A Data-Driven Method for Computing Fixed-Structure Low-Order Controllers With H∞ Performance
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This work presents a method to obtain inner and outer approximations of the region of attraction of a given target set as well as an admissible controller generating the inner approximation. The method is applicable to constrained polynomial dynamical syst ...
A new method for robust fixed-order H∞ controller design for uncertain time-delayed MIMO systems is presented. It is shown that the H∞ robust performance condition can be represented by a set of convex constraints with respect to the parameters of a linear ...
Energy efficiency is a major design issue in the context of Wireless Sensor Networks (WSN). If the acquired data is to be sent to a far-away base station, collaborative beamforming performed by the sensors may help to distribute the communication load amon ...
We present a framework based on convex optimization and spectral regularization to perform learning when feature observations are multidimensional arrays (tensors). We give a mathematical characterization of spectral penalties for tensors and analyze a uni ...
We address the long-standing problem of computing the region of attraction (ROA) of a target set (typically a neighborhood of an equilibrium point) of a controlled nonlinear system with polynomial dynamics and semialgebraic state and input constraints. We ...
Institute of Electrical and Electronics Engineers2014
A new method for H-infinity gain-scheduled controller design by convex optimization is proposed that uses only frequency-domain data. The method is based on loop shaping in the Nyquist diagram with constraints on the weighted infinity norm of closed-loop t ...
In recent works, compressed sensing (CS) and convex opti- mization techniques have been applied to radio-interferometric imaging showing the potential to outperform state-of-the-art imaging algorithms in the field. We review our latest contributions [1, 2, ...
A new method for H-infinity gain-scheduled controller design by convex optimization is proposed that uses only frequency-domain data. The method is based on loop shaping in the Nyquist diagram with constraints on the weighted infinity-norm of closed-loop t ...
In a recent article series, the authors have promoted convex optimization algorithms for radio-interferometric imaging in the framework of compressed sensing, which leverages sparsity regularization priors for the associated inverse problem and defines a m ...
The steady advance of computational methods makes model-based optimization an increasingly attractive method for process improvement. Unfortunately, the available models are often inaccurate. An iterative optimization method called "modifier adaptation" ov ...