Robust approximate constraint‐following control design for typical manipulator systems

Abstract

In this paper, the constraint equation is written into the second‐order form, and the additional generalized constraint binding force is added to the unconstrained system from the constraint equation to obtain the dynamic equation. Based on the dynamic equation, we model performance requirements as servo constraints by using the robust approximate constraint‐following servo control. In other words, the constraints are generated from the servo control which makes the system follow the constraints approximately. Finally, for verifying the effectiveness of the controller, we apply it into a two‐degree‐of‐freedom manipulator system.

Adaptive neural network control of multiple‐sectioned flexible riser with time‐varying output constraint and input nonlinearity

“…The physical characteristics of flexible structure, such as light weight and high efficiency, make it extremely important in industrial production. It is widely used in manipulator [1], spacecraft [2], riser [3], belt [4], string [5], and so forth. As a device that connects the subsea oil well and the floating platform on the sea surface, the flexible riser plays a vital role in the oil and gas gathering and transportation link.…”