A patterning strategy for large area arrays of high density nanostructures

Carlos Calaza, Mariana Antunes, Bernardo Pires, Jordi Llobet, Marco Martins, Sofia Martins, Helder Fonseca, Elisabete Fernandes and João Gaspar, NanoIL 2018

A production-worthy method to implement high density arrays of sub-micron nanostructures at a wafer scale is proposed. It is based on a co-optimization of the layout design, the e-beam lithography exposure and the intermediate SiO2 hard mask used for the final silicon etch process. The great complexity of the e-beam lithography exposure required at this scale to directly obtain the desired geometries has been reduced by introducing an intermediate hard mask to get independent control of some of the pattern parameters through the fabrication process. Rather than using e-beam lithography to create a resist mask for the etch process, which results in unaffordable exposure times for complex geometries (large patterns of curved structures), a simplified e-beamlithography step has been developed to attain a primary resist mask with needed shape and periodicity, but smaller size.


Analytical Characterization of End-to-End Communication Delays with Logical Execution Time

J. Martinez, I. Sañudo and M. Bertogna, "Analytical Characterization of End-to-End Communication Delays With Logical Execution Time," in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 37, no. 11, pp. 2244-2254, Nov. 2018. DOI: 10.1109/TCAD.2018.2857398

Modern automotive embedded systems are composed of multiple real-time tasks communicating by means of shared variables. The effect of an initial event is typically propagated to an actuation signal through sequences of tasks writing/reading shared variables, creating an effect chain (EC). The responsiveness, performance and stability of the control algorithms of an automotive application typically depend on the propagation delays of selected ECs. Indeed, task jitter can have a negative impact on the system potentially leading to instability. The logical execution time (LET) model has been recently adopted by the automotive industry as a way of reducing jitter and improving the determinism of the system. In this paper, we provide a formal analysis of the LET model for real-time systems composed of periodic tasks with harmonic and nonharmonic periods, analytically characterizing the control performance of LET ECs. We also show that by introducing tasks offsets, the real-time performance of nonharmonic tasks may improve, getting closer to the constant end-to-end latency experienced in the harmonic case. Further, we present a heuristic algorithm to obtain a set of offsets that might reduce end-to-end latencies, improving LET communication determinism. Finally, we apply this technique to an industrial case study consisting of an automotive engine control system.

Comparing Platform-Aware Control Design Flows For Composable and Predictable TDM-Based Execution Platforms

J. Valencia, D. Goswami and K. Goossens. 2019. "Comparing Platform-aware Control Design Flows for Composable and Predictable TDM-based Execution Platforms". ACM Trans. Des. Autom. Electron. Syst. 24, 3, Article 32 (March 2019), 26 pages. DOI:

We compare three platform-aware feedback control design flows that are tailored for a composable and predictable Time Division Multiplexing (TDM)-based execution platform. The platform allows for independent execution of multiple applications. Using the precise timing knowledge of the platform execution, we accurately characterise the execution of the control application (i.e., sensing, computing, and actuating operations) to design efficient feedback controllers with high control performance in terms of settling time. The design flows are derived for Single-Rate (SR) and Multi-Rate (MR) sampling schemes. We show the applicability of the design flows based on two design considerations and their trade-off: control performance and resource utilisation. The design flows are validated by means of MATLAB and Hardware-in-the-Loop (HIL) experiments for a motion control application.

MPC-PID control of operator-in-the-loop overhead cranes: A practical approach

M. Giacomelli, M. Faroni, D. Gorni, A. Marini, L. Simoni and A. Visioli, "MPC-PID control of operator-in-the-loop overhead cranes: A practical approach," 2018 7th International Conference on Systems and Control (ICSC), Valencia, 2018, pp. 321-326. DOI: 10.1109/ICoSC.2018.8587775

In this paper, a velocity control system for industrial overhead cranes based on a Model Predictive Control approach is proposed. The problem of the control of the operator-in-the-loop system is addressed, as the operator drives the system pushing a button while the control algorithm drives the cart reducing the oscillations of the load. An inner velocity control loop is used in order to overcome some of the problems of controlling the system by using directly the torque of the motor as a control variable. Simulations show the effectiveness of the approach, in particular in the presence of friction.

Model Predictive Control for operator-in-the-loop overhead cranes

M. Giacomelli, M. Faroni, D. Gorni, A. Marini, L. Simoni, A. Visioli, "Model Predictive Control for operator-in-the-loop overhead cranes", 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA), Turin, 2018, pp. 589-596. DOI: 10.1109/ETFA.2018.8502591

In this paper, a Model Predictive Control approach for the velocity control of operator-in-the loop overhead cranes is proposed. The operator can select the maximum position overshoot as a tuning parameter for the method. Simulations provide a comparison between the proposed method and the well known Zero Vibration input shaping technique, showing its effectiveness in controlling the payload oscillations.

