ACC 2022 will offer workshops addressing current and future topics in automatic control from experts in academia and industry. The workshops at ACC 2022 will take place in person prior to the conference on Monday and Tuesday, June 6 and 7. 

Conference registrants can sign up for the workshops directly through the registration site. For additional information about Workshops, please contact Workshops Chair, Danny Abramovitch ([email protected]). Please note that workshops are subject to cancellation at the discretion of the organizers due to lack of registrants. Organizers and the chair will do their best to inform workshop registrants of cancellations, but please check the Workshops page at TBD often for current status.

Workshops are primarily planned to be in-person, but some of the workshop organizers will be making an additional virtual version of their workshop available approximately two weeks before the ACC.  This is the first time we are trying this, but we are trying to hold on to some of the outreach made available from our need to be virtual in the past two years.  For those organizers choosing to provide a virtual version of their workshop, there will be a separate registration.  We hope that this allows folks who cannot reach the conference in person to access some of the workshops.  The details for the virtual components will be added as we move along but they will be here when we have them.

Below is a tentative schedule of the available workshops. The rooms and the numbering are still TBD. All times are listed in Eastern Daylight Time (EDT), UTC -4

Workshops by Schedule

Two-Day Workshops (Monday-Tuesday, June 6-7)

Organizers: Thomas A. Badgwell and James B. Rawlings
Location: M101

Model predictive control (MPC) has become the most popular advanced control method in use today. Its main attractive features are (i) optimization of a model forecast over the available actuators (ii) estimation of the state of the system and disturbances from the process measurements, (iii) accounting for the process and actuator constraints, and (iv) accounting for full multivariable interactions. After its introduction in the process industries in the 1970s, MPC has today become a pervasive control technology in many industries and is now being increasingly deployed for optimization of high-level functions such as minimizing energy consumption and maximizing product quality.

This two-day workshop is intended to introduce graduate students and practitioners to the theory and design of MPC systems. Simulation examples are implemented in a high-quality open software environment (python, octave, CasADi).  Students are expected to bring their own laptop computers and to download and install the workshop courseware prior to the class.  The following topics will be covered:

  • Model predictive control: regulation problem, dynamic programming, linear quadratic regulator, constraints, infinite horizon, LQR, constrained regulation.
  • State estimation: least-squares estimator, Kalman filter, observability and convergence.
  • Putting regulation and estimation together: industrial practice, disturbance models, and offset.
  • Nonlinear MPC: introduction, stability, Lyapunov function theory, disturbances and robust stability, nominal stability, suboptimal MPC, inherent robustness of optimal and suboptimal MPC, some examples.
  • Nonlinear moving horizon state estimation: full state estimation, moving horizon estimation with zero prior weighting, nonzero prior weighting, constrained estimation.
  • MPC Prototyping: hot air balloon autopilot

Full-Day Workshops (Monday)

Organizers: Daniel Abramovitch (Agilent Technologies), Sean Andersson (Boston University), and Craig Buhr (Mathworks)
Location: M106

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. We will examine which system identification methods work on which physical systems, as model-based control requires a model. We will discuss why so many industrial controllers are PIDs, present a universal framework for different PID implementations, describe how to tune the PID to the identified system model, and show how to augment these with higher order controller dynamics (a.k.a. filters). We will discuss how to make state-space models more useable in real-time systems. Speaking of which, we will explain how to program filters and PIDs in real-time control systems. We will discuss things to know about hardware implementation and tradeoffs with ADCs, DACs, and analog filters. We will talk about the current set of real-time processing chips and the programming models that go along with them. Throughout we will offer hardware/software demonstrations of how tools like Matlab and Simulink can be used in these contexts. We won’t bridge the gap in a day, but we can move the needle.

A web page that holds the information from the brochure can be found here.

A PDF version of the workshop flyer can be found here.

Prerequisites skills for participants: Undergraduate level knowledge of feedback systems, sampled data systems, and programming. An honest interest in being able to translate control theory into physical control systems.  The workshop is designed to be useful to industry practitioners wishing to apply more advanced control methods as well as academics wishing to make their algorithms more applicable to real world problems.

Half-Day Workshops (Tuesday pm)

Organizers: Yagiz Savas, Melkior Ornik, and Negar Mehr
Location: M104

Overview: The goal of this workshop is to discuss recent advances and research trends in the design of autonomous systems for safety-critical applications. The last decade has witnessed a dramatic increase in the presence of autonomous systems in many domains, ranging from transportation networks to defense systems and healthcare services. Many of these systems are built using costly hardware and operate in uncertain and dynamically changing environments while interacting with humans and other agents. As potential failures can have catastrophic economic and societal consequences, the reliable deployment of these autonomous systems critically depends on the verifiability of the systems’ safety and security.

