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In recent decades, flexible manipulators have been studied by many researchers from robotics, solid mechanics, and control fields. Flexible manipulators have many advantages, including low weight because of the slenderness of the links of the robot. Although the original objective was to take advantages of the slenderness or flexibility in real robots, the challenging dynamics of the systems intrigued interests to employ an experimental flexible manipulator as a test bed to evaluate different modelling or control methods. With such a vast and various literatures, a review is indispensable for researchers who want to adapt their interests with the area. Some valuable review articles have been published, referencing numerous articles on single-link or multi-link flexible arms. This article pays an inclusive focus on trends of the research on modelling and control of multi-link flexible-link manipulators. The scope of this review article is particularly on two-link flexible manipulators, relevant models presented for closed-loop applications, and model-based control. Recent and historical contributions in the modelling and control of flexible-link manipulators are presented and discussed. As regular industrial manipulators normally have multiple links with two long links, that is, upper arm and forearm, this review can introduce advances in considering elasticity effects to robotic researchers.

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In tissue engineering, 3D printing is an important tool that uses biocompatible materials, cells, and supporting components to fabricate complex 3D printed constructs. This review focuses on the cytocompatibility characteristics of 3D printed constructs, made from different synthetic and natural materials. From the overview of this article, inkjet and extrusion-based 3D printing are widely used methods for fabricating 3D printed scaffolds for tissue engineering. This review highlights that scaffold prepared by both inkjet and extrusion-based 3D printing techniques showed significant impact on cell adherence, proliferation, and differentiation as evidenced by in vitro and in vivo studies. 3D printed constructs with growth factors (FGF-2, TGF-β1, or FGF-2/TGF-β1) enhance extracellular matrix (ECM), collagen I content, and high glycosaminoglycan (GAG) content for cell growth and bone formation. Similarly, the utilization of 3D printing in other tissue engineering applications cannot be belittled. In conclusion, it would be interesting to combine different 3D printing techniques to fabricate future 3D printed constructs for several tissue engineering applications.

Due to the continued evolution of the SARS-CoV-2 pandemic, researchers worldwide are working to mitigate, suppress its spread, and better understand it by deploying digital signal processing ( DSP ) and machine learning approaches. This study presents an alignment-free approach to classify the SARS-CoV-2 using complementary DNA , which is DNA synthesized from the single-stranded RNA virus. Herein, a total of 1582 samples, with different lengths of genome sequences from different regions, were collected from various data sources and divided into a SARS-CoV-2 and a non-SARS-CoV-2 group. We extracted eight biomarkers based on three-base periodicity, using DSP techniques, and ranked those based on a filter-based feature selection. The ranked biomarkers were fed into k-nearest neighbor, support vector machines, decision trees, and random forest classifiers for the classification of SARS-CoV-2 from other coronaviruses. The training dataset was used to test the performance of the classifiers based on accuracy and F-measure via 10-fold cross-validation. Kappa-scores were estimated to check the influence of unbalanced data. Further, 10x10 cross-validation paired t -test was utilized to test the best model with unseen data. Random forest was elected as the best model, differentiating the SARS-CoV-2 coronavirus from other coronaviruses and a control a group with an accuracy of 97.4%, sensitivity of 96.2%, and specificity of 98.2%, when tested with unseen samples. Moreover, the proposed algorithm was computationally efficient, taking only 0.31 seconds to compute the genome biomarkers, outperforming previous studies.

Purpose This study presents a method for simultaneous motion and vibration control of light-weight slender robotic arms, known as flexible manipulators. In this paper, a new control algorithm is proposed for a two-link manipulator with elastic links. Design/methodology/approach The controller includes a MIMO H∞ Loop-Shaping Design (H∞LSD) as the feedback controller, and a command pre-shaping filter as the feed-forward controller. The conventional inputs and outputs of a typical two-link manipulator , that consists of the torques applied by the actuators at the joints, and the joint angles are chosen for the feedback control. Findings It is shown that by selecting a proper desired loop shape, the H∞LSD is able to control the joint angles of the manipulator, and simultaneously, suppress vibrations of the system so that the high frequency chatter due to the structural vibration modes does not appear at the outputs. Then it is shown that when the H∞LSD is equipped with a command pre-shaping filter, more efficient suppression of the chatter at the tip of the manipulator is achieved. The capability and effectiveness of the proposed control strategy in driving and stabilizing the manipulator to desired positions and simultaneously suppressing structural vibrations is shown by the simulation of the flexible manipulator in rest-to-rest maneuvers. Practical implications Flexible Manipulator, Space Manipulators Originality/value A robust MIMO controller is proposed for simultaneous motion and vibration control of flexible manipulator.

This paper demonstrates the effectiveness of applying constraints in a controller algorithm as a strategy to enhance the pneumatic actuator system’s positioning performance. The aim of the present study is to reduce the overshoot in the pneumatic actuator positioning system’s response. An autoregressive with exogenous input (ARX) model structure has been used to model the pneumatic system, while a model predictive control (MPC) has been employed as a control strategy. The input constraint has been applied to the control signals (on/off valves signals) to ensure accurate position tracking. Results show that the strategy with constraint effectively reduced overshoot by more than 99.0837 % and 97.0596 % in simulation and real-time experiments, respectively. Moreover, the performance of the proposed strategy in controlling the pneumatic positioning system is considered good enough under various loads. The proposed strategy can be applied in any industry that used pneumatic actuator in their applications, especially in industries that involved with position control such as in manufacturing, automation and robotics. The strategy proved to be capable of controlling the pneumatic system better, especially in the real-time environment.