Model-based, Distributed, and Cooperative Control of Planar Serial-link Manipulators

Soumya, S.; Guruprasad, K. R.

doi:10.1007/s12555-020-0031-7

Cited by 4 publications

(2 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, the control of a space robot after capturing a non-cooperative target is a challenging task as the dynamic model of the combination is always unknown [10,11]. In this case, approximation has been employed in manipulator tracking controllers, such as adaptive control and neural network control [12,13]. But these approximation methods require to guarantee beforehand that the system state is restricted to the compact set where the approximation capability hold, which is a tedious task because the usual means is regulating the control parameters and initial parameter estimates to attain the goal.…”

Section: Introductionmentioning

confidence: 99%

“…[19] and some advanced methods such as sliding mode control and fuzzy neural network control are introduced Refs. [12,20,21], whereas they all require a prior knowledge of the dynamic model. Furthermore, currently, robotic systems adopt lightweight and flexible materials, embedded sensors and actuators, which make the nonlinear inertia and couplings among the joints become more and more dominant and influential in system performance [22].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Nonlinear Tracking Differentiator Based Prescribed Performance Control for Space Manipulator

Fan

Jing

Bernelli‐Zazzera

2023

Int. J. Control Autom. Syst.

View full text Add to dashboard Cite

A low-complexity prescribed performance controller is proposed for motion tracking control of a space manipulator in this paper. First of all, a prescribed-time prescribed performance function is designed. Based on the function, the proposed controller is capable of guaranteeing the system transient and steady-state control performances satisfy the prescribed boundary constraints. Moreover, all tracking errors converge to stability domains before the user-defined settling time. A nonlinear tracking differentiator based on a hyperbolic sine function is adopted to estimate the derivatives of joint angles and reconstruct the angular velocity for the controller, which lowers hardware requirements for the controlled system to a certain extent. Without any time-consuming operations and model information, the proposed control scheme has a superiority in low computation complexity and robustness against model uncertainties. With the Lyapunov theory, the prescribed-time stability within prescribed performances of the closed-loop has been rigorously proven. Numerical simulation and the comparison with the traditional prescribed performance control demonstrates the effectiveness and superior performances of the proposed control scheme.

show abstract