This paper proposes the use of regularization on the multivariable formulation of the Virtual Reference Feedback Tuning (VRFT). When the process to be controlled has a significant amount of noise, the standard VRFT approach, that uses the instrumental variable technique, provides estimates with very poor statistical properties. To cope with that, this paper considers the use of regularization on the estimation procedure, reducing the covariance error at the cost of inserting a small bias. Also, this paper explains different types of regularization matrices and presents the methodology to tune these matrices. In order to demonstrate the benefits of the proposed formulation, a numerical example is presented.

Abstract This paper deals with Data-Driven (DD) control design in a Model Reference (MR) framework. We present a new \{DD\} method for tuning the parameters of a controller with a fixed structure. Because the method originates from embedding the control design problem in the Prediction Error identification of an optimal controller, it is baptized as Optimal Controller Identification (OCI). Incorporating different levels of prior information about the optimal controller leads to different design choices, which allows to shape the bias and variance errors in its estimation. It is shown that the limit case where all available prior information is incorporated is tantamount to model-based design. Thus, this methodology also provides a framework in which model-based design and \{DD\} design can be fairly and objectively compared. This comparison reveals that \{DD\} design essentially outperforms model-based design by providing better bias shaping, except in the full order controller case, in which there is no bias and model-based design provides smaller variance. The practical effectiveness of the design methodology is illustrated with experimental results.

Abstract Identification of an output error model using the prediction error method leads to an optimization problem built on input/output data collected from the system to be identified. It is often hard to find the global solution of this optimization problem because in most cases both the corresponding objective function and the search space are nonconvex. The difficulty in solving the optimization problem depends mainly on the experimental conditions, more specifically on the spectra of the input/output data collected from the system. It is therefore possible to improve the convergence of the algorithms by properly choosing the data prefilters; in this paper we show how to perform this choice. We present the application of the proposed approach to case studies where the standard algorithms tend to fail to converge to the global minimum.

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Fossil assemblages are expected to be time-averaged as a result of biological and physical processes that mix skeletal remains. Our quantitative understanding of time-averaging derives primarily from actualistic studies, in which direct numerical dating of individual specimens is used to assess the scale and structure of age mixing in death assemblages (incipient fossil assemblages). Here we examine the age, and the time-averaging of Mactra shells (Bivalvia: Mollusca) gathered from surface mixed siliciclastic-bioclastic sands at three sites on a passive-margin subtropical shelf (the Southern Brazilian Shelf; ∼ 33°S). Sixty Mactra specimens were individually dated using amino acid racemization (AAR) calibrated using radiocarbon ages (n=15). The time-averaging and the total age variability was based on a Bayesian approach that integrates the estimation errors and uncertainties derived from the posterior distribution associated with the AAR calibration average model. The 14C-calibrated AAR ages, pooled across all three sites, are strongly right-skewed with 97% of the individual mollusk shell age estimates ranging from 0 to 6 cal kyr BP. The magnitude of time-averaging varied inversely with the water depth, from < 15 yr at the deepest site (21 m) up to 1020-1250 yr at the shallowest site (7 m). The substantial variation in the temporal resolution across nearby sites, which are located in a seemingly homogenous depositional setting, indicates the presence of notable (if cryptic) spatial heterogeneities in local sedimentation, production, and exhumation, all increasing with water depth. Copyright © 2017, SEPM (Society for Sedimentary Geology).

