Workshops

The ACC offers well-attended workshops addressing current and future topics in automatic control from experts in academia, national laboratories, and industry. The workshops at ACC 2014 will take place the days prior to the conference. Both half-day and full-day workshops will be offered on Monday, June 2nd and Tuesday, June 3rd.

Advanced registration for preconference workshops will be done through the conference registration website. Onsite registration at the conference venue will also be available.

Monday, June 2nd

Full-day Workshop (8:30am-5:30pm)

Linear, Parameter-Varying Control: Tools and Applications
Organizers: Andrew K. Packard, Peter Seiler, Arnar Hjartarson, Gary J. Balas

Half-day Workshop (1:30pm-5:30pm)

Robust and Adaptive Control Workshop
Organizers: Kevin A Wise, Eugene Lavretsky

Tuesday, June 3rd

Full-day Workshops (8:30am-5:30pm)

Nonlinear Optimization: Techniques for Engineering
Organizer: R. Russell Rhinehart

Subspace Identification of Linear, Parameter Varying, and Nonlinear Systems: Theory, Computation, and Applications
Organizer: Wallace E. Larimore

Open Problems in Multi-Agent Systems
Organizers: Yasamin Mostofi, Magnus Egerstedt

Emerging Frontiers in Adaptive Systems and Learning
Organizers: Tansel Yucelen, Bozenna Pasik-Duncan, Anuradha Annaswamy, Naira Hovakimyan, Susan Frost, Margareta Stefanovic

New Advances in Uncertainty Analysis and Estimation
Organizers: Puneet Singla, Raktim Bhattacharya

40 Years of Robust Control: 1978 to 2018
Organizers: Gary J. Balas, John C. Doyle, Keith Glover, Andrew K. Packard, Peter Seiler, Roy S. Smith

Half-day Workshop (8:30am-12:30pm)

High Level Modeling for Control Systems Development
Organizers: Kenneth R. Butts, Karl Hedrick, Kyle Edelberg

Half-day Workshops (1:30pm-5:30pm)

Developing Battery Management Systems Using Model-Based Design
Organizers: Simona Onori, Federico Baronti

Ubiquitous Hands-On Learning: The Future of Engineering Education
Organizers: Bonnie Ferri, Al Ferri

Special High School Workshop (9:00am-3:00pm)

The Beauty of Controls
Organizers: Bozenna Pasik-Duncan, Ljubo Vlacic

Workshop Descriptions

Monday, June 2nd

Linear, Parameter-Varying Control: Tools and Applications
Organizers: Andrew K. Packard, Peter Seiler, Arnar Hjartarson, Gary J. Balas
Speakers: Gary Balas (University of Minnesota), Arnar Hjartarson (Musyn), Andrew Packard (UC Berkeley) and Pete Seiler (University of Minnesota)

Overview:
This is a full-day workshop, mostly of a tutorial and pragmatic nature. The basic paradigm for Linear, parameter-varying (LPV) control was formulated in the late 80’s to mid-90’s. The LPV framework was motivated by the need for a rigorous methodology to evaluate gain-scheduled controllers formed via interpolation of point designs. The LPV framework provides an intuitive framework for both synthesis and analysis that augments traditional linear metrics of robustness, e.g. classical gain/phase/delay margins and/or MIMO robustness margins, and provides metrics of performance for a class of time-varying nonlinear systems. The paradigm is gaining traction in some industrial applications, notably in aerospace applications for aeroelastic vehicles where it is being used to synthesize controllers that mitigate flutter and other aeroelastic phenomena. The purpose of this 1-day workshop is to present a concise, tutorial summary of the methodology and to introduce practical computer-aided design and analysis tools for implementation. Participants are encouraged to bring laptops and work through the tutorial exercises during the workshop. One-day licenses of Matlab will be available for installation.

Target Audience:
Graduate students without a formal education in LPV control, practitioners in multivariable control analysis and design; control researchers with different specializations wishing to get a quick overview of the field, both in terms of pragmatic tools as well as current application cases. Slides and all code to execute the tutorial examples will be provided.

