I teach a number of courses within the Faculty of Aerospace Engineering. The flagship courses I offer are:
In addition, I have also taught Control Theory (084738), Dynamic Systems (084737), Undergraduate Seminar in Controls (085802), and Control of Multi-Input Multi-Output Systems (086289).
Networked Dynamic Systems (086730)
Multi-agent systems, or networked dynamic systems (NDS), are systems composed of dynamic units that interact with each other over an information exchange network. These systems can be used to perform team objectives with applications ranging from formation flying to distributed computation. Challenges associated with these systems are their analysis and synthesis, arising due to their decoupled, distributed, large-scale nature, and due to limited inter-agent sensing and communication capabilities. This course provides an introduction to these systems via tools from graph theory, dynamic systems theory, and optimization. The course will cover a variety of modeling techniques for different types of networked systems and proceed to show how their properties, such as stability and performance, can be analyzed. The course will also explore techniques for designing these systems, including distributed control strategies, and optimization methods for network design. The course will also cover real-world applications by presenting recent results obtained in the distributed formation control of multi-robot systems.
We encourage student participation from multiple faculties/departments at the Technion.
- The course syllabus and more information can be found here.
- Let me know (by email) if you do not have a Technion email.
Robust Control (088792)
Classical “model-based control” techniques for the analysis and design of control systems are based on an implicit assumption that the available mathematical model describing the system process is accurate. In practice, however, mathematical models are inherently uncertain - these uncertainties can range from the numerical values of parameters in a system to uncertainties in the system dynamics itself. The central goal of this course, therefore, is to present a general framework for analyzing uncertain systems and designing controllers that are robust to these uncertainties.
This course, in a broad sense, covers analysis and design techniques for the control of uncertain sys- tems. Along the way, we exploit results from linear operator theory and semi-definite programming to analyze, formulate, and solve a variety of multi-variable control problems. The analysis includes the formulation and verification of stability and performance criteria in the form of function norms that allow the representation of structured and unstructured model uncertainties.
We encourage student participation from multiple faculties/departments at the Technion.
- The course syllabus and more information can be found here.
- Let me know (by email) if you do not have a Technion email.
Control Lab (085705)
This laboratory course focuses on the control and estimation of a quadcopter drone. The lab builds on materials covered in dynamic systems (084737) and control theory (084738) with the ultimate goal of designing from the ground up a complete control system for the autonomous flight of a quadcopter drone. Modeling of a quadcopter is performed using basic principles. The capabilities and limitations of the quadcopter sensors and actuators are explored, and tools related to sensor fusion and state estimation are introduced to enable good control design. The complete control problem for the quadcopter is broken down into simple single-input single-output control loops, and students close each loop individually. All control laws and estimators are tested in simulation and also with physical experiments using a quadcopter and a specially designed testing rig. The culmination of the course is the autonomous free flight of the quadcopter.