Empty mollusk shells may act as colonization surfaces for sclerobionts depending on the physical, chemical, and biological attributes of the shells. However, the main factors that can affect the establishment of an organism on hard substrates and the colonization patterns on modern and time-averaged shells remain unclear. Using experimental and field approaches, we compared sclerobiont (i.e., bacteria and invertebrate) colonization patterns on the exposed shells (internal and external sides) of three bivalve species (Anadara brasiliana, Mactra isabelleana, and Amarilladesma mactroides) with different external shell textures. In addition, we evaluated the influence of the host characteristics (mode of life, body size, color alteration, external and internal ornamentation and mineralogy) of sclerobionts on dead mollusk shells (bivalve and gastropod) collected from the Southern Brazilian coast. Finally, we compared field observations with experiments to evaluate how the biological signs of the present-day invertebrate settlements are preserved in molluscan death assemblages (incipient fossil record) in a subtropical shallow coastal setting. The results enhance our understanding of sclerobiont colonization over modern and paleoecology perspectives. The data suggest that sclerobiont settlement is enhanced by (i) high(er) biofilm bacteria density, which is more attracted to surfaces with high ornamentation; (ii) heterogeneous internal and external shell surface; (iii) shallow infaunal or attached epifaunal life modes; (iv) colorful or post-mortem oxidized shell surfaces; (v) shell size (<50 mm2 or >1,351 mm2); and (vi) calcitic mineralogy. Although the biofilm bacteria density, shell size, and texture are considered the most important factors, the effects of other covarying attributes should also be considered. We observed a similar pattern of sclerobiont colonization frequency over modern and paleoecology perspectives, with an increase of invertebrates occurring on textured bivalve shells. This study demonstrates how bacterial biofilms may influence sclerobiont colonization on biological hosts (mollusks), and shows how ecological relationships in marine organisms may be relevant for interpreting the fossil record of sclerobionts relationships in marine organisms may be relevant for interpreting the fossil record of sclerobionts. © 2017 Ochi Agostini et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Copyright © 2017, SEPM (Society for Sedimentary Geology). Fossil assemblages are expected to be time-averaged as a result of biological and physical processes that mix skeletal remains. Our quantitative understanding of time-averaging derives primarily from actualistic studies, in which direct numerical dating of individual specimens is used to assess the scale and structure of age mixing in death assemblages (incipient fossil assemblages). Here we examine the age, and the time-averaging of Mactra shells (Bivalvia: Mollusca) gathered from surface mixed siliciclastic-bioclastic sands at three sites on a passive-margin subtropical shelf (the Southern Brazilian Shelf; ∼ 33°S). Sixty Mactra specimens were individually dated using amino acid racemization (AAR) calibrated using radiocarbon ages (n=15). The time-averaging and the total age variability was based on a Bayesian approach that integrates the estimation errors and uncertainties derived from the posterior distribution associated with the AAR calibration average model. The 14C-calibrated AAR ages, pooled across all three sites, are strongly right-skewed with 97{%} of the individual mollusk shell age estimates ranging from 0 to 6 cal kyr BP. The magnitude of time-averaging varied inversely with the water depth, from {\textless} 15 yr at the deepest site (21 m) up to 1020-1250 yr at the shallowest site (7 m). The substantial variation in the temporal resolution across nearby sites, which are located in a seemingly homogenous depositional setting, indicates the presence of notable (if cryptic) spatial heterogeneities in local sedimentation, production, and exhumation, all increasing with water depth.

© 2017 Ochi Agostini et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Empty mollusk shells may act as colonization surfaces for sclerobionts depending on the physical, chemical, and biological attributes of the shells. However, the main factors that can affect the establishment of an organism on hard substrates and the colonization patterns on modern and time-averaged shells remain unclear. Using experimental and field approaches, we compared sclerobiont (i.e., bacteria and invertebrate) colonization patterns on the exposed shells (internal and external sides) of three bivalve species (Anadara brasiliana, Mactra isabelleana, and Amarilladesma mactroides) with different external shell textures. In addition, we evaluated the influence of the host characteristics (mode of life, body size, color alteration, external and internal ornamentation and mineralogy) of sclerobionts on dead mollusk shells (bivalve and gastropod) collected from the Southern Brazilian coast. Finally, we compared field observations with experiments to evaluate how the biological signs of the present-day invertebrate settlements are preserved in molluscan death assemblages (incipient fossil record) in a subtropical shallow coastal setting. The results enhance our understanding of sclerobiont colonization over modern and paleoecology perspectives. The data suggest that sclerobiont settlement is enhanced by (i) high(er) biofilm bacteria density, which is more attracted to surfaces with high ornamentation; (ii) heterogeneous internal and external shell surface; (iii) shallow infaunal or attached epifaunal life modes; (iv) colorful or post-mortem oxidized shell surfaces; (v) shell size ( {\textless} 50 mm2 or {\textgreater} 1,351 mm 2 ); and (vi) calcitic mineralogy. Although the biofilm bacteria density, shell size, and texture are considered the most important factors, the effects of other covarying attributes should also be considered. We observed a similar pattern of sclerobiont colonization frequency over modern and paleoecology perspectives, with an increase of invertebrates occurring on textured bivalve shells. This study demonstrates how bacterial biofilms may influence sclerobiont colonization on biological hosts (mollusks), and shows how ecological relationships in marine organisms may be relevant for interpreting the fossil record of sclerobionts relationships in marine organisms may be relevant for interpreting the fossil record of sclerobionts.

