The Libration Stabilization Of A Partial Space Elevator System Using Analytical Reel Rate Control

This paper investigates the libration stabilization control of a partial space elevator system with a moving climber in circular orbits. The system is described by a modified two-piece dumbbell model. The model consists of one main satellite, one climber and one end-body connected by two straight, massless and inextensible tethers. The climber and the end body can move along the tether. The libration motion and the tether reeling motion are separated. And a reel rate function is obtained by analyzing the equilibrium state of the libration motion, based on the which an analytical control scheme is designed. Using the sliding mode control law, the proposed control scheme can be implemented effectively and robustly. The results of numerical simulations show that the proposed control scheme has good performance in keeping the stable of the climber’s transfer of a partial space elevator satellite system. Furthermore, the proposed libration suppression control can be realized by using tension control only

A framework for multi-objective optimisation based on a new self-adaptive particle swarm optimisation algorithm

This paper develops a particle swarm optimisation (PSO) based framework for multi-objective optimisation (MOO). As a part of development, a new PSO method, named self-adaptive PSO (SAPSO), is first proposed. Since the convergence of SAPSO determines the quality of the obtained Pareto front, this paper analytically investigates the convergence of SAPSO and provides a parameter selection principle that guarantees the convergence. Leveraging the proposed SAPSO, this paper then designs a SAPSO-based MOO framework, named SAMOPSO. To gain a well-distributed Pareto front, we also design an external repository that keeps the non-dominated solutions. Next, a circular sorting method, which is integrated with the elitist-preserving approach, is designed to update the external repository in the developed MOO framework. The performance of the SAMOPSO framework is validated through 12 benchmark test functions and a real-word MOO problem. For rigorous validation, the performance of the proposed framework is compared with those of four well-known MOO algorithms. The simulation results confirm that the proposed SAMOPSO outperforms its contenders with respect to the quality of the Pareto front over the majority of the studied cases. The non-parametric comparison results reveal that the proposed method is significantly better than the four algorithms compared at the confidence level of 90% over the 12 test functions

A Framework for Constrained Optimization Problems Based on a Modified Particle Swarm Optimization

This paper develops a particle swarm optimization (PSO) based framework for constrained optimization problems (COPs). Aiming at enhancing the performance of PSO, a modified PSO algorithm, named SASPSO 2011, is proposed by adding a newly developed self-adaptive strategy to the standard particle swarm optimization 2011 (SPSO 2011) algorithm. Since the convergence of PSO is of great importance and significantly influences the performance of PSO, this paper first theoretically investigates the convergence of SASPSO 2011. Then, a parameter selection principle guaranteeing the convergence of SASPSO 2011 is provided. Subsequently, a SASPSO 2011-based framework is established to solve COPs. Attempting to increase the diversity of solutions and decrease optimization difficulties, the adaptive relaxation method, which is combined with the feasibility-based rule, is applied to handle constraints of COPs and evaluate candidate solutions in the developed framework. Finally, the proposed method is verified through 4 benchmark test functions and 2 real-world engineering problems against six PSO variants and some well-known methods proposed in the literature. Simulation results confirm that the proposed method is highly competitive in terms of the solution quality and can be considered as a vital alternative to solve COPs

Nonlinear Model Predictive Control for the Stabilization of a Wheeled Unmanned Aerial Vehicle on a Pipe

This letter addresses the task of stabilizing a wheeled unmanned aerial vehicle on a pipe, which is an emerging applica- tion in oil and gas facilities for nondestructive measurements. After the derivation of the dynamic model of the system, a discrete-time nonlinear model predictive controller is designed over a finite horizon. The analysis of the asymptotic stability of the designed controller is carried out. Numerical tests show the performance and the robustness of the proposed solution

Non-inverse kinematics of free-floating space robot based on motion planning of sampling

