2020
DOI: 10.1177/0142331220976114
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Robust sliding model control-based adaptive tracker for a class of nonlinear systems with input nonlinearities and uncertainties

Abstract: A robust adaptive tracker is newly proposed for a class of nonlinear systems with input nonlinearities and uncertainties. Because the upper bounds of input nonlinearities and uncertainties are difficult to be acquired, the adaptive control integrated with sliding mode control (SMC) and radial basis function neural network (RBFNN) are utilized to cope with these undesired problems and effectively complete the robust tracker design. The main contributions are concluded as follows: (1) new sufficient conditions a… Show more

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Cited by 2 publications
(5 citation statements)
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“…11, it can be observed that ASTC has better tracking effect when compared with the proposed tracking controller in ref. [36]. Furthermore, ASTC is able to eliminate the undesired chattering effectively with less control inputs in Fig.…”
Section: Example 3: System With Complex Nonlinearitymentioning
confidence: 95%
See 4 more Smart Citations
“…11, it can be observed that ASTC has better tracking effect when compared with the proposed tracking controller in ref. [36]. Furthermore, ASTC is able to eliminate the undesired chattering effectively with less control inputs in Fig.…”
Section: Example 3: System With Complex Nonlinearitymentioning
confidence: 95%
“…• Case 2: Single-link robot system In this case, a single-link robotic arm in ref. [36] is utilized to verify the effectiveness and validity of ASTC. For ease of comparison studies, both the desired joint trajectory and the complex actuator nonlinearity existing in the robot in ref.…”
Section: Example 3: System With Complex Nonlinearitymentioning
confidence: 99%
See 3 more Smart Citations