Wirelessly Enabled Control of Cyber-Physical Infrastructure with Applications to Hydronic Systems.

Civil infrastructure systems, such as transportation networks, pipe networks, electrical grids, and building environments, are typically managed and controlled with outdated, inefficient, and minimally automated legacy controllers. This is apparent from documented oil pipeline leaks, broad electrical outages, and power plant failures. The relatively recent advents of small inexpensive microcontrollers and low-power wireless networking technologies has revealed opportunities for better managing the operational effectiveness of civil infrastructure systems. Academic research in this field is maturing, yet the field remains in its nascent years of commercial viability, focusing mainly on low data-rate sensing with centralized processing. Little focus has been on distributed wireless control systems for civil infrastructure. This dissertation follows the development and utilization of a new cyber-physical system (CPS) architecture for civil infrastructure. Embedded computing power is distributed throughout the physical systems and global objectives are met with the aid of wireless information exchange. The Martlet wireless controller node was conceived during the first part of this thesis to enable this objective of wirelessly distributed CPS. Once produced, the Martlet was used to realize such a controller, motivated by an application in hydronic cooling systems. The design of the proposed controller began with a study concerning models and objective functions for the control of bilinear systems, like those found in hydronics, when constrained by the resources of a wireless control node. The results showed that previous work with linear quadratic controllers could be improved by using nonlinear models and explicit objective functions. An agent-based controller utilizing the proposed bilinear model-predictive control algorithm, was then developed accounting for the limitation of, and leveraging the advantages of, wireless control nodes in order to regulate a hydronic system with hybrid dynamics. The resulting Martlet based control system was compared to traditional benchmark controllers and shown to achieve adequate performance, with the added benefits of a wireless CPS. These developments in wirelessly distributed control of complex systems are presented not only with the tested hydronic systems in mind, but with the goal of extending this technology to improve the performance and reliability of a wide variety of controlled cyber-physical civil infrastructure systems.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107310/1/mbkane_1.pd

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Sample-Drop Firmness Analysis of TDMA-Scheduled Control Applications

This paper proposes methods for verification of (m, k)-firmness properties of control applications running on a shared TDMA-scheduled processor. We particularly consider dropped samples arising from processor sharing. Based on the available processor budget for any sample that is ready for execution, the Finite-Point (FP) method is proposed for quantification of the maximum number of dropped samples. The FP method is further generalized using a timed automata based model to consider the variation in the period of samples. The UPPAAL tool is used to validate and verify the timed automata based model. The FP method gives an exact bound on the number of dropped samples, whereas the timed-automata analysis provides a conservative bound. The methods are evaluated considering a realistic case study. Scalability analysis of the methods shows acceptable verification times for different sets of parameters