Guo Qing, Sun Ping, Yin Jing-Min, Yu Tian, Jiang Dan
School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu, 611731, China; The State Key Laboratory of Fluid Power Transmission and Control, Zhejiang University, Hangzhou, China.
School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu, 611731, China.
ISA Trans. 2016 May;62:202-14. doi: 10.1016/j.isatra.2016.02.009. Epub 2016 Feb 23.
Some unknown parameter estimation of electro-hydraulic system (EHS) should be considered in hydraulic controller design due to many parameter uncertainties in practice. In this study, a parametric adaptive backstepping control method is proposed to improve the dynamic behavior of EHS under parametric uncertainties and unknown disturbance (i.e., hydraulic parameters and external load). The unknown parameters of EHS model are estimated by the parametric adaptive estimation law. Then the recursive backstepping controller is designed by Lyapunov technique to realize the displacement control of EHS. To avoid explosion of virtual control in traditional backstepping, a decayed memory filter is presented to re-estimate the virtual control and the dynamic external load. The effectiveness of the proposed controller has been demonstrated by comparison with the controller without adaptive and filter estimation. The comparative experimental results in critical working conditions indicate the proposed approach can achieve better dynamic performance on the motion control of Two-DOF robotic arm.
由于实际中存在许多参数不确定性,在液压控制器设计中应考虑电液系统(EHS)的一些未知参数估计。在本研究中,提出了一种参数自适应反步控制方法,以改善参数不确定性和未知干扰(即液压参数和外部负载)下EHS的动态行为。通过参数自适应估计律估计EHS模型的未知参数。然后利用李雅普诺夫技术设计递归反步控制器,实现EHS的位移控制。为避免传统反步中虚拟控制的“微分爆炸”,提出了一种衰减记忆滤波器来重新估计虚拟控制和动态外部负载。通过与无自适应和滤波器估计的控制器进行比较,证明了所提出控制器的有效性。关键工况下的对比实验结果表明,该方法在两自由度机器人手臂的运动控制中能取得更好的动态性能。