Adaptive tracking control for nonlinear time-delay systems with time-varying full state constraints

Wu, Yuxiang; Xu, Tian; Mo, Hongqiang

doi:10.1177/0142331220908987

Cited by 16 publications

(10 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Assumption 2 is often used in studies that use NSDF to solve output or state constraints [16,36,37]. Assumption 3 is a common assumption about the desired signal in literature that considers time-varying output or state constraints [36,38,39,40].…”

Section: Problem Formulationmentioning

confidence: 99%

UDE-based task space tracking control of uncertain robot manipulator with input saturation and output constraint

Wan

et al. 2022

Robotica

Self Cite

View full text Add to dashboard Cite

This paper investigates the trajectory tracking problem of uncertain robot manipulators with input saturation and output constraints. Uncertainty and disturbance estimator (UDE) is used to tackle the model uncertainties and external disturbances. Different from most existing methods, UDE only needs the bandwidth of the unknown plant model for design, which makes it easy to be implemented. Nonlinear state-dependent function is employed to cope with output constraints and a second order auxiliary system is constructed to solve the input saturation. Finally, an UDE-based tracking controller is proposed based on the backstepping method. With the proposed control scheme, the input saturation and the output constraints are not violated, and all signals in the closed-loop system are bounded. The comparative simulation results of a two-link robot manipulator are utilized to validate the effectiveness and superiority of the proposed control method.

show abstract

Section: Problem Formulationmentioning

confidence: 99%

UDE-based task space tracking control of uncertain robot manipulator with input saturation and output constraint

Wan

et al. 2022

Robotica

Self Cite

View full text Add to dashboard Cite

show abstract

“…For simplicity, the controller is designed under Assumption 3. Assumption 4 is common in state constrained tracking control (Li et al, 2019; Wang et al, 2019; Wu et al, 2020).…”

Section: System Description and Some Preliminariesmentioning

confidence: 99%

“…Thus, how to solve the unknown time-varying delays effectively should be further considered. Second, though some traditional infinite-time adaptive tracking control methods have been proposed (Li et al, 2019; Wang et al, 2019; Wu et al, 2020; Yang et al, 2021; Zhu et al, 2020), it is more difficult to obtain results on the finite-time problem for general nonlinear delay systems with full state constraints and input saturation. Therefore, how to construct an adaptive finite-time tracking controller is a nontrivial task for the given nonlinear system (equation (1)).…”

Section: Adaptive Finite-time Tracking Controller Designmentioning

confidence: 99%

“…Based on the Lyapunov-Krasovskii method and NNs, the adaptive tracking control problem of nonlinear time-delay systems with unmodeled dynamics was investigated (Wang et al, 2020b). By combining the BLFs and the Lyapunov-Krasovskii method, the adaptive tracking control approach for uncertain nonlinear systems with full state constraints and time delays was developed (Wu et al, 2020). Furthermore, this result was extended to a general class of uncertain nonlinear time-delay systems with unknown output functions and unknown control directions (Hong et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive finite-time tracking control for full state constrained nonlinear systems with time-varying delays and input saturation

Fang

et al. 2021

Transactions of the Institute of Measurement and Control

Self Cite

View full text Add to dashboard Cite

This paper investigates the adaptive finite-time tracking control problem for a class of nonlinear full state constrained systems with time-varying delays and input saturation. Compared with the previously published work, the considered system involves unknown time-varying delays, asymmetric input saturation, and time-varying asymmetric full state constraints. To ensure the state constraint satisfaction, the appropriate time-varying asymmetric Barrier Lyapunov Functions and the backstepping technique are utilized. Meanwhile, the finite covering lemma and the radial basis function neural networks are employed to solve the unknown time-varying delays. The assumption that the time derivative of time-varying delay functions is required to be less than one in traditional Lyapunov–Krasovskii functionals is removed by the proposed method. Moreover, the asymmetric input saturation is handled by an auxiliary design system. Taking the norm of the neural network weight vector as an adaptive parameter, a novel adaptive finite-time tracking controller with minimal learning parameters is constructed. It is proved that the proposed controller can guarantee that all signals in the closed-loop system are bounded, all states are constrained within the predefined sets, and the tracking error converges to a small neighborhood of the origin in a finite time. Finally, a comparison study simulation is given to demonstrate the effectiveness of our proposed strategy. The simulation results show that our proposed strategy has good advantages of high tracking precision and disturbance rejection.

show abstract

“…Note that tracking control plays an important role in control theory, which can be applied in many practical engineering (Hua et al, 2020; Li et al, 2018; Sun et al, 2020; Wu et al, 2020b; Yao and Zhang, 2019; Zhang et al, 2018; Zhao et al, 2015). It is well known that tracking control is to design a controller to track a predetermined signal, which is more challenging than the conventional stabilization problem.…”

Section: Introductionmentioning

confidence: 99%

Dynamic event-triggered tracking control for a class of p-normal switched stochastic nonlinear systems

Yuan

Zhai

2022

Transactions of the Institute of Measurement and Control

View full text Add to dashboard Cite

This paper investigates the event-triggered tracking issue for p-normal switched stochastic nonlinear systems. Unlike the existing event-triggered schemes, an event-triggering mechanism is proposed with a dynamic gain. Then, a new adaptive event-triggered controller (ETC) is designed via output feedback. The presented control scheme can render that all signals of the closed-loop system are bounded almost surely. Moreover, the Zeno phenomenon is excluded. Three examples are provided to verify the efficiency of the presented strategy.

show abstract

Adaptive tracking control for nonlinear time-delay systems with time-varying full state constraints

Cited by 16 publications

References 52 publications

UDE-based task space tracking control of uncertain robot manipulator with input saturation and output constraint

UDE-based task space tracking control of uncertain robot manipulator with input saturation and output constraint

Adaptive finite-time tracking control for full state constrained nonlinear systems with time-varying delays and input saturation

Dynamic event-triggered tracking control for a class of p-normal switched stochastic nonlinear systems

Contact Info

Product

Resources

About