Continuous Control Strategy of Planar 3-Linkage Underactuated Manipulator Based on Broad Neural Network

For the position control of a planar 3-linkage underactuated manipulator (PTUM) with a passive first linkage, a continuous control strategy is developed in this paper. In particular, a broad neural network (BNN)-based model is first established to accurately describe the motion coupling relationship between the passive linkage and the second linkage. Based on this model, by using the particle swarm optimization algorithm, the target angles of all linkages are calculated combining the start states of all linkages and the target position of the PTUM. Then, the target angles of the active linkages are directly achieved by their respective actuators, and that of the passive linkage is also achieved by the rotation of the second linkage. By carrying out several experiments, the effectiveness of the above strategy is verified.

Optimal Reference Trajectory for a Type Xn-1Rp Underactuated Manipulator

The aim of the present research is to find an optimal reference trajectory for an underactuated manipulator of type Xn-1Rp, where X is any type of joints and R is the last rotary joint, for n≥3. It is worth noting that in the case of absence of control of fully actuated manipulator, some second-order nonholonomic constraints may appear; these are known as acceleration constraints. The second-order nonholonomic constraint is a non-integrable differential equation. For this purpose, it was decided to combine two methods. The first one provides the open-loop control of the manipulator whatever the motion time is; in practice, the motion time should be minimal under the given geometric, technological, and dynamic constraints. To address this issue, a second method, based on the offline optimization approach, was used to achieve the time-optimal motion. It was revealed that the above combination gives an optimal control trajectory for an underactuated manipulator in which a reference trajectory can be utilized.