具有未建模动力学和输入约束的双单连杆柔性臂的神经网络自适应边界力控制
Neuro-Adaptive Boundary Force Control of Dual One-Link Flexible Arms with Unmodeled Dynamics and Input Constraints
摘要：
本文的主要目的是利用双单连杆柔性机器人完成安全抓取任务。为了设计一个无力传感器的力控制器，直接力控制问题被简化为普通的运动控制问题，在某种程度上，通过满足新的控制目标，建立抓取任务。之后，第一次在双单连杆柔性机械臂领域，智能控制方法结合鲁棒控制方法，努力：i）完成运动控制目标，ii）处理系统中的不确定性，iii）考虑未知的，混合输入约束，导致NABFC（神经自适应边界力控制）。此外，为了处理未知的模型不确定性以及未知的输入饱和和死区，径向基函数神经网络（RBFNN）。以同样的方式，利用自适应控制来估计未知参数。通过利用李雅普诺夫直接方法，适当的李雅普诺夫泛函和能量乘子方法被定义来表达著名的强稳定性过程，这补偿了以前的工作中提出的复杂的稳定性过程。在所设计的控制器的存在下，所提出的稳定性程序导致系统的一致最终有界（UUB）稳定。最后，为了与其他控制器进行比较，通过数值分析验证了所设计控制器的优良性能和稳定性分析结果的正确性。
英文摘要：
The primary purpose of this article is to accomplish safe grasping task by means of dual one-link flexible manipulators. In order to design a force-sensor-less force control, the direct force control problem is reduced to common motion control problem, in a way that by satisfying new control objectives the grasping task is established. Afterwards, for the first time in the field of dual one-link flexible manipulators, intelligent control methods are combined with robust control approaches in an effort to; i) accomplish motion control objectives, ii) handle uncertainties in the system, and iii) consider unknown, mixed input constraints, resulting in NABFC (Neuro-Adaptive Boundary Force Control). Moreover, to deal with unknown model uncertainties as well as unknown input saturation and dead zones, Radial Basic Function Neural-Networks (RBFNNs) are used. In the same way, adaptive control is utilized to estimate unknown parameters. By exploiting Lyapunov's direct method, proper Lyapunov functional and Energy multiplier method are defined to express well-known yet strong stability procedure, which compensates a complex stability procedure proposed in the previous works. In the presence of the designed controller, the presented stability procedure resulted in a uniform ultimate boundedness (UUB) stability for the system. Finally, for comparison aim between the designed controller with other controllers, numerical analysis is used to demonstrate both the excellent performance of the proposed controller and the correctness of the stability analysis outcomes.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
