Towards Computationally Efficient One-Shot Design for Performance-Critical Distributed Multi-Agent Control

University Of Rhode Island, Kingston RI

Investigators

Abstract

Multi-agent systems, an important class of interconnected/networked systems composing a group of distributed interacting entities, have been emerging as a powerful paradigm for various unprecedented engineering applications, such as spacecraft formation flying, air-traffic management, sensory networks, etc. Through collaboration, a multi-agent system can accomplish numerous complicated control tasks that surpass the capability of a single dynamical system, such as moving an oversized object, environmental monitoring, and disaster search/rescue. Moreover, a multi-agent system can solve some problems faster using parallelism and increase robustness through redundancy. However, implementing cooperative multi-agent systems also presents challenges, making many related applications (especially those demanding critical controlled performance) remain conceptual. One important challenge lies in the lack of a systematic approach that allows control engineers to treat associated multi-agent distributed control design in a computationally-efficient and fully-integrated manner. Existing approaches of separating the design into high- and low-level controls often fail to analytically guarantee reliability, which is a critical requirement for acceptance by control engineers. This project supports fundamental research to provide the knowledge needed to overcome these challenges, thereby promoting broader real-world applications of multi-agent distributed control techniques. This project will also create unique opportunities to promote engineering education through the development of a cross-departmental robotics engineering program, and to boost minority involvement in scientific research. The goal of this project is to make fundamental contributions to the advancement of distributed multi-agent control theory by (i) developing novel hybrid switching control schemes to address complicated factors (e.g., agent’s physical dynamics, actuation and data sampling limitations, communication delays) in a holistic, one-shot distributed control design, and (ii) generating effective computational tools from combined deterministic and probabilistic perspectives to enable balancing design complexity and controlled performance. It will introduce innovative methodologies and tools to the field, leading to the following important paradigm changes: (i) from separated two-step designs dominantly adopted in current study to holistic, one-shot designs with provable network stability and controlled performance; (ii) from Lyapunov functions with simple quadratic forms dominantly utilized for current stability analysis and distributed control synthesis to Lyapunov functions with advanced composite forms that would significantly reduce analysis conservatism and improve controlled performance; and (iii) from distributed algorithms with trivial state/output feedback controller structures dominantly exploited by existing methods to distributed algorithms with novel hybrid controller structures of mixed continuous-time and discrete-event dynamics, facilitating simplified distributed optimal control synthesis via off-line convex optimization. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.