochastic modelling
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