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The paper aims to compare and prove a pair of disturbance/uncertainty rejection control laws for the well-known four-tank control problem. The control requirements are expressed in terms of a set point sequence as usual in the literature. The uncertainty class is defined as the union of four sub-classes: unknown disturbance, parametric uncertainty, measurement errors and neglected dynamics. Modelling and design give insight on the dynamic properties of the problem. Two theorems, which fix the range of application, are presented. These theorems are confirmed by the simulated results, and indicate the correct way to further broaden the control design applicability. The disturbance rejection design is deployed using the Embedded Model Control methodology. Accordingly, only the unknown disturbance and parametric uncertainty can be rejected, whereas the effects of neglected dynamics must be filtered. As a result, simple performance and stability inequality can be formulated in the frequency domain: they guide the closed-loop pole placement. These inequalities reveal whether pole placement is feasible and how feasibility can be recovered. The latter is an issue, which at the authors' knowledge, is rarely encountered in the literature. Simulated runs prove the effectiveness of the design procedure., (Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.)

Objective: The treatment of platinum resistant/refractory epithelial ovarian cancer (EOC) is a challenge for oncologists. One of the most utilized drugs in these patients is pegylated liposomal doxorubicin (PLD). As PLD is active only in a small subset of patients and causes side effects, selection of responsive patients is an unmet need and might be guided by the status of the DNA topoisomerase II alpha (TOP2A) that is poisoned by the drug., Methods: From 176 ovarian cancers treated in three institutions, we selected 38 patients treated with PLD monotherapy as second/third line of treatment. TOP2A gene copies were measured using Fluorescent In Situ Hybridization (FISH) and expression evaluated using immunohistochemistry. Patients' derived xenografts (PDXs) of ovarian cancers were used to assess the correlation between TOP2A protein expression and response to PLD., Results: Clinical data showed that TOP2A gene gain that is paralleled by increased expression of the protein, was associated with a higher probability of clinical benefit from PLD. Treatment of PDXs demonstrated that only xenografts showing a high percentage of TOP2A expressing cells underwent tumor shrinkage when treated with PLD., Conclusions: These data show that TOP2A gene gain and protein over-expression might predict activity of PLD in platinum resistant/refractory EOC., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Solenoid current regulation is well-known and standard in any proportional electro-hydraulic valve. The goal is to provide a wide-band transfer function from the reference to the measured current, thus making the solenoid a fast and ideal force actuator within the limits of the power supplier. The power supplier is usually a Pulse Width Modulation (PWM) amplifier fixing the voltage bound and the Nyquist frequency of the regulator. Typical analog regulators include three main terms: a feedforward channel, a proportional feedback channel and the electromotive force compensation. The latter compensation may be accomplished by integrative feedback. Here the problem is faced through a model-based design (Embedded Model Control), on the basis of a wide-band embedded model of the solenoid which includes the effect of eddy currents. To this end model parameters must be identified. The embedded model includes a stochastic disturbance dynamics capable of estimating and correcting the electromotive contribution together with parametric uncertainty, variability and state dependence. The embedded model which is fed by the measured current and the supplied voltage becomes a state predictor of the controllable and disturbance dynamics. The control law combines reference generator, state feedback and disturbance rejection to dispatch the PWM amplifier with the appropriate duty cycle. Modeling, identification and control design are outlined together with experimental result. Comparison with an existing analog regulator is also provided., (© 2013 ISA. Published by Elsevier Ltd. All rights reserved.)

Robust control design guarantees closed-loop stability of a model-based control law in the presence of parametric uncertainties. Stability is guaranteed by introducing some ignorance coefficients and restricting the feedback control effort. Embedded Model Control shows that the model-based control law can be kept intact in the case of uncertainty, if the controllable dynamics is complemented by a suitable disturbance dynamics. The disturbance state must be driven by an unpredictable input vector, the noise, which can only be estimated from the model error i.e. the difference between plant and model output. The uncertainty-based design concerns the noise estimator, so as to prevent the model error from conveying uncertainty components which are command-dependent and thus prone to destabilizing the controlled plant. Separation of the components in the low and high frequency domain by the noise estimator itself allows stability recovery and guarantee, and the rejection of low frequency components. Two simple case studies help to understand the key assets of the methodology., (Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.)

Embedded Model Control allows one to proceed systematically from fine plant dynamics and control requirements to the Embedded Model (EM), which is the core of control design and algorithms. The model defines three interconnected parts: the controllable dynamics, the disturbance class to be rejected and the neglected dynamics. Controllable and disturbance dynamics must be observable from the plant measurements. Control algorithms are designed around the first two parts, while stability and performance are constrained by the third one. The key design issue is discriminating between driving noise and neglected dynamics, to guarantee updating disturbance in view of its rejection. To this end, concept and equations of the 'error loop' are outlined: it maps error sources to performance and shows how to discriminate destabilizing sources, while meeting performance requirements. An introductory example with analytical and simulated results illustrates the design steps.

Embedded Model Control (EMC) methodology is applied to web-winding control problems. These require time-varying Embedded Model and adaptive control law, because of a variable winder radius; disturbance estimation and rejection, because of friction and variable web speed and acceleration; sensorless reel radius estimation; and robust stability and performance in the presence of web and gear vibrations. The goal is to solve these key issues in the framework of EMC, which amounts to (i) designing a time-varying Control Law capable of disturbance rejection, (ii) designing Noise Estimators capable of keeping live and accurate disturbance and radius estimates, and (iii) tuning their eigenvalues to guarantee stability and performance. Tuning takes advantage of an 'error loop' formulation, which explicitly relates neglected dynamics to eigenvalues, stability and performance. Simulated runs from a fine winder model are compared to published results.

This paper is concerned with active vibration suppression in a suspended Fabry-Pérot cavity, employed as the sensor in an innovative thrust-stand, called Nanobalance. The Nanobalance aims to exploit the sensitivity of in-vacuum Fabry-Pérot interferometers to sub-nanometric displacements in order to measure thrust (<1 mN) and noise of space microthrusters with micronewton accuracy. The instrument has been conceived around an in-vacuum optical Fabry-Pérot cavity embraced by two pendulums (the active and the passive) suspended to an athermic spacer. The thruster under test is mounted on the active pendulum and an equal dummy thruster is mounted on the passive one for balancing. The objective of the paper is to suppress the beat motion centered on the mean pendulum natural frequency (10-14 Hz depending on the thruster under test) without affecting the measurement bandwidth (2 Hz) where thrust has to be measured. Beat motion arises because of small pendulum imbalances excited by ground noise. Relevant digital control strategies and experimental results will be presented and discussed.