This paper proposes an alternative approach based on a fuzzy-interval analysis to assess how dimensional tolerances affect the kinematics of parallel manipulators. The novel contribution of the proposed approach consists of modeling and analyzing the dimensional tolerances as fuzzy-intervals based on fuzzy theory and interval sensitivity methods. The dimensional tolerances are modeled as intervals weighted by the membership function for the proposed fuzzy-interval approach. The proposed fuzzy-interval analysis is used to analyze the positioning error, sensitivity, and design analysis. The proposed fuzzy-interval method was applied using numerical simulations to assess the effect of dimensional tolerances and sensitivity of parallel manipulators. The proposed approach showed as a complementary procedure that can be used in the design phase of parallel manipulators.

Human-centered robotic systems open a large field of new applications, both in industry and service contexts. For their interaction with human beings, up to physical collaboration, they rely heavily on computer vision, and more recently on human motion tracking algorithms, which are examples of intelligent components. The complexity resulting from the variety of human behaviors and the combination of intelligent components with robotic collaborative tasks raises the problem of the performance evaluation of the overall system. To support experiment design for performance evaluation of intelligent collaborative robotic systems, we propose an approach combining real-world human motion recordings with numerical simulations of the dynamics of the robotic system with its controller. In this article, we illustrate this approach on the example of the handover task.

Intelligent collaborative robots or smart cobots can achieve high levels of flexibility by combining the human ability to adapt to new tasks with the performance of automated robots (precision, repeatability, etc.). This is a major innovation for Industry 4.0. Nevertheless, at present, cobots are not widely deployed in industry because they are difficult to evaluate and current standards for them are limited. The evaluation of collaborative tasks is difficult due to their specificities such as the variability of human behavior, artificial intelligence systems (e.g., smart cameras), and advanced control laws. This paper is a short review that aims to identify the methods and material resources needed to address this need for evaluation of intelligent cobots to foster their development and acceptability.

Fed‐batch cultures of Escherichia coli are commonly used for the production of biopharmaceuticals. However, productivity can be adversely affected by the production of acetate inhibiting the cell respiratory capacity. In this study, a nonlinear predictive control is developed based on a process model, and an unscented Kalman filter for estimating the evolution of the glucose and acetate concentrations. The control objective is to regulate the acetate concentration at a low level, so as to maintain the culture close to the edge between the fermentative and respirative regimes. The control strategy is tested in simulation and in lab‐scale experiments, demonstrating its feasibility and performance.

This paper proposes a novel design criterion for manipulators with flexible joints based on elastodynamic performance.Consequently, the elastodynamic performance is assessed; the eigenvalue problem is solved to determine the first natural frequency based on the manipulator's inertia and stiffness matrices.Then, the elastodynamic criterion is evaluated within a region of the Cartesian workspace in order to obtain a global measure.The global elastodynamic performance of a planar serial manipulator and a planar parallel manipulator with flexible joints were obtained.The numerical results show a high dependency of the elastodynamic performance on the configuration and geometric parameters of the manipulator.

This paper considers the control of spacecraft's vibration testing system. This test system is used for the qualification of the dynamic behavior of spacecraft under severe launch environment. The vibration testing system shall cover the launcher's vibration frequency band with respect to the spacecraft limitations (notching around the eigen frequencies). Several control strategies were already studied, leading however to inaccurate tracking performance and important oscillations due to the excitation of the vibrational modes of the spacecraft. An additional difficulty results from the large spectral interval tracking problem, generally beginning at 5 Hz, and continuing up to 150 Hz. In this paper, a switching control strategy is developed based on several robust controllers, where the switch between controllers depends on the reference frequency. The performance of this strategy is assessed by means of a model in- the-loop (MIL) architecture introduced for the virtual shaker testing campaign up to 40 Hz, including Monte-Carlo simulations. Moreover, the campaign's security is assured through guaranteed stability margins of the closed-loop system, limiting the testing campaign to a single run vibration testing instead of the current four-stage one, reducing the testing cost.

