Publications de Alireza Karimi

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Fixed-order controller design for LTI-SISO polytopic systems is investigated using rank deficiency constraint on the controller Sylvester resultant matrix. It is shown that the non-convexity of fixed-order controller design problem can be gathered in a ran ...

A novel approach for robust controller synthesis, which models uncertainty as an elliptical set, is proposed in the paper. Given a set of frequency response functions of linear time-invariant (LTI) multiple-input multiple-output (MIMO) systems, the approac ...

Friction modeling of a high-precision positioning system using linear permanent magnet synchronous motors is investigated. The friction force is measured precisely by some specific experiments to eliminate the parasitic ripple force. The experimental data ...

A new approach for robust fixed-order H-infinity controller design by convex optimization is proposed. Linear time-invariant single-input single-output systems represented by nonparametric models in the frequency domain are considered. It is shown that the ...

The frequency response data of a generalized system is used to design fixed-structure controllers for the H2 and H∞ synthesis problem. The minimization of the two and infinity norm of the transfer function between the exogenous inputs and performance outpu ...

An iterative data-driven correlation-based method has been proposed recently to tune multivariable linear time-invariant controllers in closed-loop operation. In this contribution, the preferred way of exciting a 2 × 2 system is investigated via the accura ...

This paper deals with the modeling and control of a magnetically levitated planar motor. The actuator considered has moving coils and stationary magnets. The principal objective is to develop a model which can be implemented in simulation. Therefore, the d ...

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 ...

In this paper, a new method for designing robust fixed-order

\mathcal{H}_{\infty}

discrete-time controllers is presented. The controller structure is a two-degree of freedom polynomial controller of the

RST

type. A data-driven approach is implemented f ...

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 ...

This paper deals with direct data-driven design of model-reference controllers whose number of parameters is constrained. Input-output (I/O) sparse controllers are introduced and proposed as an alternative to low-order controller tuning. The optimal I/O sp ...

In this paper, a direct data-driven approach is proposed to tune fixed-order controllers for unknown stable LTI plants in a mixed-sensitivity loop-shaping problem. The method requires a single set of input-output samples and it is based on simple convex op ...

In this paper a new method for fixed-order output-feedback Linear Parameter Varying (LPV) controller design is presented. First, a set of stabilizing LPV controllers is given as an inner convex approximation of the non-convex set of all stabilizing LPV con ...

In this paper stochastic approximation theory is used to produce Iterative Learning Control algorithms which are less sensitive to stochastic disturbances, a typical problem for the learning process of standard ILC algorithms. Two algorithms are developed, ...

In non-iterative data-driven controller tuning, a set of measured input/output data of the plant is used directly to identify the optimal controller that minimizes some control criterion. This approach allows the design of fixed-order controllers, but lead ...

A linear programming approach is proposed to tune fixed-order linearly parameterized controllers for stable LTI plants. The method is based on the shaping of the open-loop transfer function in the Nyquist diagram. A lower bound on the crossover frequency a ...

In recent years, direct data-driven controller tuning methods have been proposed as an alternative to the standard model-based approach for model-reference control design. In this work, the problem of input design for noniterative direct data-driven techni ...

The estimation of a system’s infinity norm using one set of measured input and output data is investigated. It is known that, if the data set is noise free, this problem can be solved using convex optimization. In the presence of noise, convergence of this ...

In this work, we propose a novel data-driven representation for general linear time-invariant (LTI) systems based on behavioral system theory. This representation relies solely on input-output data, eliminating the need for exact knowledge of the system st ...

A new approach is presented to obtain a convex set of robust D—stabilizing fixed structure controllers, relying on Cauchy's argument principle. A convex set of D—stabilizing controllers around an initial D—stabilizing controller for a multi-model set is re ...

Alireza Karimi

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Fixed-Order Controller Design for Polytopic Systems Using Rank Deficiency in a Sylvester Matrix

Data-driven IQC-Based Robust Control Design for Hybrid Micro-disturbance Isolation Platform

Friction Modeling of a High-Precision Positioning System

Fixed-order H-infinity Controller Design for Nonparametric Models by Convex Optimization

Data-driven fixed-structure frequency-based H2 and H∞ controller design

On the Input Design for Data-Driven Correlation-Based Tuning of Multivariable Controllers

Modeling and Control of a Magnetically Levitated Planar Motor

H∞ smith predictor design for time-delayed MIMO systems via convex optimization

A Data-Driven Approach in Designing RST Controllers with H∞ Performance via Convex Optimization

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Direct data-driven design of sparse controllers

Direct data-driven H2 − H∞ loop-shaping

Fixed-order LPV Controller Design for LPV Systems by Convex Optimization

Iterative Learning Control based on Stochastic Approximation

On identification methods for direct data-driven controller tuning

Robust PID Controller Design by Linear Programming

Optimal input design for direct data-driven tuning of model-reference controllers

Data-Driven Estimation of the Infinity Norm of a Dynamical System

Data-Driven Output Feedback Control Based on Behavioral Approach

A convex set of robust D—stabilizing controllers using Cauchy's argument principle