Learning in Machines

T. Oomen, "Learning in Machines", Mikroniek December 2018

Control of high-tech mechatronic systems traditionally involves feedback and feedforward control, and essentially only uses a few recent measurements. Here, we aim to explore what can be learned from all available sensor data. A general learning framework is developed that exploits the abundance of data of previously executed tasks. Both fundamental insight and experimental results show that such iterative learning control approaches enable substantial performance improvement compared to traditional control. Interestingly, traditional model-based control theory turns out to have an essential role for fast and safe learning from measured data.

A Fast Autotuning Method for Velocity Control of Mechatronic Systems

M. Giacomelli, D. Colombo, L. Simoni, G. Finzi, A. Visioli, “A Fast Autotuning Method for Velocity Control of Mechatronic Systems”, IFAC-PapersOnLine, Volume 51, Issue 4, 2018, Pages 208-213

In this paper a fast automatic tuning methodology for velocity controllers of mechatronic systems is proposed. In order to be applicable in general, the method takes into account the position, velocity and torque constraints of the motion control system and it requires a minimum intervention of the operator. Further, it can be implemented also with small computational capabilities which makes it suitable for industrial drives. Simulation results show the effectiveness of the technique.

Simplified input-output inversion control of a double pendulum overhead crane for residual oscillations reduction

Marco Giacomelli, Fabrizio Padula, Luca Simoni, Antonio Visioli, “Simplified input-output inversion control of a double pendulum overhead crane for residual oscillations reduction” MECHATRONICS, DOI: 10.1016/j.mechatronics.2018.10.002

In this paper we present the application of an input-output inversion technique for the open-loop control of an overhead crane modelled as a double pendulum. The method is mathematically derived, obtaining a parametric trajectory that ensures reduced residual oscillations. Then, it is shown that the postactuation can be neglected so that the method can be implemented with standard industrial drives. The robustness of the method is evaluated by means of simulations, and the performance of the method is experimentally compared with the well-known input shaping technique. The advantages of using a double pendulum model instead of a simple pendulum one are also shown.

On the inclusion of temperature in the friction model of industrial robots

L. Simoni, M. Beschi, G. Legnani, A. Visioli, “On the inclusion of temperature in the friction model of industrial robots”, 20th IFAC World Congress, Tolouse (F), 2017, DOI: 10.1016/j.ifacol.2017.08.933

This paper deals with a modelling technique that takes into account the effects of the temperature in the joint friction of industrial robot manipulators. In particular, it is shown that a general friction model can be suitably modified by explicitly considering the temperature as a parameter. This allows to estimate the friction term accurately in different operating conditions without the direct measurement of the joint internal temperature, which makes the overall technique suitable to apply in practical cases. Experimental results show the effectiveness of the methodology.

Modelling the temperature in joint friction of industrial manipulators

L. Simoni, M. Beschi, G. Legnani, A. Visioli, “Modelling the temperature in joint friction of industrial manipulators, Robotica, DOI: 10.1017/S0263574717000509

In this paper, a new model for joint dynamic friction of industrial robot manipulators is presented. In particular, the effects of the temperature in the joints are considered. A polynomial-based model is proposed and the parameter estimation is performed without the need of a joint temperature sensor. The use of an observer is then proposed to compensate for the uncertainty in the initial estimation of the temperature value. A large experimental campaign show that the model, in spite of the simplifying assumptions made, is effective in estimating the joint temperature and therefore the friction torque during the robot operations, even for values of velocities that have not been previously employed.

On the use of a temperature based friction model for a virtual force sensor in industrial robot manipulators

L. Simoni, E. Villagrossi, M. Beschi, A. Marini, N. Pedrocchi, L. Molinari Tosatti, G. Legnani, A. Visioli, “On the use of a temperature based friction model for a virtual force sensor in industrial robot manipulators”, IEEE International Conference on Emerging Technologies and Factory Automation, Limassol (CY), 2017. DOI: 10.1109/ETFA.2017.8247655

In this paper we propose the use of a dynamic model in which the effects of temperature on friction are considered to develop a virtual force sensor for industrial robot manipulators. The estimation of the inertial parameters and of the friction model are explained. The effectiveness of the virtual force sensor has been proven in a polishing task. In fact, the interaction forces between the robot and the environment has been measured both with the virtual force sensor and a common load cell.  Moreover, the advantages provided by considering the temperature dependency are highlighted.