An iterative convergence control method (ICCM) based on the support vector regression (SVR) is proposed to realize the position–posture control of the planar four-link underactuated manipulator with a passive second link. Firstly, the particle swarm optimization (PSO) algorithm is used to obtain the target angles of all links according to the position–posture control objective. Then, two prediction models for the coupling relationship between the first link and the passive link, and the third link and the passive link are established based on the SVR, whose optimal parameters are selected by the chaos particle swarm optimization (CPSO) algorithm. By repeatedly controlling the first link or the third link to rotate an angle which is calculated by the trained SVR model, the passive link gradually converges to its target angle after several iterations. Next, the active links are controlled to rotate to their target angles with low speeds, and the passive link does not rotate due to friction. Finally, the experimental results verify the effectiveness and feasibility of the proposed method.

提出了一种基于支持向量回归（SVR）的迭代收敛控制方法（ICCM），以实现具有被动第二连杆的平面四连杆欠驱动机械臂的位置姿态控制。首先，使用粒子群算法（PSO）根据位置-姿态控制目标获得所有链路的目标角度。然后，基于SVR建立了第一链路与无源链路，第三链路与无源链路之间耦合关系的两个预测模型，并通过混沌粒子群优化算法选择了最优参数。通过反复控制第一连杆或第三连杆旋转由训练有素的SVR模型计算出的角度，无源链接经过几次迭代后逐渐收敛到其目标角度。接下来，控制主动连杆以低速旋转至其目标角度，而被动连杆则不会由于摩擦而旋转。最后，实验结果验证了该方法的有效性和可行性。