Morning:
Tutorial session: preliminary linear systems review; linear parameter-varying systems; stability and performance; analysis with parametrized linear matrix inequalities (LMIs); control synthesis with parametrized linear matrix inequalities; controller reconstruction; interactive tutorial exercises; LPV modeling; robust stability and performance of uncertain LPV systems using integral quadratic constraints.

Early afternoon:
Industrial-sized example case: complete, step-by-step process that illustrates how to formulate a problem in the LPV framework, use LPV specific tools to analyze performance and uncover issues related to the parameter dependence of the underlying system, use LPV synthesis techniques to design a parameter-dependent controller to meet a set of requirements.

Late afternoon:
Short discussion of current industrial applications of LPV techniques.

New Developments in Robust and Adaptive Control
Organizers: Kevin A Wise, Eugene Lavretsky
Speaker: Dr. Kevin A. Wise, Dr. Eugene Lavretsky, The Boeing Company

Overview:
This half-day workshop covers new developments in observer-based architectures used in robust and output feedback model reference adaptive control (MRAC), and is presented in two parts. Part 1 introduces a method called Observer-Based Loop Transfer Recovery (OBLTR). Part 2 presents an output feedback MRAC augmentation that is added to the OBLTR architecture, where the observer becomes the reference model. The workshop presents both the theory and design insights into using the adaptive-OBLTR method for flight control problems, including systems with acceleration feedbacks (measurements) that are non-minimum phase. During the design process, the observer is artificially squared-up. This adds fictitious inputs to make the number of controls equal the number of measurements, and makes the observer design model minimum phase. This step is central to asymptotically achieving the positive real behavior during recovery. To place the transmission zeros in a desired location during plant squaring, an LQR or pole-placement algorithm can be used. The OBLTR method’s ability to reduce transients in the closed loop system will be discussed. Tutorial design examples will be covered and Matlab code will be provided.

Tuesday, June 3rd

Nonlinear Optimization: Techniques for Engineering
Organizer: R. Russell Rhinehart
Speaker: R. Russell Rhinehart, Chemical Engineering, Oklahoma State University

Overview:
This full-day workshop will be a practical guide for those using multivariable, constraint handling, nonlinear optimization. Although theoretical analysis behind techniques will be revealed, the takeaway will be participants’ ability to:

The workshop will cover common gradient-based (Newton, Levenberg-Marquardt, etc.), and single- and multi-player direct search optimization techniques (Hook-Jeeves, Particle Swarm, Leapfrogging, etc.) that represent the fundamental techniques of most approaches.

This session is based on a popular interdisciplinary graduate engineering course. Participants will receive course notes (approximately 200-pages) and software to provide exercises with access to code. Exercises and code can be implemented in any environment, but Excel/VBA will used as in-workshop examples and exercises. Participants are invited to bring a computer with Excel version 2010 or higher for in-class exploration of application examples to diverse engineering/economic situations.

The major challenges in optimization are often not 1) the mathematics of the algorithm, but the clear and complete statement of the 2) objective function, 3) constraints, 4) decision variables, 5) models, 6) convergence criterion, and 7) initialization. This short-course addresses all seven of the elements.

Subspace Identification of Linear, Parameter Varying, and Nonlinear Systems: Theory, Computation, and Applications
Organizer: Wallace E. Larimore
Speaker: Wallace E. Larimore; Adaptics, Inc, Email: [email protected]

Overview:
In this workshop, the powerful subspace identification method (SIM) is described for the well understood case of linear time-invariant (LTI) systems. Recent extensions are then developed to linear parameter-varying (LPV), Quasi-LPV, and general nonlinear (NL) systems such as polynomial systems. The presentation, following the extended tutorial paper (Larimore, ACC2013), includes detailed conceptual development of the theory and computational methods with references to the research literature for those interested. Numerous applications including aircraft wing flutter (LPV), chemical process control (LTI), automotive engine (Quasi-LPV, NL) modeling, and the Lorenz attractor (NL) are discussed. An emphasis is placed on conceptual understanding of the subspace identification method to allow effective application to system modeling, control, and fault diagnosis.