Assuring certifiably safe autonomy requires a number of challenges to be addressed. The broad challenges that will be discussed in this workshop include, but are not limited to, (i) safe and efficient decision-making under limited information, (ii) on-the-fly system identification and control with safety guarantees, (iii) planning and learning in adversarial environments, and (iv) distributed and resilient learning in multi-agent systems.

Expected outcomes: In this workshop, we expect to bring together experts of diverse backgrounds to discuss the recent approaches for addressing the aforementioned challenges in safety-critical system design, understand the challenges that remain to be addressed in the future, and identify the novel challenges that arise with the emergence of new application areas.

Intended audience: We envision the workshop will be of interest to (i) both junior and senior theoretical researchers working on controls, optimization, learning, and game theory, (ii) applied researchers in the areas of robotics, autonomous cars, and unmanned aerial vehicles, and (iii) students interested in learning about the current challenges in the growing field of autonomy and developing the skill sets to address some of those issues.

For more information about the talks and the speakers, please see the following website:

Full-Day Workshops (Tuesday)

Organizer: R. Russell Rhinehart
Location: M108

This full-day workshop will be a practical guide for those considering the use of first-principles models for control of processes.  First-principles models do not seek full rigor, and they are fully accepted in engineering design, process analysis, and learning.  First-principles models are phenomenological (mechanistic) and mathematically express a specific mechanism, as opposed to being generically empirical.  Fundamental control concepts will be revealed, and the participants should take away the ability to implement several of the simple and effective methods for either SISO or MIMO applications.

The workshop will cover SISO versions of Generic Model Control (with steady state models), which become easy-to-implement output-characterized PI control.  Then move to Process-Model Based Control and Predictive Functional Control (with dynamic models).  It will start with simple unconstrained versions, and progress to constrained nonanalytic applications and on-line model adaptation.  Then the course will cover the use of nonlinear models in a MIMO, constraint-handling MBC structure. 

Participants will receive course notes and software that provides exercises and access to code.  Participants are invited to bring a computer with Excel version 2010 or higher for in-class exploration.  Participants have permission to directly apply the provided software to their specific problems. 

The workshop material is an expansion of material and software on the companion web site

Organizers: Uros Markovic (Embotech) and Craig Buhr (MathWorks)
Location: M107

While an abundance of literature is available on the theory of NMPC, there is a lack concerning the detailed treatment of necessary steps for real-world applications in a serial deployment context, as well as the available tools for such implementation. This full-day workshop will give an overview on Nonlinear Model Predictive Control algorithm development, primarily focusing on the industrial perspective and real-world application. At the beginning, an overview of the topic of real-time Nonlinear MPC will be provided, followed by some best practices and state-of-the-art tools that facilitate the design. Finally, various success stories for application of Nonlinear MPC in real-world systems will be presented. They will especially deal with automotive applications in the fields of EV speed and energy management, economic adaptive cruise control and autonomous driving. The presenters from Embotech and MathWorks will highlight some use cases and experience from their industrial work.

This workshop is intended for students from academia as well as industrial control engineers and industrial researchers on the topic. The attendees should have familiarity with optimization and closed-loop control (however, no in-depth knowledge is necessary). Participants are also encouraged to download and test the workshop material prior to the presentation. In particular, the following topics will be covered and examples provided during this workshop:

  • NMPC design workflow (MathWorks): What steps need to be undertaken to develop an NMPC controller?
  • Model-based rapid prototyping workflow (Embotech): What software tools can be employed to facilitate the NMPC controller design?
  • Platoon adaptive cruise control (Embotech): NMPC example on adaptive cruise control application for heavy-duty platoons
  • EV energy management (Embotech): NMPC example on EV speed control and battery charge management for shortest trip time
  • Tractor-trailer stabilization (Embotech): NMPC example on tractor-trailer stabilization using differential braking
  • Automotive motion planning (Embotech): NMPC motion planning example for automotive applications
  • Motion tracking & highway lane change (MathWorks): Automotive NMPC example on motion tacking and highway lane change
  • Automated parking of tractor-trailer (MathWorks): Automotive NMPC example on motion planning and tracking for parking maneuvers
  • Tips and tricks (MathWorks): Tips and trick for designing an NMPC controller

The workshop material is an expansion of example resources and software provided on the Embotech webpage.

