A Data-driven Approach to Robust Control of Multivariable Systems by Convex Optimization

The frequency-domain data of a multivariable system in different operating points is used to design a robust controller with respect to the measurement noise and multimodel uncertainty. The controller is fully parametrized in terms of matrix polynomial functions and can be formulated as a centralized, decentralized or distributed controller. All standard performance specifications like $H_2$, $H_\infty$ and loop shaping are considered in a unified framework for continuous- and discrete-time systems. The control problem is formulated as a convex-concave optimization problem and then convexified by linearization of the concave part around an initial controller. The performance criterion converges monotonically to a local optimal solution in an iterative algorithm. The effectiveness of the method is compared with fixed-structure controllers using non-smooth optimization and with full-order optimal controllers via simulation examples. Finally, the experimental data of a gyroscope is used to design a data-driven controller that is successfully applied on the real system

A shifting pole placement approach for the design of performance-varying multivariable PID controllers via BMIs

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/In this paper, the design of a performance-varying multivariable Proportional-Integral-Derivative (PID) controllers is presented. The main objective is to provide a framework for changing online the closed-loop behavior of the controlled system using the shifting pole placement approach. In order to carry out this target, the PID design problem is transformed into a static output feedback design problem which is analyzed through the linear parameter-varying (LPV) paradigm. An academic example is used to demonstrate the effectiveness of the proposed approach.Peer ReviewedPostprint (author's final draft

On the Robust Control of DC-DC Converters: Application to a Hybrid Power Generation System

International audienceIn this paper a complete robust control synthesis is performed for a hybrid power generation structure composed by a Fuel Cell and a Supercapacitor. The control strategies are applied to the DC-DC boost power converters associated to each power source. Multivariable PI control with H∞ performance, H∞ full and reduced order controllers are designed and compared. The multivariable PI controller is designed through an optimization procedure based on solving some Linear Matrix Inequalities. A μ-analysis and frequency/time response performances results shows the advantages of the different proposed control strategies

Structured Control of LPV Systems with Application to Wind Turbines

Abstract — This paper deals with structured control of linear parameter varying systems (LPV) with application to wind turbines. Instead of attempting to reduce the problem to linear matrix inequalities (LMI), we propose to design the controllers via an LMI-based iterative algorithm. The proposed algorithm can synthesize structured controllers like decentralized, static output and reduced order output feedback for discrete-time LPV systems. Based on a coordinate decent, it relies on a sufficient matrix inequality condition extended with slack variables to an upper bound on the induced L2-norm of the closed-loop system. Algorithms for the computation of feasible as well as optimal controllers are presented. The general case where no restrictions are imposed on the parameter dependence is treated here due to its suitability for modeling wind turbines. A comprehensive numerical example of a gain-scheduled LPV controller design with prescribed pattern for wind turbines illustrate the utilization of the proposed algorithm. I