2023
DOI: 10.1007/s11071-023-08277-1
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Backstepping control for the optoelectronic stabilized platform based on adaptive fuzzy logic system and nonlinear disturbance observer

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Cited by 9 publications
(7 citation statements)
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“…Following the NDO form from Zhang et al, 27 Dutta and Kumar, 28 we have leftdˆ=z+p(x),ż=L(x)z+L(x)[p(x)f(x)g(x)u], $\left\{\begin{array}{c}\hat{d}=z+p({\rm{x}}),\\ \dot{z}=L({\rm{x}})z+L({\rm{x}})[-p({\rm{x}})-f({\rm{x}})-g({\rm{x}})u],\end{array}\right.$where dˆ $\hat{d}$ is the observer estimate value of d , z is the internal state of the observer, p ( x ) is the nonlinear function to be designed, and L ( x ) is the gain of the nonlinear observer satisfying L(x)trueẋ2=dp(x)dt. $L({\rm{x}})\cdot {\dot{x}}_{2}=\frac{dp({\rm{x}})}{dt}.$…”
Section: Design Of the Nonlinear Disturbance Observermentioning
confidence: 99%
“…Following the NDO form from Zhang et al, 27 Dutta and Kumar, 28 we have leftdˆ=z+p(x),ż=L(x)z+L(x)[p(x)f(x)g(x)u], $\left\{\begin{array}{c}\hat{d}=z+p({\rm{x}}),\\ \dot{z}=L({\rm{x}})z+L({\rm{x}})[-p({\rm{x}})-f({\rm{x}})-g({\rm{x}})u],\end{array}\right.$where dˆ $\hat{d}$ is the observer estimate value of d , z is the internal state of the observer, p ( x ) is the nonlinear function to be designed, and L ( x ) is the gain of the nonlinear observer satisfying L(x)trueẋ2=dp(x)dt. $L({\rm{x}})\cdot {\dot{x}}_{2}=\frac{dp({\rm{x}})}{dt}.$…”
Section: Design Of the Nonlinear Disturbance Observermentioning
confidence: 99%
“…The disturbance in this paper is an unknown time-varying function, which is more general than the disturbance in [15][16][17]26]. Compared with [28][29][30], this paper designs an auxiliary system for the compensation term and independently proves the stability of the disturbance observer.…”
Section: Fuzzy Compensation Disturbance Observermentioning
confidence: 99%
“…In [19,20], the authors used the parameter estimation methods to estimate external disturbances and enhance the disturbance attenuation ability of controllers. The disturbance observer-based control schemes were utilized to deal with disturbances in [18,[24][25][26][27][28][29][30]. Different from the other schemes used to handle the disturbance, the disturbance observer is a tool that can directly and quickly press the strong disturbance.…”
Section: Introductionmentioning
confidence: 99%
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“…Nevertheless, the effectiveness of these research improvements is constrained by the low-frequency phase lag issue caused by filters lacking a zero point. Some other researchers have used adaptive algorithms to enhance the stability error compensation process for optoelectronic platforms and validated their approach through simulations [15,[17][18][19][20]. However, developing an adaptive algorithm model requires extensive empirical data and can be challenging to implement, raising questions about its practical utility in solving engineering problems.…”
Section: Introductionmentioning
confidence: 99%