2020
DOI: 10.1016/j.ifacol.2020.12.1182
|View full text |Cite
|
Sign up to set email alerts
|

Dynamic output feedback sliding mode control for non-minimum phase systems with application to an inverted pendulum

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1

Citation Types

0
3
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
4
1

Relationship

0
5

Authors

Journals

citations
Cited by 6 publications
(3 citation statements)
references
References 13 publications
0
3
0
Order By: Relevance
“…A different approach is required to formalize the control law design for either the nonminimum phase or unstable system. Some ideas, such as in previous works, [31][32][33][34] can be utilized to compensate for the systems' nonminimum phase or unstable behavior. However, a thorough analysis is still required to extend the SMRC design to properly handle the above systems.…”
Section: Controller Designmentioning
confidence: 99%
“…A different approach is required to formalize the control law design for either the nonminimum phase or unstable system. Some ideas, such as in previous works, [31][32][33][34] can be utilized to compensate for the systems' nonminimum phase or unstable behavior. However, a thorough analysis is still required to extend the SMRC design to properly handle the above systems.…”
Section: Controller Designmentioning
confidence: 99%
“…There are some difficulties in the design and implementation of OFSMC, but it has excellent performance in terms of control effect and robustness. Existing OFSMC methods mainly include the following [15,16]: the first is the conventional OFSMC. The conventional OFSMC method estimates the system state by introducing a state observer and then designs according to the error between the estimated and expected states.…”
Section: Introductionmentioning
confidence: 99%
“…Thus, considerable attention has been dedicated, to stability analysis and control synthesis for NMPS. 14 Furthermore, for a broad class of systems, SMC is particularly appealing due to its ability to deal with nonlinearities, parameter uncertainties and disturbances. 15,16 The SMC is mainly relevant to state-space representation.…”
Section: Introductionmentioning
confidence: 99%