Real-time robot manipulator tracking control as multilayered time-varying problem

Li, Jian; Zhu, Xinhui; Shi, Yang; Wang, Jing; Guo, Huaping

doi:10.1016/j.apm.2021.03.021

Cited by 8 publications

(2 citation statements)

References 30 publications

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“…Classical time-varying problems are single-layered, which have relatively weak ability to describe practical problems [36][37][38][39][40]. Recently, by introducing multilayers in time-varying problems, multilayered time-varying problems are investigated [41][42][43][44][45]. For example, in [37], multilayered time-varying linear systems including equality and inequality layers were investigated by ZND method.…”

Section: Introductionmentioning

confidence: 99%

Noise-Tolerant Zeroing Neural Dynamics for Solving Hybrid Multilayered Time-Varying Linear Equation System

Shi

Sun

et al. 2022

Security and Communication Networks

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Resource allocation problem in a wireless sensor network can be formulated as time-varying optimization, which can be further converted as time-varying linear equation system (TVLES). Hybrid multilayered time-varying linear equation system (HMTVLES) involving hybrid multilayers and time-variation characteristic is a complicated and challenging problem. Recently it has been solved by zeroing neural dynamics (ZND) method under ideal conditions, i.e., without noises. However, noises are ubiquitous, immanent and unavoidable in real-time systems. In this work, we propose a noise-tolerant zeroing neural dynamics (NTZND) model for solving HMTVLES. It can deal with different kinds of noises such as constant noise, linear-increasing noise, and random noise. Theoretical analyses guarantee the precision of NTZND model in the presence of different kinds of noises. In addition, a general NTZND model is proposed based on general activation function. Besides, classical ZND method and gradient neural dynamics (GND) method are also investigated and compared. Numerical experimental results are presented to verify the theoretical results of proposed models.

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Section: Introductionmentioning

confidence: 99%

Noise-Tolerant Zeroing Neural Dynamics for Solving Hybrid Multilayered Time-Varying Linear Equation System

Shi

Sun

et al. 2022

Security and Communication Networks

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“…Considering the physical constraints of industrial robots are less studied. In [45], the motion process of an industrial robot is modelled as a multilayer time-varying problem in order to solve the problem of joint angle constraints in the control process [46]. proposed a physical limit constrained minimum velocity parametric coordination scheme to solve the constraints of a wheeled robot.…”

Section: Introductionmentioning

confidence: 99%

Towards non-linearly activated ZNN model for constrained manipulator trajectory tracking

Lan

Liu²

2023

Front. Phys.

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As a powerful method for time-varying problems solving, the zeroing neural network (ZNN) is widely applied in many practical applications that can be modeled as time-varying linear matrix equations (TVLME). Generally, existing ZNN models solve these TVLME problems in the ideal no noise situation without inequality constraints, but the TVLME with noises and inequality constraints are rarely considered. Therefore, a non-linear activation function is designed, and based on the non-linear activation function, a non-linearly activated ZNN (NAZNN) model is proposed for solving constrained TVLME (CTVLME) problems. The convergence and robustness of the proposed NAZNN model are verified theoretically, and simulation results further demonstrate the effectiveness and superiority of the NAZNN model in dealing with CTVLME and the constrained robot manipulator trajectory tracking problems. In addition, the wheeled robot trajectory tracking fault problems with physical constraints are also analyzed theoretically, and the proposed NAZNN model is also applied to the manipulator trajectory tracking fault problem, and the experimental results prove that the NAZNN model also deal with the manipulator trajectory tracking fault problem effectively.

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Observer-based event-triggered sliding mode tracking control for uncertain robotic manipulator systems

Guo

Sun

et al. 2023

J Braz. Soc. Mech. Sci. Eng.

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Real-time robot manipulator tracking control as multilayered time-varying problem

Cited by 8 publications

References 30 publications

Noise-Tolerant Zeroing Neural Dynamics for Solving Hybrid Multilayered Time-Varying Linear Equation System

Noise-Tolerant Zeroing Neural Dynamics for Solving Hybrid Multilayered Time-Varying Linear Equation System

Towards non-linearly activated ZNN model for constrained manipulator trajectory tracking

Observer-based event-triggered sliding mode tracking control for uncertain robotic manipulator systems

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