Over the past decade, major advances have been made in system identification for the LTI cases of no feedback (Larimore, ACC1999) and unknown feedback (Larimore, DYCOPS2004; Chiuso, TAC2010). However, for LPV and NL systems limitations remain including, for subspace methods the required computation grows exponentially with the number of system inputs, outputs, and states, and for maximum likelihood methods iterative nonlinear parameter optimization may not convergence, leading often to infeasible computation.

The workshop presents a first principles statistical approach using the fundamental canonical variate analysis (CVA) method for subspace identification of linear time-invariant (LTI) systems, with detailed extensions to linear parameter-varying (LPV) and nonlinear systems. The LTI case includes basic concepts of reduced rank modeling of ill-conditioned data to obtain the most appropriate statistical model structure and order using optimal maximum likelihood methods. The fundamental statistical approach gives expressions of the multistep-ahead likelihood function for subspace identification of LTI systems. This leads to direct estimation of parameters using singular value decomposition type methods that avoid iterative nonlinear parameter optimization. The parameter estimates have optimal Cramer-Rao lower bound accuracy, and the likelihood ratio hypothesis tests on model structure, model change, and process faults produce optimal decisions. Comparisons are made between system identification methods including subspace, prediction error, and maximum likelihood, and show considerably less computation and higher accuracy.

The LTI subspace methods are extended to Strict-LPV systems that are in the LTI form where the constant LTI parameters are multiplied by parameter-varying scheduling functions depending on exogenous system operating point variables. For example, this allows for the identification of constant underlying structural stiffness parameters while wing flutter dynamics vary with scheduling functions of speed and altitude operating point variables. The developed subspace identification method for Strict-LPV systems avoids the exponential growth in computations characteristic of previous SIM methods. This is further extended to Quasi-LPV systems where the scheduling functions may be functions of the inputs and/or outputs of the system. Quasi-LPV systems include bilinear and general polynomial systems that are universal approximators. Applications are discussed to monitoring and fault detection in closed-loop chemical processes, identification of vibrating structures under feedback, adaptive control of aircraft wing flutter, identification of the chaotic Lorenz attractor, and identification and monitoring of Quasi-LPV automotive engines.

Additional information at: www.adaptics.com/workshops/ACC2014

Open Problems in Multi-Agent Systems
Organizers: Yasamin Mostofi, Magnus Egerstedt
Speakers: Francesco Bullo (UCSB), Vijay Kumar (UPenn), Mehran Mesbahi (UW), Jeff Shamma (Georgia Tech), Magnus Egerstedt (Georgia Tech), Yasamin Mostofi (UCSB)

Overview:
Over the past two decades, we have witnessed an unprecedented growth in sensing, communications, computation, and robotic actuation, which can drastically change the way our society collects and processes information. This has consequently resulted in several exciting work in the area of multi-agent autonomous systems.

However, we are still quite far from fully understanding how to design a multi-agent system such that all the issues of sensing, communication, navigation, and resource/system constraints are addressed in a general framework that is as independent of a specific scenario as possible. Furthermore, due to the multi-disciplinary nature of these systems, research has also been conducted in several different communities in parallel.

As such, after several years of extensive work in this area, it is the right time to pause and ask about the important problems that are still open and need to be solved to fundamentally move the field forward. This is the main goal of the workshop. By bringing together experts that have extensively worked in different aspects of multi-agent systems, we hope to achieve a clear understanding of the road ahead in realizing the full vision of multi-agent systems. Thus, the purpose of the workshop is not just to present a collection of recent results, but rather to explicitly highlight what we still, as a community, do not know.

The slides of the talks and a summary of the discussions/conclusions will be made available to the attendees.