Motion planning is one of the fundamental technologies for robots to achieve autonomy. Free-floating space robots composed manipulators and base satellite that do not actively control its position and attitude has nonholonomic characteristics, and there is a first-order differential relationship between its joint angle and the base attitude. In addition, the planning framework which first converts the goal end-effector pose to its corresponding target configuration, and then plan the trajectory from the initial configuration to the goal configuration still has the following problems: the goal configuration and the initial configuration may not be in the same connected domain. Based on the RRT framework, the motion planning of a free-floating space robot from the initial configuration to the goal end-effector pose is studied. In the algorithm design, in order to deal with the differential constraints of the free-floating space robot, and the requirement that the attitude disturbance of its base cannot exceed its limit, a control-based local planner for random configuration guiding growth of the tree and a control-based local planner for goal end-effector pose guiding growth of the tree that can adjust the attitude of the base when necessary are proposed. The former can ensure the effective exploration of the configuration space, and the latter can avoid the occurrence of singularity while ensuring that the algorithm converges quickly and the base attitude disturbance meets the constraints. The present algorithm does not need to solve the inverse kinematics, can successfully complete the planning task, and ensure that the base attitude disturbance meets the requirements. The simulation verifies the effectiveness of the algorithm

Multitask-Based Trajectory Planning for Redundant Space Robotics Using Improved Genetic Algorithm

This work addresses the multitask-based trajectory-planning problem (MTTP) for space robotics, which is an emerging application of successively executing tasks in assembly of the International Space Station. The MTTP is transformed into a parameter-optimization problem, where piecewise continuous-sine functions are employed to depict the joint trajectories. An improved genetic algorithm (IGA) is developed to optimize the unknown parameters. In the IGA, each chromosome consists of three parts, namely the waypoint sequence, the sequence of the joint configurations, and a special value for the depiction of the joint trajectories. Numerical simulations, including comparisons with two other approaches, are developed to test IGA validity

Rotation–translation coupling analysis on perturbed spacecraft relative translational motion

This paper explores an accurate and complete spacecraft six-degree-of-freedom coupled relative motion model using the dual quaternion representation. Based on this technique, we build a scheme capable of describing both kinematic and dynamic coupling effects on the spacecraft relative translational motion through a further combination with the chaser’s precise absolute translational and rotational dynamics. This new model generalizes the existing nonlinear spacecraft relative translational model to include both the kinematic coupling effect due to the displacements of selected feature points relative to the spacecraft centers of mass and the dynamic coupling effect induced by the gravity gradient torque and the orbital perturbations. Several numerical simulations are implemented to validate the feasibility of the proposed model, for analyzing both the kinematic and dynamic coupling effects, on the relative translational motion of two arbitrary feature points in either Keplerian or J2 perturbed orbits. The results are further compared against the J2 perturbation effect.J.C. thanks the support of the Chinese Scholarship Council. This study was funded by the Ministerio de Economia y Competividad (Grant Numbers PGC2018-100928-B-100 and MTM2016-80117-P), the Catalan government (Grant Numbers 2017SGR-1049 and 2017SGR-1374) and the National Natural Science Foundation of China (Grant Number 11572248).Peer reviewe

miR-145 and miR-497 suppress TGF-β-induced epithelial–mesenchymal transition of non-small cell lung cancer by targeting MTDH

Abstract Background MicroRNAs (miRNAs) have been reported to play crucial roles in multiple cancers including non-small cell lung cancer (NSCLC). Here, we investigated the role of miR-145 and miR-497 in TGF-β-induced epithelial–mesenchymal transition (EMT) process of NSCLC. Methods We performed quantitative real time PCR (qRT-PCR) to detect the expression level of miR-145 and miR-497 in NSCLC cell lines. Then in the presence/absence of TGF-β, we transfected miRNA mimics or inhibitor into A549 and H1299 cells and investigated the role of miR-145 and miR-497 in cell migration and invasion using transwell and wound-healing assay. The regulation role of miR-145 and miR-497 on Metadherin (MTDH) was determined by luciferase assay. The expression level of MTDH and EMT markers E-cadherin and vimentin were detected on mRNA and protein level. Results In our study, our results showed that miR-145 and miR-497 were downregulated in NSCLC cell lines. Overexpression of miR-145 and miR-497 inhibited TGF-β-induced EMT and suppressed cancer cell migration and invasion, while the opposite results were observed in cells transfected with miR-145 or miR-497 inhibitor. Moreover, the luciferase assay confirmed that miR-145 and miR-497 attenuated MTDH expression by directly binding 3′-UTR of MTDH mRNA and exert the tumor-suppression role. Conclusions Overall, we demonstrated that miR-145 and miR-497 functioned as EMT-suppressor in NSCLC by targeting MTDH, provided new evidence that miR-145 and miR-497 as potential therapeutic targets