Gain scheduling for hybrid force/velocity control in contour tracking task

In this paper a gain scheduling approach is proposed for the hybrid force/velocity control of an industrial manipulator employed for the contour tracking of objects of unknown shape. The methodology allows to cope with the configuration dependent dynamics of the manipulator during a constrained motion and therefore a significant improvement of the performance results. Experimental results obtained with an industrial SCARA manipulator demonstrate the effectiveness of the technique

Modelling the temperature in joint friction of industrial manipulators

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 Inclusion of Temperature in the Friction Model of Industrial Robots

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

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

Nash Solution as a Multi-Criteria Decision Making Technique for Control Problems

[Abstract] A control system problem can be viewed as a multiobjective problem due to the fact that there are many requirements to be satisfied. Nowadays, multi-objective optimization deals with this kind of problem by implementing optimization techniques, capable of searching for the Pareto set approximation, hereafter the designer needs to select the best solution that provides a good trade-off among the competitve objectives from the Pareto front approximation. Therefore, in this communication we address the problem of selecting the best trade-off between the conflictive objectives, this stage is called the Multi-Criteria Decision Making (MCDM). In this paper we propose to use the Nash solution as a tuning technique to select the design alternative to implement on the control system. This selection is compared with others Proportional-Integral (PI) tuning rules on the literature.This work has received financial support from the Spanish Ministry of Economy and Competitiveness program under grant DPI2013-47825-C3-1-R. The financial support from the University of Costa Rica, under the grants 322-B4-218 and 731-B4-213, is greatly appreciatedUniversidad de Costa Rica; 322-B4-218Universidad de Costa Rica; 731-B4-213https://doi.org/10.17979/spudc.978849749808

International Master Program on Mechatronic Systems for Rehabilitation

This paper describes a second level of university course called Master in France, Laurea Magistrale in Italy, jointly organized by UPMC Université Pierre et Marie Curie – Paris (France) and UniBS Università degli Studi di Brescia (Italy). During this "double-degree" course, students coming from these universities share two semesters while studying subjects related to mechatronics and biomechanics. At the end of the program the students obtain a double degree from both universities

A Predictive Technique for the Real-Time Trajectory Scaling under High-Order Constraints

Modern robotic systems must be able to react to unexpected environmental events. To this purpose, planning techniques for the real-time generation/modification of trajectories have been developed in recent times. In the frequent case of applications which require following a predefined path, the assigned time-law must be inspected in real time so as to verify whether it satisfies the system constraints or, conversely, if it must be scaled in order to obtain a feasible trajectory. The problem has been addressed in several ways in the literature. One of the known approaches, based on the use of nonlinear filters, is revised in this paper in order to return feasible solutions under any circumstances. Differently from alternative strategies, it manages constraints up to the torque derivatives and has evaluation times compatible with the ones required by modern control systems. The proposed technique is validated through simulations and real experiments. Comparisons are proposed with an algorithm based on a model predictive technique and with an alternative scaling system

MPC for Propofol Anesthesia: the Noise Issue

The design of automatic control systems for general anesthesia is a challenging task due to the severe safety requirements and process constraints. This is even more complex when model-based control techniques are used due to the significant variability of the process model. Additionally, issues like noisy measurements and interference also influence the control system overall performance. In this context, adequate filtering and control system sampling period selection should be analyzed to test their influence on the controller. In this paper, an MPC system for the depth of hypnosis, where the BIS signal is used as a controlled variable, is analyzed. The main purpose is to test and evaluate how the process noise affects the performance of the control system. The analysis is performed in a simulation study using a dataset of virtual patients representative of a wide population. Results show that a satisfactory performance is obtained when the noise is explicitly taken into account in the controller tuning procedure for a specific sampling period

Event-based MPC for propofol administration in anesthesia

Background and Objective : The automatic control of anesthesia is a demanding task mostly due to the presence of nonlinearities, intra- and inter-patient variability and specific clinical requirements to be meet. The traditional approach to achieve the desired depth of hypnosis level is based on knowledge and experience of the anesthesiologist. In contrast to a typical automatic control system, their actions are based on events that are related to the effect of the administrated drug. Thus, it is interesting to build a control system that will be able to mimic the behavior of the human way of actuation, simultaneously keeping the advantages of an automatic system.Methods : In this work, an event-based model predictive control system is proposed and analyzed. The nonlinear patient model is used to form the predictor structure and its linear part is exploited to design the predictive controller, resulting in an individualized approach. In such a scenario, the BIS is the controlled variable and the propofol infusion rate is the control variable. The event generator governs the computation of control action applying a dead-band sampling technique. The proposed control architecture has been tested in simulation considering process noise and unmeasurable disturbances. The evaluation has been made for a set of patients using nonlinear pharmacokinetic/pharmacodynamic models allowing realistic tests scenarios, including inter- and intra-patient variability.Results For the considered patients dataset the number of control signal changes has been reduced of about 55% when compared to the classical control system approach and the drug usage has been reduced of about 2%. At the same time the control performance expressed by the integrated absolute error has been degraded of about 11%.Conclusions : The event-based MPC control system meets all the clinical requirements. The robustness analysis also demonstrates that the event-based architecture is able to satisfy the specifications in the presence of significant process noise and modelling errors related to inter- and intra-patient variability, providing a balanced solution between complexity and performance. (c) 2022 Elsevier B.V. All rights reserved