Additional information at: www.ece.ucsb.edu/~ymostofi/ACC14Workshop_OpenProblems.html

Emerging Frontiers in Adaptive Systems and Learning
Organizers: Tansel Yucelen, Bozenna Pasik-Duncan, Anuradha Annaswamy, Naira Hovakimyan, Susan Frost, Margareta Stefanovic
Speakers: Tansel Yucelen, Missouri University of Science and Technology ( [email protected] ); Bozenna Pasik-Duncan, University of Kansas ([email protected]); Travis Gibson, Harvard Medical School; Naira Hovakimyan, University of Illinois at Urbana-Champaign ([email protected]); Susan Frost, National Aeronautics and Space Administration ([email protected]); Margareta Stefanovic, University of Wyoming ([email protected])

Overview:
This workshop will provide a detailed review of a number of well-established and emerging methods in adaptive systems and learning and discuss the future directions of this field. Starting with an overview of nonlinear stability theory, adaptive systems, and learning, this workshop will build a strong foundation of adaptive control techniques and the tools used in their stability and robustness analysis. Specifically, authors will cover state-of-the-art methods including frequency-limited adaptive control, open- and closed-loop reference model design for safe and robust learning, L1 adaptive control, stability margins of adaptive systems, verification and validation of adaptive systems, and unfalsified switching adaptive control with applications to networked control systems, multi-agent networks, large-scale modular systems, wind turbines, and stochastic systems. The workshop will then continue with a discussion panel to create a venue for opening a pathway to merging ideas to allow for a unified viewpoint on the future directions of adaptive systems and learning field.

Additional information at: http://asrl.us/page3/page13/index.html

New Advances in Uncertainty Analysis and Estimation
Organizers: Puneet Singla, Raktim Bhattacharya
Speakers: Puneet Singla (SUNY Buffalo), Raktim Bhattacharya (Texas A&M University)

Overview:
Both sensor observation data and mathematical models are used to assist in the understanding of physical dynamic systems. However, observational data is often limited in terms of the kind and frequency of observations that can be taken and may only provide access to limited aspects of the system states. Also, any mathematical model used to represent the system dynamics is a reflection of numerous assumptions and simplifications to permit determination of a tractable model. These factors cause overall accuracy to degrade as the model states evolve. The fusion of observational data with state models promises to provide greater understanding of physical phenomenon than either approach alone can achieve. The most critical challenge here is to provide a quantitative assessment of how closely our estimates reflect reality in the presence of model uncertainty, discretization errors as well as measurement errors and uncertainty. The quantitative understanding of uncertainty is essential when predictions are to be used to inform policy making or mitigation solutions where significant resources are at stake.

This workshop will focus on recent development of mathematical and algorithmic fundamentals for uncertainty propagation, forecasting, and model-data fusion for nonlinear systems. The emphasis of this workshop will be on an intuitive understanding of the stochastic processes and practical applications of theory of stochastic processes in estimation and control area. The objectives are to develop a fundamental understanding of stochastic processes and its applications in the area of filtering and control of dynamical systems, to develop an appreciation for the strengths and limitations of state-of-the-art numerical techniques for uncertainty propagation and nonlinear filtering, to reinforce knowledge in stochastic systems with particular emphasis on nonlinear and dynamic problems, and to learn to utilize stochastic system analysis methods as research tools. After the completion of this workshop, audience should be able to apply the discussed methods to real engineering problems with the awareness of potential difficulties that might arise in practice.