Organizers: Daniel Lofaro, Donald Sofge, Hoa Nguyen, Sridhar Ravi, and Fumin Zhang
Location: L402

The goal of this workshop is to give participants hands-on experience with using lighter-than-air autonomous agents (LTA3) and to discuss the recent advances and trends of these platforms. This will include, but is not limited to, a discussion on platform design, flight dynamics, actuation techniques, sensing capabilities, and control methodologies. These platforms have the potential to greatly improve swarming and human-robot-interaction research in both academic and industrial settings. While these platforms are considerably slower when compared to other miniature aerial vehicles (e.g., fixed wing aircraft, rotorcraft), these platforms can loiter for long time intervals and are extremely safe to fly due to their soft helium envelopes.

During the workshop, participants will have access to physical LTA3 agents in which they will be able to program agents to solve a predefined task. Accompanied with this tutorial will be keynote lectures given by government and industry leaders in the LTA3 field in order to encourage discussion. The tutorial will conclude with a live demonstration of a swarm of LTA3 agents performing the given task as implemented by the participants. Top tutorial participants will also be given one of the LTA3 agents on extended loan to allow them to perform LTA3 research at their home institutions. These participants will be encouraged to participate in our future follow up tutorials on the same topic at IROS 2022.

We envision the workshop will be of interest to applied researchers in the areas of robotics, swarming, and unmanned aerial vehicles, and students interested in learning about the current challenges in the growing field of lighter-than-air agents.

For more information about the talks and the speakers, please see the following website:

Organizers: Wenlong Zhang, Changliu Liu, Shaoshuai Mou, Yue Wang, Ningshi Yao, and Neera Jain
Location: L405

The goal for this workshop is to present recent advancement of human-autonomy interaction and integration. This workshop is motivated by a healthy growth of the body of research in many areas related to systems and control, including but not limited to, design and verification of safe co-robots in an industrial environment, autonomous or assisted driving on highways, human in-the-loop control and monitoring of swarms of unmanned vehicles, and assist-as-needed control of wearable robotics. Canonical control systems design and analysis tools have found their way into solving a small subset of problems but are still largely on a case-by-case basis. Research in this domain require a good balance between model-based methods and learning-based methods, and between fully autonomy and human guidance. Major challenges naturally arise in addressing the lack of first principles and proven mathematical models for human intentions and human behaviors. We have envisioned that the control community will play an increasingly crucial role in human autonomy interaction and integration by taking on challenges including joint decision making, verifiable safety, learning based adaptation, workload and comfort management, trust calibration and control. We aim to report recent research achievements and identify these relevant challenges, as well as a review for testbed and facilities for this domain of research. This full-day workshop will include invited talks, interactive poster sessions, and a panel discussion.

Link to workshop webpage:

Organizers: Jason B. Siegel*, Anna G. Stefanopoulou, Scott Moura, and Xinfan Lin
Location: L406

Overview: Lithium-ion batteries have become economically viable solutions for large-scale energy storage to support renewables and are quickly reaching cost parity with internal combustion engines for transportation. There will be an increasing need for engineers that understand battery systems to design safety and control systems, develop algorithms that perform diagnostics/prognostics, and frameworks to optimize these systems for novel applications. The aim of this workshop is to introduce the methods, algorithms, and models used in developing Battery Management Systems (BMS).

Expected outcomes: At the end of the workshop participants will be able to: 1) Develop models of lithium-ion batteries from experimental data, 2) Understand the key performance metrics of battery systems, 3) Describe the degradation mechanisms responsible for loss in battery capacity and power capability 4) Develop control algorithms which safely operate the battery system and manage degradation while optimizing the performance of the system 5) identify faulty battery cells based on measurements of the current, voltage, and temperature during operation.

Intended audience: The workshop material is intended for engineers with a background in control theory who are interested to learn about batteries, but only requires a basic knowledge of chemistry and physics.

A web page that holds the information from the brochure can be found here.

Organizers: Ye Zhao*, Yan Gu, Ayonga Hereid, and Jason Pusey
Location: M106

The primary purpose of our workshop is to discuss the fundamental challenges in learning, planning, estimation, and control for safe legged robotics in complex, real-world environments. These legged robotic platforms have an enormous potential for swaths of applications, particularly where mobility challenges limit the application of more traditional ground robots. We will host this workshop to present discussion pieces and foster conversations on the true challenges limiting the fielding of legged robots. The workshop proposed this year will be the third series of our ACC locomotion workshops and will feature invited pioneers in the legged robotics community to discuss what they see as technical challenges limiting legged technology. We will focus on the following topics with an eye on their application to legged robots: Learning, Planning, Estimation, and Autonomy.

The workshop website is attached at