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Robust control of systems with sector nonlinearities via convex optimization: A data-driven approach
Related publications (102)
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This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...
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A novel approach for linear parameter-varying (LPV) controller synthesis for adaptive rejection of time-varying sinusoidal disturbances is proposed. Only the frequency response data of a linear time-invariant (LTI) multiple-input multiple-output (MIMO) sys ...
2024Non-parametric IQC Multipliers in Data-Driven Robust Controller Synthesis
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The paper presents a robust data-driven controller synthesis method for generalised multi-input multioutput (MIMO) systems. Using the frequency response of a linear time-invariant (LTI) MIMO system and characterising perturbations through Integral Quadrati ...
2024Data-Driven Control and Optimization under Noisy and Uncertain Conditions
Control systems operating in real-world environments often face disturbances arising from measurement noise and model mismatch. These factors can significantly impact the perfor- mance and safety of the system. In this thesis, we aim to leverage data to de ...
EPFL2023Data-driven Methods for Control: from Linear to Lifting
The progress towards intelligent systems and digitalization relies heavily on the use of automation technology. However, the growing diversity of control objects presents significant challenges for traditional control approaches, as they are highly depende ...
EPFL2023Safe Zeroth-Order Convex Optimization Using Quadratic Local Approximations
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We address black-box convex optimization problems, where the objective and constraint functions are not explicitly known but can be sampled within the feasible set. The challenge is thus to generate a sequence of feasible points converging towards an optim ...
2023Neural System Level Synthesis: Learning over All Stabilizing Policies for Nonlinear Systems
Giancarlo Ferrari Trecate, Luca Furieri, Clara Lucía Galimberti
We address the problem of designing stabilizing control policies for nonlinear systems in discrete-time, while minimizing an arbitrary cost function. When the system is linear and the cost is convex, the System Level Synthesis (SLS) approach offers an effe ...
IEEE2022Stabilization and Accuracy Improvement of Power-Hardware-in-the-Loop Test Using a Robust Data-Driven Method
Alireza Karimi, Seyed Sohail Madani
Power-Hardware-In-the-Loop (PHIL) setups have gained high importance in validation of the performance of newly developed algorithms and devices with low risk and implementation cost. However, the interconnection of a power hardware with a simulated model v ...
2021Sample Complexity of Linear Quadratic Gaussian (LQG) Control for Output Feedback Systems
Maryam Kamgarpour, Luca Furieri, Na Li
This paper studies a class of partially observed Linear Quadratic Gaussian (LQG) problems with unknown dynamics. We establish an end-to-end sample complexity bound on learning a robust LQG controller for open-loop stable plants. This is achieved using a ro ...
PMLR2021On the Equivalence of Youla, System-Level, and Input-Output Parameterizations
Maryam Kamgarpour, Luca Furieri, Yu Zheng
A convex parameterization of internally stabilizing controllers is fundamental for many controller synthesis procedures. The celebrated Youla parameterization relies on a doubly coprime factorization of the system, while the recent system-level and input-o ...
2021