53 research outputs found

    Model-Free Plant Tuning

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    Given a static plant described by a differentiable input-output function, which is completely unknown, but whose Jacobian takes values in a known polytope in the matrix space, this paper considers the problem of tuning (i.e., driving to a desired value) the output, by suitably choosing the input. It is shown that, if the polytope is robustly nonsingular (or has full rank, in the nonsquare case), then a suitable tuning scheme drives the output to the desired point. The proof exploits a Lyapunov-like function and applies a well-known game-theoretic result, concerning the existence of a saddle point for a min-max zero-sum game. When the plant output is represented in an implicit form, it is shown that the same result can be obtained, resorting to a different Lyapunov-like function. The case in which proper input or output constraints must be enforced during the transient is considered as well. Some application examples are proposed to show the effectiveness of the approach

    Model Predictive Control for Temperature Regulation of Professional Ovens

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    We apply the model predictive control (MPC) strategy in an industrial setting, specifically for controlling the temperature of Combi Oven Professional Appliances. The proposed method takes into account input and output constraints, as well as the presence of multiple sources of disturbance. The workflow includes identifying and validating a model of the cell temperature and incorporating disturbance models. MPC is implemented using a state-space formulation. The proposed method shows significant energy saving and tracking error reduction with respect to the current oven control; its effectiveness has been demonstrated through several tests carried out on a professional oven

    Model-free feedback control synthesis from expert demonstration

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    We show how it is possible to synthesize a stabilizing feedback control, in the complete absence of a model, starting from the open-loop control generated by an expert operator, capable of driving a system to a specific set-point. We assume that the system is linear and discrete time. We propose two different controls: a linear dynamic and a static, piecewise linear, one. We show the performance of the proposed controllers on a ship steering problem

    A convex programming approach to the inverse kinematics problem for manipulators under constraints

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    Abstract We propose a novel approach to the problem of inverse kinematics for possibly redundant planar manipulators. We show that, by considering the joints as point masses in a fictitious gravity field, and by adding proper constraints to take into account the length of the links, the kinematic inversion may be cast as a convex programming problem. Convex constraints in the decision variables (in particular, linear constraints in the workspace) are easily managed with the proposed approach. We also show how to exploit the idea for avoiding obstacles while tracking a reference end-effector trajectory and discuss how to extend the results to some kinds of non-planar manipulators. Simulation results are reported, showing the effectiveness of the approach

    Quality of images with toric intraocular lenses

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    Purpose: To objectively evaluate the image quality obtained with toric intraocular lenses (IOLs) when misaligned from the intended axis. Setting: University Eye Clinic and the Department of Industrial and Information Engineering, University of Trieste, Trieste, Italy. Design: Experimental study. Methods: An experimental optoelectronic test bench was created. It consisted of a high-resolution monitor to project target images and an artificial eye. The system simulates the optical and geometric characteristics of the human eye with an implanted toric IOL. A 3.00 diopters corneal astigmatism was simulated. Images reproduced by the optical system were captured according to different IOL axis positions. The quality of each image was analyzed using the visual information fidelity (VIF) criterion. The VIF reduction was calculated at each IOL rotational step. Results: A 5-degree IOL axis rotation from the intended position determined a decay in the image quality of 7.03%. Ten degrees of IOL rotation caused an 11.09% decay of relative VIF value. For a 30-degree rotation, the VIF decay value was 45.85%. Finally, the image decay with no toric correction was 56.70%. Conclusions: The more the objective quality of the image decays progressively, the further the axis of the IOL is rotated from its intended position. The reduction in image quality obtained after 30 degrees of toric IOL rotation was less than 50% and after 45 degrees, the image quality was the same as that of no toric correction

