Publishing June 2025

This book presents a solution to a problem in adaptive control design that had been open for 40 years: robustification to disturbances without compromising asymptotic performance. This original methodology builds on foundational ideas, such as the use of a deadzone in the update law and nonlinear damping in the controller and advances the tools for and the theory behind designing robust adaptive controllers, thus guaranteeing robustness properties stronger than previously achieved. The authors present all stability notions, old and new, that are useful in adaptive control, provide numerous examples, and contrast their analysis to landmark approaches to robustification of adaptive controllers in prior literature.

This book

• develops the Deadzone-Adapted Disturbance Suppression (DADS) control, a novel adaptive control methodology, and constructs a novel robust identifier that can work in parallel with every direct adaptive controller (not only DADS);

• illustrates the DADS design with the wing rock instability application; and

• provides ideas for the extension of the control scheme to cases not studied in the book.

Publishing September 2025

This book compiles key findings on the modeling, analysis, estimation, and control design of various tubular reactor configurations. It explores both linear and nonlinear hyperbolic and parabolic partial differential equations, bridging the gap between theory and applications in distributed parameter systems.

The tubular reactor offers several important advantages when teaching and studying distributed parameter systems:

• It covers multiple partial differential equations classes.

• It bridges finite- and infinite-dimensional models.

• It demonstrates diverse behaviors.

• It links theory to practice.

• It has a broad scope of application in biological, environmental, and chemical systems.

Publishing November 2024

This book provides the mathematical foundations needed for designing practical controllers for linear time-invariant systems. The authors accomplish this by incorporating intentional time delays into measurements with the goal of achieving anticipation capabilities, reduction in noise sensitivity, and a fast response. The benefits of these types of delay-based controllers have long been recognized, but designing them based on an analytical approach become possible only recently.

Design of Delay-Based controllers for Linear Time-Invariant Systems provides a thorough survey of the field and the details of the analytical approaches needed to design delay-based controllers. In addition, readers will find

• accessible mathematical tools and self-contained proofs for rigorous analysis

• numerous examples and comprehensive computational algorithms to motivate the results

• experiments on single-input single-output systems and multi-agent systems using real-world control applications to illustrate the benefits of intentionally inducing delays in control loops

This book introduces transfinite interpolation as a generalization of interpolation of data prescribed at a finite number of points to data prescribed on a geometrically structured set such as a piece of curve, surface, or submanifold. The time-invariant theory is readily extended to a moving/deforming data set whose dynamics is specified in a Eulerian or Lagrangian framework. The resulting innovative tools cover a very broad spectrum of applications in fluid mechanics, geometric optimization, and imaging. The authors chose to focus on the dynamical mesh updating in fluid mechanics and the construction of velocity fields from the boundary expression of the shape derivative.

Transfinite Interpolations and Eulerian/Lagrangian Dynamics

• is a self-contained graduate-level text that integrates theory, applications, numerical approximations, and computational techniques; and

• applies transfinite interpolation methods to finite element mesh adaptation and ALE fluid-structure interaction.

This self-contained book presents in a unified, systematic way the basic principles of optimal control governed by ODEs. Using a variational perspective, the author incorporates important restrictions like constraints for control and state, as well as the state system itself, into the equivalent variational reformulation of the problem. The fundamental issues of existence of optimal solutions, optimality conditions, and numerical approximation are then examined from this variational viewpoint.

Readers will find

• a unified approach to all the basic issues of optimal control,

• academic and real-world examples testing the book's variational approach, and

• a rigorous treatment stressing ideas and arguments rather than the underlying mathematical formalism.

Extremum Seeking through Delays and PDEs, the first book on the topic, expands the scope of applicability of the extremum seeking method, from static and finite-dimensional systems to infinite-dimensional systems. In this book,

• numerous algorithms for model-free real-time optimization are developed and their convergence guaranteed,

• extensions from single-player optimization to noncooperative games, under delays and PDEs, are provided,

• the delays and PDEs are compensated in the control designs using the PDE backstepping approach, and stability is ensured using infinite-dimensional versions of averaging theory, and

• accessible and powerful tools are provided for analysis.

This book introduces optimal control methods, formulated as optimization problems, applied to business dynamics problems. Business dynamics refers to a combination of business management and financial objectives embedded in a dynamical system model. The model is subject to a control that optimizes a performance index and takes both management and financial aspects into account.

Business Dynamics Models: Optimization-Based One Step Ahead Optimal control includes

• solutions that provide a rationale for the use of optimal control and guidelines for further investigation into more complex models;

• formulations that can also be used in a so-called flight simulator mode to investigate different complex scenarios; and

• a modern programming environment (Jupyter notebooks in JuMP/Julia) for modeling, simulation, and optimization. Julia code and notebooks are provided on a website for readers to experiment with their own examples.