Virtual Reference Feedback Tuning (VRFT) is a data-driven technique used to design controllers without the need of a process model, only input-output data is utilized. When the process has non-minimum phase (NMP) zeros, the original method usually presents poor performance, because scarcely the reference model has the same NMP zeros as the process. To overcome this problem, a flexible criterion has been proposed to the VRFT method, in a way that both the controller parameters and the NMP zeros of the process are estimated together. In this paper we present the application of the VRFT method with flexible criterion to the level control of a MIMO pilot plant. We show that a sequential controller design may incorporate NMP behavior to the process. We then use the VRFT method with flexible criterion to design the controller using only closed-loop data from the process.

This paper considers the design and implementation of a discrete-time fast tracking controller for quadrotor vehicles subject to perturbations. The proposed controller consists of a model-based disturbance observer and a Composite Nonlinear Feedback (CNF) controller. The CNF control law introduces nonlinear damping to the system so that it possesses a fast rise time without overshoot. The least square identification method is applied to develop a model based disturbance observer, thus decoupling the problems of track following and disturbance rejection. Experimental results are provided in order to validate the proposed approach.

In this work a modified Resonant Controller is proposed to deal with the tracking/rejection problem of periodic signals robust to period variations and parametric uncertainties in the plant. The control strategy is based on a resonant structure in series with a notch filter, which will be responsible to improve the robustness to period variation. A robust state feedback controller is designed by solving a linear matrix inequality (LMI) optimization problem guaranteeing the robust stability of the closed loop system. A numerical example is presented to illustrate the method.

Iterative Feedback Tuning (IFT) is a data-driven method used to tune parameters of feedback controllers minimising an H2 criterion. The method uses data from experiments to estimate the gradient of the criterion, and uses iterative quasinewton algorithms to adjust the controllers. When the method is used in cascade systems, usually the inner loop is firstly adjusted, and after the outer loop. In this article we describe an extension to the IFT method that adjusts both inner and outer loop at the same time using only data from closed-loop experiments at each iteration.

Abstract Continuous process industries usually have hundreds to thousands of control loops, most of which are coupled, i.e. one control loop affects the behavior of another control loop. In order to properly design the controllers and reduce the interactions between loops it is necessary to consider the multivariable structure of the process. Usually {MIMO} (multiple-input, multiple-output) controllers are designed using {MIMO} models of the process, but obtaining these models is a task very demanding and time consuming. Virtual Reference Feedback Tuning ({VRFT}) is a data-driven technique to design controllers which do not use a model of the process; all the needed information is collected from input/output data from an experiment. The method is well established for {SISO} (single-input, single-output) systems and there are some extensions to {MIMO} process which assume that all the outputs should have the same closed-loop performance. In this paper we develop a complete framework to {MIMO} {VRFT} which provides unbiased estimates to the optimal {MIMO} controller (when it is possible) even when the closed-loop performances are distinct to each loop. When it is not possible to obtain the optimal controller because the controller class is too restrictive (for example {PID} controllers) then we propose the use of a filter to reduce the bias on the estimates. Also, when the data is corrupted by noise, the use of instrumental variables to eliminate the bias on the estimate should be considered. The article presents simulation examples and a practical experiment on a tree tank system where the goal is to control the level of two tanks.