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About us Practical matters How to find us C. (Claudio) De Persis, Prof

Research interests

My field is Automatic Control and its applications.
I work on the automatic design of controllers from data by integrating control theory and data science and proposing methods that reduce control design to the solution of data-dependent convex programs. 
Previously, I worked on networked and cyber-physical control systems, with applications to energy systems, for which distributed controllers were designed relying on a unifying passivity property that holds for electrical grids, district heating networks and data centres. I hold two patents for inventions related to these topics. 
In the context of cyber-physical control systems I studied the effect of information quantisation and asynchronous information transmission including their resilience to denial-of-service (DoS) attacks, for which we proposed a now widely accepted model.  
For my doctoral dissertation, I worked on the problem of detecting faults in nonlinear dynamical systems, solving the so-called Fundamental Problem of Residual Generation for nonlinear systems, based on the newly introduced differential-geometric concept of observability codistributions.


Controller Synthesis for Input-State Data With Measurement Errors

Data-based Transfer Stabilization in Linear Systems

Data-Driven Control of Nonlinear Systems from Input-Output Data

Data-driven design of safe control for polynomial systems

Data-Driven Feedback Linearization with Complete Dictionaries

Data-Driven Stabilization of Nonlinear Systems via Taylor’s Expansion

Data Driven System Identification of Water Distribution Systems via Kernel-Based Interpolation

Learning Controllers from Data Via Kernel-Based Interpolation

Learning Control of Second-Order Systems via Nonlinearity Cancellation

Controller design for robust invariance from noisy data

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