Data-Driven Controller Design

Bazanella, Alexandre Sanfelice; Campestrini, Lucíola; Eckhard, Diego

doi:10.1007/978-94-007-2300-9

Cited by 77 publications

(20 citation statements)

References 1 publication

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“…In most model-based robust control design methodologies, including each of these resonance modes in the actuator models directly increases the controller order [34]. However by using the data-driven control methodology, all these modes are already included in the system frequency response measurements and will be considered in the controller design step without any direct effect on the controller order [9].…”

Section: Design Resultsmentioning

confidence: 99%

“…In the data-driven control design, the measurements represent the real dynamics of the system. Therefore, if the number of measurements are adequate enough to represent uncertainties and modes of the system, the stability and performance level achieved in the design step are guaranteed to be achieved when implementing the controller on the real system [9]. Moreover, the data-driven control methodologies can be useful in designing a common controller for a set of plants produced in a production line [17].…”

Section: Introductionmentioning

confidence: 99%

“…A sufficient convex condition for the H ∞ norm of Multi Input-Multi Output (MIMO) systems was also developed in [19]. The data-driven H 2 control problem for SISO systems with pre-specified control structures such as Finite Impulse Response (FIR) filters was given in [9]. The data-driven H 2 control for MIMO systems with general control structures was developed in [19], where a sufficient convex condition for the upper-bound of the H 2 norm of closed loop transfer functions was derived.…”

Section: Introductionmentioning

confidence: 99%

“…Including each of these resonance modes in the actuator model directly increases the controller order [34]. However by using the data-driven control methodology, all these modes are already included in the system frequency response measurements and are considered in the controller design step without any direct effect on the controller order [9]. In the proposed methodology, the controller order is fixed and is a function of the control objectives rather than a direct function of the model complexity.…”

Section: Introductionmentioning

confidence: 99%

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Mixed H<inf>2</inf>/H<inf>∞</inf> Data-Driven Control Design for Hard Disk Drives

Bagherieh

Horowitz

2018

2018 Asia-Pacific Magnetic Recording Conference (APMRC)

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A frequency based data-driven control design considering mixed H2/H∞ control objectives is developed for multiple input-single output systems. The main advantage of the data-driven control over the model-based control is its ability to use the frequency response measurements of the controlled plant directly without the need to identify a model for the plant. In the proposed methodology, multiple sets of measurements can be considered in the design process to accommodate variations in the system dynamics. The controller is obtained by translating the mixed H2/H∞ control objectives into a convex optimization problem. The H∞ norm is used to shape closed loop transfer functions and guarantee closed loop stability, while the H2 norm is used to constrain and/or minimize the variance of signals in the time domain.The proposed data-driven design methodology is used to design a track following controller for a dual-stage HDD. The sensitivity decoupling structure[16] is considered as the controller structure. The compensators inside this controller structure are designed and compared by decoupling the system into two single input-single-output systems as well as solving for a single input-double output controller.Index Terms-Data-driven control design, Mixed H2/H∞ norms, Multiple input-single output systems, Hard disk drives, Trackfollowing controller, Sensitivity decoupling.

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Section: Design Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Mixed H<inf>2</inf>/H<inf>∞</inf> Data-Driven Control Design for Hard Disk Drives

Bagherieh

Horowitz

2018

2018 Asia-Pacific Magnetic Recording Conference (APMRC)

View full text Add to dashboard Cite

show abstract

“…In addition, the performance of the designed controller may or may not be robust because the concept of robustness is not included in the VRFT method. [ 3,4,7–12 ] The higher order controllers based on VRFT is designed with bandwidth and settling time based

M (z)

, that is,

^{‘} {z_{p}}^{’}

depends on design specification, where ‘ n ’ and ‘ d ’ of

M (z)

are chosen randomly selected, and the concept of robustness is not considered. [ 3,13 ] The proportional integral (PI)/proportional integral derivative (PID) controller is designed for multiple input multiple output (MIMO) systems using first‐order

M (z)

based on settling time in the literature [ 14–16 ] and second‐order

M (z)

.…”

Section: Introductionmentioning

confidence: 99%

Robust control of discrete minimum and non‐minimum phase systems via data‐driven virtual reference feedback tuning and IMC

et al. 2022

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In this paper, we develop a novel robust control approach for discrete minimum and non-minimum phase systems via a combined data-driven virtual reference feedback tuning (VRFT) and internal model control (IMC) scheme. The first step in the conventional VRFT method controller design is the selection of the closed-loop reference model (M z ð Þ), and M z ð Þ selection is still an open problem. The integration of the IMC scheme and the VRFT method provides

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A Measurement‐Based Approach for Designing Fixed‐Order Controllers for Unknown Closed‐Loop Architecture

Khadraoui

Nounou

et al. 2014

Asian Journal of Control

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This paper presents a new technique to design fixed‐structure controllers for linear unknown systems using a set of measurements. In model‐based approaches, the measured data are used to identify a model of the plant for which a suitable controller can be designed. Due to the fact that real processes cannot be described perfectly by mathematical models, designing controllers using such models to guarantee some desired closed‐loop performance is a challenging task. Hence, a possible alternative to model‐based methods is to directly utilize the measured data in the design process. We propose an approach to designing structured controllers using a set of closed‐loop frequency‐domain data. The principle of such an approach is based on computing the parameters of a fixed‐order controller for which the closed‐loop frequency response fits a desired frequency response that describes some desired performance indices. This problem is formulated as an error minimization problem, which can be solved to find suitable values of the controller parameters. The main feature of the proposed control methodology is that it can be applied to stable and unstable plants. Additionally, the design process depends on a pre‐selected controller structure, which allows for the selection of low‐order controllers. An application of the proposed method to a DC servomotor system is presented to experimentally validate and demonstrate its efficacy.

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Data-Driven Controller Design

Cited by 77 publications

References 1 publication

Mixed H<inf>2</inf>/H<inf>∞</inf> Data-Driven Control Design for Hard Disk Drives

Mixed H<inf>2</inf>/H<inf>∞</inf> Data-Driven Control Design for Hard Disk Drives

Robust control of discrete minimum and non‐minimum phase systems via data‐driven virtual reference feedback tuning and IMC

A Measurement‐Based Approach for Designing Fixed‐Order Controllers for Unknown Closed‐Loop Architecture

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