U-model-based double sliding mode control (U<sub>DSM</sub>-control) of nonlinear dynamic systems

Zhu, Quanmin; Li, Ruobing; Yan, Xiangwu

doi:10.1080/00207721.2021.1991503

Cited by 5 publications

(2 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…During testing, two target trajectories are assigned. One is a constant value target (2) for each one of the N particles do (3) Initialize the position x i and velocity v i (4) Set particles' best position as current pbest i � x i (5) Calculate the fitness of each particle and set the optimum as the gbest (6) end for (7) Update. ( 8) while stopping Criterion not met do (9) Update particles' velocity using…”

Section: Parameters Initializationmentioning

confidence: 99%

See 1 more Smart Citation

U-Model-Based Adaptive Sliding Mode Control Using a Deep Deterministic Policy Gradient

Lei

Zhu

2022

Mathematical Problems in Engineering

Self Cite

View full text Add to dashboard Cite

This paper presents a U-model-based adaptive sliding mode control (SMC) using a deep deterministic policy gradient (DDPG) for uncertain nonlinear systems. The configuration of the proposed methodology consisted of a U-model framework and an SMC with a variable boundary layer. The U-model framework forms the outer feedback loop that adjusts the overall performance of the nonlinear system, while SMC serves as a robust dynamic inverter that cancels the nonlinearity of the original plant. Besides, to alleviate the chattering problem while maintaining the intrinsic advantages of SMC, a DDPG network is designed to adaptively tune the boundary and switching gain. From the control perspective, this controller combines the interpretability of the U-model and the robustness of the SMC. From the deep reinforcement learning (DRL) point of view, the DDPG calculates nearly optimal parameters for SMC based on current states and maximizes its favourable features while minimizing the unfavourable ones. The simulation results of the single-pendulum system are compared with those of a U-model-based SMC optimized by the particle swarm optimization (PSO) algorithm. The comparison, as well as model visualization, demonstrates the superiority of the proposed methodology.

show abstract

Section: Parameters Initializationmentioning

confidence: 99%

“…In doing this, the U-model provides a general routine to separate the system design and control design processes [2]. e gist of the U-model lies in designing a robust dynamic inverter that transforms the original plant into an identity matrix [2,3]. is brings about two advantages.…”

Section: Introductionmentioning

confidence: 99%

U-Model-Based Adaptive Sliding Mode Control Using a Deep Deterministic Policy Gradient

Lei

Zhu

2022

Mathematical Problems in Engineering

Self Cite

View full text Add to dashboard Cite

show abstract

Trajectory tracking of a quadrotor using extend state observer based U-model enhanced double sliding mode control

Zhu

Nemati

et al. 2023

Journal of the Franklin Institute

View full text Add to dashboard Cite

An improved U-control design for nonlinear systems represented by input/output differential models with a disturbance observer

Zhu

Zhang

et al. 2022

International Journal of Control

View full text Add to dashboard Cite

U-model-based double sliding mode control (U_DSM-control) of nonlinear dynamic systems

Cited by 5 publications

References 21 publications

U-Model-Based Adaptive Sliding Mode Control Using a Deep Deterministic Policy Gradient

U-Model-Based Adaptive Sliding Mode Control Using a Deep Deterministic Policy Gradient

Trajectory tracking of a quadrotor using extend state observer based U-model enhanced double sliding mode control

An improved U-control design for nonlinear systems represented by input/output differential models with a disturbance observer

Contact Info

Product

Resources

About

U-model-based double sliding mode control (UDSM-control) of nonlinear dynamic systems

Cited by 5 publications

References 21 publications

U-Model-Based Adaptive Sliding Mode Control Using a Deep Deterministic Policy Gradient

U-Model-Based Adaptive Sliding Mode Control Using a Deep Deterministic Policy Gradient

Trajectory tracking of a quadrotor using extend state observer based U-model enhanced double sliding mode control

An improved U-control design for nonlinear systems represented by input/output differential models with a disturbance observer

Contact Info

Product

Resources

About

U-model-based double sliding mode control (U_DSM-control) of nonlinear dynamic systems