The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
Adaptive Neural Network Control of a Robotic Manipulator With Time-Varying Output Constraints
Abstract
The control problem of an uncertain n -degrees of freedom robotic manipulator subjected to time-varying output constraints is investigated in this paper. We describe the rigid robotic manipulator system as a multi-input and multi-output nonlinear system. We devise a disturbance observer to estimate the unknown disturbance from humans and environment. To solve the uncertain problem, a neural network which utilizes a radial basis function is used to estimate the unknown dynamics of the robotic manipulator. An asymmetric barrier Lyapunov function is employed in the process of control design to avert the contravention of the time-varying output constraints. Simulation results validate the validity of the presented control scheme.
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Citations
Cites
Barrier Lyapunov Functions for the control of output-constrained nonlinear systems
Tee, K. P., Ge, S. S., & Tay, E. H. (2009) · Automatica · doi:10.1016/j.automatica.2008.11.017 · Cited by 2,912
Self-citationRobust Adaptive Control of Feedback Linearizable MIMO Nonlinear Systems With Prescribed Performance
Bechlioulis, C. P., & Rovithakis, G. A. (2008) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2008.929402 · Cited by 2,756
Sliding-Mode Control for Systems With Mismatched Uncertainties via a Disturbance Observer
Yang, J., Li, S., & Yu, X. (2013) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2012.2183841 · Cited by 1,332
Adaptive Neural Network Control of an Uncertain Robot With Full-State Constraints
He, W., Chen, Y., & Yin, Z. (2016) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2015.2411285 · Cited by 1,273
Self-citationAdaptive Neural Control for Output Feedback Nonlinear Systems Using a Barrier Lyapunov Function
Ren, B., Ge, S. S., Tee, K. P., & Lee, T. H. (2010) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2010.2047115 · Cited by 1,087
Self-citationControl of nonlinear systems with time-varying output constraints
Tee, K. P., Ren, B., & Ge, S. S. (2011) · Automatica · doi:10.1016/j.automatica.2011.08.044 · Cited by 1,059
Self-citationAdaptive tracking control of uncertain MIMO nonlinear systems with input constraints
Chen, M., Ge, S. S., & Ren, B. (2011) · Automatica · doi:10.1016/j.automatica.2011.01.025 · Cited by 1,056
Self-citationBechlioulis, C. P., & Rovithakis, G. A. (2009) · Automatica · doi:10.1016/j.automatica.2008.08.012 · Cited by 1,054
Adaptive Neural Control of Uncertain MIMO Nonlinear Systems
Ge, S. S., & Wang, C. (2004) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2004.826130 · Cited by 971
Self-citationLiu, Y.-J., & Tong, S. (2016) · Automatica · doi:10.1016/j.automatica.2015.10.034 · Cited by 883
Cited by
Full-State Error Constraints Based Dynamic Surface Control of Electro-Hydraulic System
Guo, Q., Li, X., & Jiang, D. (2018) · IEEE Access · doi:10.1109/access.2018.2870956 · Cited by 28
“[48], [49], and He and Dong [50] utilized BLF in nonlinear strict-feedback system, manipulator and rehabilitation robot.”
MethodYang, G., Wang, H., Chen, J., & Zhang, H. (2020) · Nonlinear Dynamics · doi:10.1007/s11071-020-05921-y · Cited by 27
Wang, Y., Zhao, J., Ding, H., & Zhang, H. (2021) · Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science · doi:10.1177/0954406220978263 · Cited by 10
Metadata
- Authors
- He, W., Huang, H., & Ge, S. S.
- Venue
- IEEE Transactions on Cybernetics
- Published
- 2017-10
- Volume
- 47
- Issue
- 10
- Pages
- 3136-3147
- ISSN
- 2168-2267 (ISSN-L)
- 2168-2275
- OpenAlex
- W2740675802
- Cited by
- 361
- References
- 55
- FWCI
- 20.83
- Type
- journal article
- Language
- en
- Open access
- closed
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