Additional information at: PDF File

40 Years of Robust Control: 1978 to 2018
Organizers: Gary J. Balas, John C. Doyle, Keith Glover, Andrew K. Packard, Peter Seiler, Roy S. Smith
Speakers: Gary Balas (University of Minnesota), John Doyle (Caltech), Pascal Gahinet (The MathWorks), Keith Glover (Cambridge), Andy Packard (UC Berkeley), Pete Seiler (University of Minnesota), Roy Smith (ETHZ)

Overview:
This full-day workshop is mostly of a tutorial nature. The basic paradigm for robust control was formulated in the late 70’s and early 80’s, starting with interesting examples illustrating non-intuitive robustness properties of multi-loop systems. Over a 10-year period, research flourished, understanding these issues, developing rigorous analysis techniques based on efficient computations, and devising approximate methods for controller synthesis. These tools are used ubiquitously throughout various industries. Active research continues to this day, with generalizations along several diverse directions, including distributed and decentralized systems, nonlinear systems and novel applications. The purpose of this 1-day workshop is to present a concise, tutorial summary of the initial research phase, and present the results of more recent research activity. Participants are encouraged to bring laptops and work through the tutorial exercises during the workshop. One-day licenses of Matlab will be available for installation.

Target Audience:
Graduate students without a formal education in robust control, practitioners in multivariable control analysis and design; control researchers with different specializations wishing to get a quick overview of the field, both in terms of pragmatic tools as well as current research. Slides and all code to execute the tutorial examples will be provided

Morning:
SISO Loopshaping; Classic MIMO/multiloop counterexamples; MIMO system theory; Glover-McFarlane Loopshaping; Structured Singular Value; Signal-based, norm-optimal Control Synthesis; Model Reduction; Analysis & Design Examples

Afternoon:
Synthesis reformulations using Linear Matrix Inequalities; Integral Quadratic Constraints; Youla Parametrization; Decentralized and structured feedback; Networks; Bio/Neuro/Medical; Cyber-security; MPC/RHC; Nonlinear systems and sum-of-squares optimization; Adaptive Control

High Level Modeling for Control Systems Development
Organizers: Kenneth R. Butts, Karl Hedrick, Kyle Edelberg
Speakers: J. Karl Hedrick, Kyle Edelberg, Andreas Hansen (University of California – Berkeley), Jürgen Gerhard, (Maplesoft), Hisahiro Ito, Ken Butts (Toyota Technical Center) ([email protected])

Overview:
Model-based design (MBD) is used in the automotive industry to develop ever more sophisticated control systems and, consequently, the use of dynamical plant models to guide hardware, control, and software design, as well as validation and verification, is prevalent.

To formally address plant modeling, we have developed the High Level Modeling (HLM) framework wherein a physics-based plant-model-development process is defined. By following conservation principles, a model design of the system can be created which we call the High Level Model Description (HLMD). With the HLMD, design teams can readily review and critique the design of the model. In addition, HLMD-based models are easier to reuse and/or modify than traditional equation-only models due to the clear exposition of design intent.

In this half-day workshop, we will a) introduce HLM and shows its role in a plant modeling for control workflow, b) demonstrate the High Level Modeling Tool (HLMT), c) present the HLMD and control of an automotive engine cold-start system, d) describe an associated computer algebra-based model simplification and control design environment, and e) close with a discussion of open issues and development direction.

Developing Battery Management Systems Using Model-Based Design
Organizers: Simona Onori, Federico Baronti
Speakers: Simona Onori (Clemson University), Federico Baronti (University of Pisa), Mo-Yuen Chow (North Carolina State University), Robyn Jackey (MathWorks), Kevin Rzemien (MathWorks)

Note:This workshop is sponsored by MathWorks so all participants may register at the Student/Retiree rate.

Overview:
In this workshop, we will provide an overview of the current state of the art, technical and technological challenges, and future research directions for battery management system (BMS) design in electrified vehicles.

Specifically, the workshop will provide a technology overview, including the latest techniques in battery systems modeling, control, and diagnosis, along with current trends in modeling energy storage systems for automotive applications. We will then introduce methods for battery models using experimental data with emphasis on parameter identification techniques for both battery cell and battery pack modeling design. Next, we discuss state of charge and state of health estimation methods, including analysis and comparison of different model-based approaches using field application data.

The development of safe management systems is critical for the Li-ion battery industry. In the second part of the workshop, model-based design techniques will be used to design, implement, and validate algorithms that ensure the safety of a Li-ion battery pack by monitoring each individual cell for overvoltage or undervoltage conditions. Next, the discussion will move to charge equalization to discuss open issues and compare different solutions. Finally, some BMS implementation examples will be presented.