Fed-batch cultures of are commonly used for the production of biopharmaceuticals. However, productivity can be adversely affected by the production of acetate inhibiting the cell respiratory capacity. In this study, a nonlinear predictive control is developed based on a process model, and an unscented Kalman filter for estimating the evolution of the glucose and acetate concentrations. The control objective is to regulate the acetate concentration at a low level, so as to maintain the culture close to the edge between the fermentative and respirative regimes. The control strategy is tested in simulation and in lab-scale experiments, demonstrating its feasibility and performance.

SUMMARYThis paper aims at developing a novel method to assess the kinematic reliability of robotic manipulators based on the fuzzy theory. The kinematic reliability quantifies the probability of obtaining positioning errors within acceptable limits. For this purpose, the fuzzy reliability evaluates the effect of the joint clearances on the end-effector position to compute a failure possibility index. As an alternative to the conventional methods reported in the literature, this failure possibility index conveys a novel assessment of the kinematic performance. The numerical results are compared with the well-known probabilistic approach based on the Monte Carlo simulation.

SLM (Selective Laser Melting) is the most widespread additive manufacturing technique of metal part. The desired part is elaborated through local melting of a raw metal powder bed by means of laser. In industrial machines, galvanometer motors achieve the laser beam deflection and focus control tasks. This paper proposes a H-infinity controller synthesis which improves the system accuracy and robustness towards physical features. Compared to a conventional control scheme, results obtained with the H-infinity controller implemented in an open architecture test bench consisting of a 2-axis laser deflection system showed improved accuracy performance while operation rapidity is optimized.

Avoiding acetate accumulation is a major challenge in Escherichia coli fed-batch cultures, since it leads to an inhibition of the cell respiratory capacity. A closed-loop regulation ensuring a low acetate concentration offers a practical solution to maintain the cultures near the optimal operating conditions. In this work, a robust Generic Model Controller (GMC) is designed and implemented to regulate the acetate concentration in E. coli BL21 (DE3) fed-batch cultures. To compensate for model mismatch, disturbances, and measurement noise, a robust design using the LMI formalism is achieved, considering robustness and transient performance requirements. Since the acetate concentration is not available for on-line measurement, an Unscented Kalman Filter (UKF) is also designed and implemented to estimate the acetate concentration based on an on-line biomass measurement. The proposed GMC-UKF strategy is validated through simulation runs and experimental tests at lab-scale. The control strategy shows good performance in regulating the non-measured acetate concentration. The estimation of this latter signal from the biomass measurement is performed accurately by the UKF.

The vibration testing system of a large structure spacecraft presents inaccurate precision tracking and high oscillations in the neighborhood of its vibrational modes, particularly at higher frequencies. In the presence of varying modal parameters of a spacecraft such as the mode frequency and corresponding damping ratio, the performance of the controlled system degrades. Robust high precision tracking control of such systems with varying modal parameters is rarely addressed in the literature. A new closed-loop system architecture is proposed in this paper, based on a feedforward-feedback tracking control strategy involving an $H_{\infty}$ controller. Simulation results show that the new architecture allows precise tracking of a sine sweep acceleration reference signal avoiding vibrations when sweeping through modes. Furthermore, it appears to be highly robust against varying parameters, model uncertainties, as well as the presence of sensor noise. The proposed controller also limits the control effort to avoid the actuator saturation. A minimal order controller is derived which makes it tractable for further industrial implementation.

This paper presents a novel robust optimal design for parallel manipulators to optimize the performance indices subject to the unavoidable effect of the uncertainties. The robust optimization proposed in the present contribution consists of a multi-objective optimization problem that aims at maximizing the performance index and robustness criterion simultaneously. The design variables should be adjusted to minimize the effects of the uncertainties and maximize the performance index. The single-objective optimization problem is also carried out to evaluate the optimal design obtained by using the proposed robust optimization approach. Numerical results illustrate the benefits of the proposed robust optimization applied to the optimal kinematic design of a parallel Cartesian manipulator with clearances and the optimal dynamic design of a Stewart–Gough platform.

This paper presents a novel performance criterion applied to robotic manipulators based on kinematic reliability. The kinetostatic performance criteria have been used to quantify the effect of errors in the manipulators. Nevertheless, design criteria based on the kinematic errors produced by joint clearances have not been established. This contribution proposes a novel performance index based on kinematic reliability concepts that evaluates the effect of the kinematic error produced by clearances over a required workspace. The application of the proposed global kinematic reliability criterion is evaluated for serial and parallel manipulators.

