In this paper, some issues related to design and analysis of real networked control systems （NCS） under the focus of the most likely region of stability are addressed. Such a system is cumbersome due to its inherent...In this paper, some issues related to design and analysis of real networked control systems （NCS） under the focus of the most likely region of stability are addressed. Such a system is cumbersome due to its inherent variable time delays, ranging from microseconds to hours. To show the influence of such huge variations in the control performance, a laboratory-scale luminosity system has been setup using the Internet as part of the control loop with dominant time constant in the order of milliseconds. Proportional and integral （PI） control strategies with and without explicit compensation for the time-delay variations were implemented using an event-driven controller. Using the well-known Monte Carlo method and subsequent analyses of time responses, it has been possible to identify the most likely region of stability. Some experimental results show the influence of the statistical parameters of the delays on the determination of the most likely regions of stability of the NCS and how these can be used in assessment and redesign of the control system. The experiments show that much larger delays than one sample period can be supported by real NCSs without becoming unstable.展开更多
This paper proposes a method for determining the stabilizing parameter regions for general delay control systems based on randomized sampling. A delay control system is converted into a unified state-space form. The n...This paper proposes a method for determining the stabilizing parameter regions for general delay control systems based on randomized sampling. A delay control system is converted into a unified state-space form. The numerical stability condition is developed and checked for sample points in the parameter space. These points are separated into stable and unstable regions by the decision function obtained from some learning method. The proposed method is very general and applied to a much wider range of systems than the existing methods in the literature. The proposed method is illustrated with examples.展开更多
基金supported by the Energy Utility Company of Minas Gerais(CEMIG)
文摘In this paper, some issues related to design and analysis of real networked control systems （NCS） under the focus of the most likely region of stability are addressed. Such a system is cumbersome due to its inherent variable time delays, ranging from microseconds to hours. To show the influence of such huge variations in the control performance, a laboratory-scale luminosity system has been setup using the Internet as part of the control loop with dominant time constant in the order of milliseconds. Proportional and integral （PI） control strategies with and without explicit compensation for the time-delay variations were implemented using an event-driven controller. Using the well-known Monte Carlo method and subsequent analyses of time responses, it has been possible to identify the most likely region of stability. Some experimental results show the influence of the statistical parameters of the delays on the determination of the most likely regions of stability of the NCS and how these can be used in assessment and redesign of the control system. The experiments show that much larger delays than one sample period can be supported by real NCSs without becoming unstable.
文摘This paper proposes a method for determining the stabilizing parameter regions for general delay control systems based on randomized sampling. A delay control system is converted into a unified state-space form. The numerical stability condition is developed and checked for sample points in the parameter space. These points are separated into stable and unstable regions by the decision function obtained from some learning method. The proposed method is very general and applied to a much wider range of systems than the existing methods in the literature. The proposed method is illustrated with examples.
