Adaptive Control of Space Robot Despinning Tumbling Target Using Flexible Brushes

A flexible brush mechanism is designed and mounted at the end of a seven-degree-of-freedom robotic arm to despin a tumbling target. The dynamics model of the flexible brush is established using the absolute nodal coordinate method (ANCF), and its contact collision with the solar wing of the tumbling target is analysed. The H ∞ optimal control is proposed for a seven-degree-of-freedom robotic arm during despinning of a tumbling target while ensuring the global robustness and stability. Simulations verify that the despinning strategy can successfully eliminate the rotation speed and is feasible and effective.

Robustness of Reinforced Concrete Frames against Blast-Induced Progressive Collapse

A quantitative procedure for the robustness and progressive collapse assessment of reinforced concrete (RC) frames under blast load scenarios is presented. This procedure is supported by multilevel numerical models, including nonlinear numerical analyses of the structural response of both local (i.e., response of the single structural element to the blast load) and global levels (i.e., response of the structural system to the blast-induced damage). Furthermore, the procedure is applied to a 2D RC frame structure. The novelty of the proposed procedure is that the global robustness is evaluated by the so-called “damage-presumption approach” where the considered damages are defined both in typology and extension depending on the blast scenario occurring at the local level. The dedicated local response analysis of a specified blast scenario leads to the proper definition of the so-called “blast-scenario dependent robustness curves”.

Point set registration for assembly feature pose estimation using simulated annealing nested Gauss-Newton optimization

Purpose This paper aims to propose a fast and robust 3D point set registration method for pose estimation of assembly features with few distinctive local features in the manufacturing process. Design/methodology/approach The distance between the two 3D objects is analytically approximated by the implicit representation of the target model. Specifically, the implicit B-spline surface is adopted as an interface to derive the distance metric. With the distance metric, the point set registration problem is formulated into an unconstrained nonlinear least-squares optimization problem. Simulated annealing nested Gauss-Newton method is designed to solve the non-convex problem. This integration of gradient-based optimization and heuristic searching strategy guarantees both global robustness and sufficient efficiency. Findings The proposed method improves the registration efficiency while maintaining high accuracy compared with several commonly used approaches. Convergence can be guaranteed even with critical initial poses or in partial overlapping conditions. The multiple flanges pose estimation experiment validates the effectiveness of the proposed method in real-world applications. Originality/value The proposed registration method is much more efficient because no feature estimation or point-wise correspondences update are performed. At each iteration of the Gauss–Newton optimization, the poses are updated in a singularity-free format without taking the derivatives of a bunch of scalar trigonometric functions. The advantage of the simulated annealing searching strategy is combined to improve global robustness. The implementation is relatively straightforward, which can be easily integrated to realize automatic pose estimation to guide the assembly process.

PMLSM Nonlinear Integral Sliding Mode Control Based on Gain Time- Varying Reaching Law

Background: The permanent magnet synchronous linear motor is a strongly coupled, nonlinear system. It has been applied in many fields, especially in the field of machining lathes and rail transportation. In order to ensure the permanent magnet synchronous linear motor has good dynamic performance and robustness, sliding mode control is gradually applied to the control system of permanent magnet synchronous linear motor. However, in the traditional sliding mode control, the convergence speed is slow, and the robust performance is poor when the sliding surface is not reached. Objective: The main purpose of this paper is to improve the dynamic performance and robustness of the permanent magnet synchronous linear motor during the process of approaching the sliding surface. Methods: Firstly, the type of nonlinear curve with "small error reduction, large error saturation" is introduced to design a nonlinear integral speed controller with global robustness. Secondly, the gain rate time-varying reaching law is introduced to reduce "chattering". Finally, using a symbolic tangent function instead of a sign function in designing a sliding mode observer reduces fluctuations in load observations. Results: Finally, the correctness and effectiveness of the control method are proved by simulation. Conclusion: The results of the simulation show that the nonlinear integral sliding mode controller based on gain time-varying reaching law is shown to have good global robustness and dynamic performance.

Sliding mode prediction fault-tolerant control method for multi-delay uncertain discrete system with sensor fault

In this paper, we design a novel sliding mode prediction fault-tolerant control algorithm for multi-delays discrete uncertain systems with sensor fault. The global sliding surface is designed to replace the traditional linear sliding surface as a predictive model to ensure the global robustness of the system. For sensor fault and sliding mode buffeting, a power-dependent function reference trajectory with fault compensation is designed to attenuate chattering and achieve better stability. In the process of rolling optimization, an improved whale optimization algorithm is developed. On the premise of obtaining good convergence speed and accuracy, the optimization process can avoid falling into the local minimum value and solve the problem of premature convergence. Finally, the comparison experiments on the quad-rotor simulation platform prove the rationality and superiority of the algorithm.