Target Audience:
The target audience of the proposed workshop includes graduate students, researchers and professionals engineers interested in gaining an in-depth understanding of modeling, identification and estimation methods for advanced battery management system design.

This workshop will be beneficial for system engineers (in both academia and industry) working on, or interested in, model-based design for BMS applications in electrified vehicles.

Additional information at: www.iet.unipi.it/f.baronti/acc14/

Ubiquitous Hands-On Learning: The Future of Engineering Education
Organizers: Bonnie Ferri, Al Ferri
Speakers: Bonnie Heck Ferri, Aldo Ferri (Georgia Tech), Deborah Walter (Rose-Hulman)

Note:This workshop is sponsored by the National Science Foundation so all participants will be reimbursed up to $100 of the registration fee. The attendance is limited to 40 people.

Organized by: the Center for Mobile Hands-On STEM

Endorsed by: the IEEE Control Systems Society Technical Committee on Education

Overview:
Studies have demonstrated that concrete experimentation improves student understanding of abstract concepts and motivates students by providing examples of theory in practice. Development of inexpensive and portable USB-powered oscilloscopes, function generators, microcontroller boards, and other portable electronic equipment has facilitated a new model of engineering education where hands-on experiences can be done ubiquitously anytime anywhere. Students can explore the theoretical concepts introduced in lectures with hands-on activities either immediately in the classroom or at home rather than waiting for a scheduled laboratory time.

Why should you come? Learn different models for the effective implementation of hands-on learning: 1) hands-on experiences in traditional lecture-based courses; 2) lab courses where students own their own equipment and do the labs at home; 3) studio classes; 4) flipped classes; and 5) online lab courses. Participants will use a selection of low-cost electronic boards and portable instruments, which include the National Instruments’ myDAQ, Digilent’s Analog Discovery board, and ARM’s mbed microcontroller platform to carry out a number of experiments during the workshop. The experiments will demonstrate the range of hands-on activities and some of the diverse theoretical concepts that can be taught via active hands-on learning in systems and controls, circuits, and system dynamics courses. Participants will leave the workshop with a set of tested experimental procedures and other instructional resources.

Additional information at: PDF File

The Beauty of Controls
Organizers: Bozenna Pasik-Duncan, Ljubo Vlacic
Co-Organizers: Daniel Abramovitch, Linda Bushnell, Dominique Duncan, Lucy Pao, Molly Shor

Organizing and Program Committee: Members of the AACC Technical Committee on Education and the IEEE CSS Technical Committee on Control Education.

Sponsored by: American Automatic Control Council (AACC), IEEE Control Systems Society (CSS), ACC 2014, and the University of Kansas.

Purpose:
This outreach event is designed to increase the general awareness of the importance of systems and control technology and its cross-disciplinary nature among middle and high school students and teachers. Control is used in many common devices and systems: cell phones, computer hard drives, automobiles, and aircraft, but is usually hidden from view. The control field spans science, technology, engineering and mathematics (STEM). The success of all STEM disciplines depends on attracting the most gifted young people to science and engineering profession. Early exposure to middle and high school students and their teachers is a key factor. The goal of these outreach efforts is to promote an increased awareness of the importance and cross-disciplinary nature of control and systems technology.

The workshop activities include presentations by control systems experts from our technical community, informal discussions, and the opportunity for teachers and students to meet passionate researchers and educators from academia and industry. The talks are designed to be educational, inspirational and entertaining showing the excitement of controls.

Lunch and will be provided and participants will receive certificates.

Additional information at: http://www.math.ku.edu/ksacg/workshops/ACC_2014/acc2014workshop.html

2014 workshop photos at: http://www.math.ku.edu/ksacg/workshops/ACC_2014/acc2014workshop_photos.html

Past workshop photos at: http://www.math.ku.edu/ksacg/photos/workshops.html