    A control system for preventing cavitation of centrifugal pumps

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    Cavitation is a well-known phenomenon that may occur, among other turbo-machines, in centrifugal pumps and can result in severe damage of both the pump and the whole hydraulic system. There are situations in which, in principle, the cavitation could be avoided by detecting the condition of incipient cavitation, and changing slightly the working point of the whole system in order to move away from that condition. In the present paper two simple closed-loop control strategies are implemented, acting on the pump's rotational speed and fed by the measurements of a set of inertial sensors. In particular, the research is focused on a centrifugal pump normally employed in hydraulic systems. The pump operates in a dedicated test rig, where cavitation can be induced by acting on a reservoir's pressure. Three accelerometers are installed in the pump body along three orthogonal axes. An extensive set of experiments has been carried out at different flow rates and a number of signals' features both in the time domain and in the frequency domain have been considered as indicators of incipient cavitation. The amount of energy of the signal captured by the accelerometer in the component orthogonal to the flow direction, in the band from 10 to 12.8 kHz, demonstrated to be effective in detecting the incipient cavitation, by selecting a proper (condition-dependent) threshold. Therefore, two simple controllers have been designed: the first regulates the speed of the pump, to recover from cavitation, bringing the indicator back to the nominal value, while the second allows to reduce the pump's rotational speed when the cavitation detector indicates the incipient cavitation and restoring the nominal speed when possible. The latter approach is rather general, because the threshold-based detector can be substituted by any detector providing binary output. Experimental results are reported that demonstrate the effectiveness of the approach

    Free-electron laser spectrum evaluation and automatic optimization

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    The radiation generated by a seeded free-electron laser (FEL) is characterized by a high temporal coherence, which is close to the Fourier limit in the ideal case. The setup and optimization of a FEL is a non-trivial and challenging operation. This is due to the plethora of highly sensitive machine parameters and to the complex correlations between them. The fine tuning of the FEL process is normally supervised by physicists and is carried out by scanning various parameters with the aim of optimizing the spectrum of the emitted pulses in terms of intensity and line-width. In this article we introduce a novel quantitative method for the evaluation of the FEL spectrum via a quality index. Moreover, we investigate the possibility of optimization of the FEL parameters using this index as the objective function of an automatic procedure. We also present the results of the preliminary tests performed in the FERMI FEL focused on the effectiveness and ability of the automatic procedure to assist in the task of machine tuning and optimization

    Implementation of the ERAS (Enhanced Recovery After Surgery) protocol for colorectal cancer surgery in the Piemonte Region with an Audit and Feedback approach: study protocol for a stepped wedge cluster randomised trial: a study of the EASY-NET project

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    Speeding-up pruning for Artificial Neural Networks: Introducing Accelerated Iterative Magnitude Pruning

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    In recent years, Artificial Neural Networks (ANNs) pruning has become the focal point of many researches, due to the extreme overparametrization of such models. This has urged the scientific world to investigate methods for the simplification of the structure of weights in ANNs, mainly in an effort to reduce time for both training and inference. Frankle and Carbin, and later Renda, Frankle, and Carbin introduced and refined an iterative pruning method which is able to effectively prune the network of a great portion of its parameters with little to no loss in performance. On the downside, this method requires a large amount of time for its application, since, for each iteration, the network has to be trained for (almost) the same amount of epochs of the unpruned network. In this work, we show that, for a limited setting, if targeting high overall sparsity rates, this time can be effectively reduced for each iteration, save for the last one, by more than 50%, while yielding a final product (i.e., final pruned network) whose performance is comparable to the ANN obtained using the existing method

    Crossing the Reality Gap: a Survey on Sim-to-Real Transferability of Robot Controllers in Reinforcement Learning

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    The growing demand for robots able to act autonomously in complex scenarios has widely accelerated the introduction of Reinforcement Learning (RL) in robots control applications. However, the trial and error intrinsic nature of RL may result in long training time on real robots and, moreover, it may lead to dangerous outcomes. While simulators are useful tools to accelerate RL training and to ensure safety, they often are provided only with an approximated model of robot dynamics and of its interaction with the surrounding environment, thus resulting in what is called the reality gap (RG): a mismatch of simulated and real control-law performances caused by the inaccurate representation of the real environment in simulation. The most undesirable result occurs when the controller learnt in simulation fails the task on the real robot, thus resulting in an unsuccessful sim-to-real transfer. The goal of the present survey is threefold: (1) to identify the main approaches to face the RG problem in the context of robot control with RL, (2) to point out their shortcomings, and (3) to outline new potential research areas
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