Workshops

Duration: Half day - afternoon
Room: Pier 8
Presenter: Daniel Abramovitch

Abstract:
Computation is an essential component of implementing any real world control system, but the details of how to make this work are often either left to the individual contributors to figure out or handed off to turn-key vendors. This workshop intends to provide insights, methods, and concrete examples into three major pieces of this subject. First, the workshop will present recent tutorial material (ACC 2023) from the author on real-time computing issues for control systems. This material explains the principal factors affecting the four computing chains inside a feedback system. After this overview, the workshop will spend time on an often-neglected area of computation for control system measurements, whether they be used in the control loop operation or in the system identification used in model building for control. Finally, the workshop will hone in on specific programming methods and components in the controller itself, describing efficient implementation methods and structures. Together these three thrusts should equip the participant with tools that they can apply almost immediately in their work. While the technology of computation constantly changes, the principles that lead any one of those signal chains to be a limiting factor remain the same.

Duration: Full day
Room: Pier 2
Presenter: Russell Rhinehart

Abstract:
This full-day workshop has two objectives: 1) For those in research related to control methods the workshop will reveal successful techniques and issues that need to be incorporated in model based controllers. 2) For those considering implementing first- principles models for control, it will be a practical how-to guide.

Duration: Full day
Room: Pier 3
Presenters: Raman Goyal and Suman Chakravorty

Abstract: 
Data-based control has a long history in the Control community, tracing back to seminal work in adaptive control and system identification. However, much of this past work concentrated, for good reason, on linear time-invariant (LTI) problems. With the rapid advances of Reinforcement Learning (RL) in the past decade, owing partly to the vast increase in computing power, data-based control is enjoying a renaissance and seems poised to advance control synthesis to a slew of new applications that are non-LTI.

Duration: Full day
Room: Pier 4
Presenters: Huazhen Fang, Xinfan Lin, Scott Moura, Simona Onori, and Ziyou Song

Abstract:
Battery energy storage systems are emerging as the backbone of numerous industrial and civilian applications, serving as pivotal components in transitioning the world toward a clean energy era. Their performance and safety critically rely on advanced battery management techniques, which have garnered significant attention from the research community, particularly in the systems and control domain, over the past decade. These concerted efforts have resulted in remarkable progress, harnessing control theory to enable sophisticated, high-performing battery systems across a wide array of applications. 

Duration: Full day
Room: Dockside 1
Presenter: Joshua Pulsipher

Short Summary:
This workshop will be an interactive tutorial on how to model complex nonlinear, continuous-time optimal control problems via InfiniteOpt.jl and JuMP.jl. Leveraging a unifying abstraction for infinite-dimensional optimization (InfiniteOpt) problems, InfiniteOpt.jl is a Julia-based open-source software package that builds upon JuMP.jl to provide an intuitive symbolic modeling environment for many problem classes in dynamic, PDE constrained, and stochastic optimization. Moreover, its extensibility allows researchers to make their cutting-edge techniques accessible to a wide audience of individuals. All these aspects make InfiniteOpt.jl a powerful tool for tackling advanced optimal control problems.

Duration: Full day
Room: Dockside 2
Presenters: Amor Menezes and Ali Mesbah

Abstract:
Foundational 21st-century control theory advances have helped realize practical cyberphysical systems, captured biological system dynamics both mechanistically and phenomenologically, and developed biosystem regulation at multiple interaction scales, from molecules to organisms. At the intersection of these advances lies the field of cybermedical systems. Cybermedical systems are physical or biological constructs that incorporate automated monitoring, manipulation, and testing of biological systems with programmed knowledge and artificial Intelligence, to achieve a goal of improved human health. 

Duration: Full day
Room: Pier 5
Presenters: Thomas Beckers, Jan Drgona, Madelyn Shapiro, Draguna Vrabie, Rolf Findeisen, and Sandra
Hirche

Abstract:
In recent years, there has been an explosion of research on the intersection of machine learning and classical engineering domains. Machine learning is increasingly being used in the development of novel data-driven approaches for modeling and control of dynamical systems, traditionally dominated by physics-based models and scientific computing solvers. On the other hand, engineering and scientific computing principles are changing the machine learning landscape from purely black-box into domain-aware methods by incorporating more structure and prior knowledge into their model architectures and loss functions.

