Decision and Control

How can we create systems that can learn from their environment, take decisions based on what is learned and navigate in this environment autonomously in the face of uncertainty? Decision and Control has considered aspects of these questions for many years. Applications are found everywhere: robotics, economics, biology, manufacturing and other academic fields such as computer science and communications. This is a mathematical discipline, drawing on a large range of fields including functional analysis, game theory, probability, statistics and optimization.

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It is commonplace to observe students slinging backpacks across their shoulders, while automatically adjusting their balance to maintain eye contact with the person they are conversing with. Clearly, the balance control system is capable of effortless adaptation to large dynamic loads while maintaining stability. It is easy to overlook the challenges and difficulty of creating and engineering a man-made system with similar capabilities. The central mechanism is feedback, the ability to sense and react to one’s environment. While feedback lies at the heart of most research done in D&C, a significant portion of the group’s research concerns the environmental information required before guarantees can be made about the quality of our solutions.

Networks and Control

Can we wirelessly network cars so they never collide, or operate green buildings so that resource usage and environmental impact are minimized? How should we control networks so information flows efficiently over them? These questions represent challenges in creating future wireless and sensor networks for information flow, or large smart systems that interact with their environment, sometimes called cyberphysical systems, networked control systems or embedded systems.

Social, Economic and Technological Systems

One branch of this research concerns the development of new communication systems and infrastructures. We study the increased use of the electromagnetic spectrum by license-exempt wireless devices, investigating how we can plan for a future that includes ubiquitous communication. Another direction concerns the creation of theory and algorithms to contend with planning and operational decisions in socio-economic systems. A current Department of Energy project concerns the next generation of engineering-economic systems. A key question is, how can we create energy markets that are efficient and reliable?

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Group Contact:
Angie Ellis: 153 CSL
amellisatillinois [dot] edu
Phone: 217-300-1910

Andrew Alleyne: Fluid power systems, nonlinear control
Yuliy Baryshnikov: Nonlinear dynamics and control, applied topology, stochastic processes
Tamer Başar: Control and optimization, multi-agent networked systems, game theory,
pricing and security in networks
Carolyn Beck: Complex systems, dynamic data clustering
Mohamaed Ali Belabbas: Network control systems
Timothy Bretl: Theoretical and algorithmic foundations of robotics and automation, motion planning, control, optimization
Geir Dullerud: Network control, Model validation
Naira Hovakimyan: Adaptation, robustness
Seth Hutchinson: Robotics, computer vision
Cedric Langbort: Theory and applications of distributed control systems
Steven LaValle: Robotics, motion planning
Daniel Liberzon: Nonlinear control theory, analysis and design of hybrid systems
Prashant Mehta: Control using methods of stochastic dynamics
William Perkins (emeritus): Control systems, systems theory
Maxim Raginsky: Statistical signal processing, game theory and stochastic control, optimization, statistical learning, information theory, information processing and decision-making in uncertain environments under resource and complexity constraints
Vasu Salapaka: Scanning probe microscopy, combinatorial optimization
Lui Sha: Distributed real-time computing systems, dynamic real-time architecture
R. Srikant: Communication networks, machine learning, cloud computing
R.S. Sreenivas: Coding and information theory
Dusan Stipanovic: Decentralized control, stability of dynamic systems
Petros Voulgaris: Robust and optimal control and estimation
Dan Work: Control, estimation, and optimization of cyber physical systems, mobile sensing, and inverse modeling and data assimilation