The objective of this research is to address issues related to the platform revolution leading to a third generation of networked control systems. The approach is to address four fundamental issues: (i) How to provide delay guarantees over communication networks to support networked control? (ii) How to synchronize clocks over networks so as to enable consistent and timely control actions? (iii) What is an appropriate architecture to support mechanisms for reliable yet flexible control system design? (iv) How to provide cross-domains proofs of proper performance in both cyber and physical domains?
Intellectual Merit: Currently neither theory nor networking protocols provide solutions for communication with delay constraints. Coordination by time is fundamental to the next generation of event-cum-time-driven systems that cyber-physical systems constitute. Managing delays and timing in architecture is fundamental for cyberphysical systems.
Broader Impact: Process, aerospace, and automotive industries rely critically on feedback control loops. Any platform revolution will have major consequences. Enabling control over networks will give rise to new large scale applications, e.g., the grand challenge of developing zero-fatality highway systems, by networking cars traveling on a highway. This research will train graduate students on this new technology of networked control. The Convergence Lab (i) has employed minority undergraduate students, including a Ron McNair Scholar, as well as other undergraduate and high school researchers, (ii) hosts hundreds of high/middle/elementary school students annually in Engineering Open House. The research results will be presented at conferences and published in open literature.
Cyberphysical systems refer to the new generation of engineered systems that require tight integration of communication, computing and control technologies. Systems of specific and increasing interest are energy systems, transportation systems, water systems, health care systems, etc. Several properties are important for the overall systems. These include issues such as stability, performance, reliability, robustness, safety, etc. Being often safety critical, the last property is of course of specific interest. Going beyond safety however, one would also like the overall system to be efficient. Since these systems feature the interaction of computers for decision-making and control with physical objects, their analysis however poses challenges. A particular difficulty is that they combine the behavior of physical systems, often described by differential equations, with the dynamics of computerized decision making, often modeled by logical discrete dynamics. To make progress on the general problem of safety of cyber-physical systems, as well as specifically in an area of importance, we have studied the problem of automated transportation systems, since it is an important area of cyber-physical systems research. The particular system we have examined is automated roadways and intersections. The development of smart ground transportation systems is important due to their potentially significant impact on safety, the economy, and the environment. While technologies for smart transportation systems have advanced significantly over the last decade, there remain several challenges for the development of transportation systems that are collision free. We have proposed an approach called "Model Predictive Control (MPC)" for the development of provably collision free autonomous ground transportation systems, and presented an autonomous intersection management framework. This approach enables a vehicle to generate its own motion locally in time based on an optimization framework, incorporating constraints based on the states of other vehicles in the neighborhood, such as the speed limit of a road, the maximum values of acceleration and deceleration, etc. Safety and liveness of the traffic are however system-wide properties, not merely neighborhood properties, and the challenge is to augment this distributed optimization with coordination rules that guarantee overall system-wide safety as well as liveness of the traffic. We have designed two vehicle-to-vehicle (V2V) coordination rules, along with a vehicle-to-infrastructure rule. We have established the system-wide safety and liveness of the autonomous traffic based on each vehicle’s MPC motion planner, operating in conjunction with an algorithm that orders vehicles according to their runtime properties. We have also conducted a preliminary comparative simulation study of the throughput performance at an intersection of the above approach against another popular algorithm, the All-Way STOP.