This work proposes a Generic Model Control (GMC) strategy to regulate biomass growth in fed-batch cultures of Escherichia coli BL21(DE3). The control law is established using a previously validated mechanistic model based on the overflow metabolism paradigm. A model reduction is carried out to prevent the controller from relying on kinetics, which may be uncertain. In order to limit the controller to the use of a single measurement, i.e., biomass concentration which is readily available, a Kalman filter is designed to reconstruct the nonmeasurable information from the outlet gas and the remaining stoichiometry. Several numerical simulations are presented to assess the controller robustness with respect to model uncertainty. Experimental validation of the proposed GMC strategy is achieved with a lab-scale bioreactor.

Robust control of a lightly-damped system, such as the mechanical structure of a spacecraft, is a dilemma for control engineers. The shaker’s table used for satellite vibration tests for qualification uses a sine sweep acceleration signal to characterize the satellite’s frequency signature. The current control system presents strong oscillation while sweeping through high-frequency modes. Moreover, the process of fixing control parameters takes a long time leading to an increase in the testing costs. In this paper, a robust controller is proposed, based on an synthesis. This approach reduces the duration of vibration testing, and eliminates the vibration for any sine sweep rate, for all lower and higher modes. Moreover, the proposed controller is able to achieve good stability margins, a certain level of delay margin, and a small tracking error, which complies entirely with the specifications.

This paper presents a novel method to assess the kinematic reliability of parallel manipulators based on the fuzzy theory. For this purpose, the error propagation method permits to compute the position error in the endeffector, taking into account the clearances, and the kinematic constraints of the parallel manipulator. The failure possibility conveys an assessment of the insight kinematic performance that can not be obtained by the conventional methods used in the literature. Numerical results are compared with the well known probabilistic approach based on the Monte Carlo Simulation (MCS).

This paper proposes a new ellipsoid-based guaranteed state estimation approach for linear discrete-time systems with bounded perturbations and bounded measurement noise. This approach is based on the minimization of the radius of the ellipsoidal state estimation set. Firstly, the ellipsoidal state estimation is computed by o -line solving a Linear Matrix Inequality optimization problem. Secondly, a new online method is developed in order to improve the accuracy of the estimation but it leads to an increase of the online computation load. A new scaling technique is proposed to reduce the computation time, while keeping a good accuracy of the state estimation. An illustrative example is analyzed in order to show the advantages of the proposed approach.

Generic model control (GMC), a model-based adaptive control strategy, is applied to a fed-batch high cell density cultivation of Escherichia coli, with biomass production maximization as an objective. A macroscopic model based on the overflow metabolism assumption is used, considering two metabolic pathways (respirative and respiro-fermentative), and consisting of a set of nonlinear differential equations. A linear Kalman filter is designed to reconstruct the assumed unmeasured variables required to calculate the control law. Since the bioprocess model may present uncertainties, the robustness of the approach is tested through a set of Monte-Carlo simulations.

This paper focuses on the design, implementation and experimental validation of a Tube-Based Model Predictive Control (TBMPC) law for the stabilization of the horizontal dynamics of an Unmanned Aerial Vehicle (UAV) quadrotor. These dynamics are modelled by a discrete-time linear system subject to additive disturbance and polytopic constraints, which model is derived through an identification strategy from experimental flight data that is adapted to the subsequent design of invariant sets. The results obtained from a validation flight with the TBMPC law are presented to illustrate the robust state and control input constraints satisfaction.

The aging monitoring of Lithium-ion batteries (LIBs) represents a critical point for electrified vehicle applications. Consumers may expect their vehicle to have a steady autonomy range and available power throughout the lifetime of their cars. Several embedded solutions exist in the literature. In this paper two new approaches are suggested to enrich the existing solutions. To that extent, capacity fading is studied using exchanged energy during charging events. What's more, power fading is assessed using direct current resistance (DCR) and voltage measurement at the beginning of charge events. Both solutions produce reliable state of health measurements SoH with significantly good accuracy.