Duration: Full day
Room: Dockside 3
Presenters: Daniel Abramovitch, Sean Andersson, and Craig Buhr

Abstract:
A question one should ask of any advanced algorithm is, “How do we make that work in a real system?” A question one should ask of any industrial control system is, “How do we apply better algorithms to this problem?” The two questions are dual sides of the same “bridging the gap” problem that has hounded control for decades. This workshop will examine practical methods that address this problem from both sides: ways to implement advanced algorithms on real systems and ways to improve industrial control using advanced methods.

Duration: Full day
Room: Dockside 4
Presenters: Mohammad Pirani, Walter Lucia, Ehsan Nekouei, Bruno Sinopoli, and Karl Henrik Johansson

Overview:
Advancements in embedded systems, sensor technologies, communication devices, and artificial intelligence have resulted in vehicles that are pervasively monitored by dozens of digital computing units coordinated via internal vehicular communication networks. While this evolution in vehicle connectivity has propelled major advancements in driving efficiency, it has also introduced a new range of potential risks, including the unwanted access of third parties with malicious motives which can endanger driving safety. For instance, it has been experimentally demonstrated that bypassing the security mechanisms of a vehicle is not difficult for attackers. Moreover, attackers can also completely erase any evidence of their presence.

Duration: Full day
Room: Pier 8
Presenters: Aditya Dave, Logan E. Beaver, Heeseung Bang, and Andreas A. Malikopoulos

Abstract:
As the world grows increasingly well connected, multi-agent systems have encompassed many critical applications such as cooperative robots, networked control systems, power systems, autonomous vehicles, mobility markets, smart cities, economic institutions, and online social networks. Typically, a multi-agent system comprises many decision-makers that must either learn to act or compute coordinated actions to achieve the design objective. A key feature of such systems is the need for decentralized decision-making arising from different factors such as restricted communication, computational limits, and requirements of resilience against the failure of any subgroup of agents. Under these conditions, traditional centralized approaches for both optimal control and reinforcement learning are rendered unsuitable. Thus, studying the confluence of the different approaches to learning and control in multi-agent systems has emerged as a crucial area of research and development.

Duration: Full day
Room: Dockside 6
Presenters: Gioele Zardini, Carlo Cenedese, Emilio Frazzoli, and John Lygeros

Abstract:
Increasing urbanization and exacerbation of sustainability goals threaten the operational efficiency of current transportation systems and confront cities with complex choices with huge impacts on future generations. At the same time, the rise of private, profit-maximizing Mobility Service Providers leveraging public resources, such as ride-hailing companies, entangles current regulation schemes. This calls for tools to study such complex socio-technical problems. In past years, optimization and control played an important role when solving decision-making problems in this space.

Duration: Half day - afternoon
Room: Pier 7
Presenters: Jie Huang, Changran He, Yamin Yan, Selahattin Burak Sarsılmaz, and Ahmet Taha Koru

Abstract:
In cooperative control of multi-agent systems, one of the fundamental problems is to design a distributed control law such that the output of every agent asymptotically tracks a class of references and asymptotically rejects a class of disturbances while preserving the closed-loop stability. The term ‘cooperative output\ regulation’ was coined in the 2010s to refer to this problem. It offers a unifying framework that considers heterogeneity in multi-agent systems, paves the way for a capability of tracking and rejecting a large class of signals, and contains typical cooperative control problems such as leader-following and formation as subcases. The main difficulty here lies in the lack of central authority. In other words, each agent can share information with only their neighbors. From a control theory viewpoint, how should distributed controllers (i.e., local interactions between the agents and control protocols) be structured to ensure that the cooperative output regulation is undertaken?

Duration: Half day - afternoon
Room: Dockside 5
Presenters: Junjie Qin and Sivaranjani Seetharaman

Abstract:
Abstract: As the electrification of transportation becomes a crucial component of sustainable mobility in the future, cities across the globe have set ambitious goals to promote the use of electric vehicles. The increasing penetration of electric vehicles (EVs) altered not only the travel patterns of private car users and fleet operators over the transportation network, but also the power consumption patterns over the distribution power networks, resulting in a tighter coupling between the transportation and power systems.