May 14, 2026
Date: Tuesday May 19
Time: 2:30PM – 3.30PM 
Zoom:
Event-Triggered Control using New Trigger Rules
Abstract: Control systems are widely used in engineering to model forces that can be applied to dynamical systems. The forces are usually modeled as feedback controls, which can be functions of the available measurements from the systems. Then the feedback control problem consists of finding formulas for feedback controls that ensure prescribed qualitative behaviors for the dynamical systems, such as global asymptotic convergence towards an equilibrium point. Traditional feedback control methods call for continuously changing the feedback control values or changing their values at a sequence of times that are independent of the state of the control systems. This can lead to unnecessarily frequent changes in control values, which can be undesirable in engineering applications that have constrained communication resources. This motivated the development of event-triggered control, whose objective is to find formulas for feedback controls whose values are only changed when it is essential to change them in order to achieve a prescribed system behavior. This talk summarizes the speaker’s recent research on event-triggered control theory for systems of ODEs, which is collaborative with Frederic Mazenc, Anton Selivanov, and others [1,2]. Two key novel techniques are the use of matrices of absolute values in the trigger rules instead of the usual Euclidean norm [2], and a smoothed switching function approach that helps cancel the effects of unknown nonlinearities [1]. We illustrate how these techniques beneficially reduce the instances of changes in the control values, as compared with previous methods. The talk will be understandable to those familiar with the basic theory of ordinary differential equations. No prerequisite background in event-triggered control will be needed to understand and appreciate this talk.
Abstract: Control systems are widely used in engineering to model forces that can be applied to dynamical systems. The forces are usually modeled as feedback controls, which can be functions of the available measurements from the systems. Then the feedback control problem consists of finding formulas for feedback controls that ensure prescribed qualitative behaviors for the dynamical systems, such as global asymptotic convergence towards an equilibrium point. Traditional feedback control methods call for continuously changing the feedback control values or changing their values at a sequence of times that are independent of the state of the control systems. This can lead to unnecessarily frequent changes in control values, which can be undesirable in engineering applications that have constrained communication resources. This motivated the development of event-triggered control, whose objective is to find formulas for feedback controls whose values are only changed when it is essential to change them in order to achieve a prescribed system behavior. This talk summarizes the speaker’s recent research on event-triggered control theory for systems of ODEs, which is collaborative with Frederic Mazenc, Anton Selivanov, and others [1,2]. Two key novel techniques are the use of matrices of absolute values in the trigger rules instead of the usual Euclidean norm [2], and a smoothed switching function approach that helps cancel the effects of unknown nonlinearities [1]. We illustrate how these techniques beneficially reduce the instances of changes in the control values, as compared with previous methods. The talk will be understandable to those familiar with the basic theory of ordinary differential equations. No prerequisite background in event-triggered control will be needed to understand and appreciate this talk.
[1] Malisoff, M., and A. Selivanov, “Event-triggered sliding mode control using new triggering rules,” Automatica, Volume 188, June 2026, Article 112923.
https://doi.org/10.1016/j.
[2] Mazenc, F., and M. Malisoff, “Dynamic event-triggered control under input and state delays using interval observers,” IEEE Control Systems Letters, Volume 8, 2024, pp. 2565-2570.
https://doi.org/10.1109/LCSYS.
https://doi.org/10.1109/LCSYS.
Bio: Michael Malisoff earned his Ph.D. in Mathematics from Rutgers University in New Brunswick, NJ in 2000. He holds Roy P. Daniels Professorship #3 in the Department of Mathematics at Louisiana State University. His research is on control theory, with engineering applications. He was an associate editor for Automatica, IEEE Transactions on Automatic Control, and SIAM Journal on Control and Optimization, and is an associate editor for Discrete and Continuous Dynamical Systems Series B, European Journal of Control, and Mathematical Control and Related Fields.
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See you all on Tuesday!
Fabio Spada – PhD Student
Autonomous Controls Laboratory
Aeronautics & Astronautics
University of Washington