Adaptive control for an uncertain robotic manipulator with input saturations

Tran, Trong-Toan; Ge, Shuzhi Sam; He, Wei

doi:10.1007/s11768-016-5059-0

Cited by 22 publications

(6 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…! nd % 4:6 d t sd (11) Finally, the coefficients in the denominator, the closedloop transfer function (3), can be computed through the equivalence of the terms in the denominator of equation ( 9), the second-order desired transfer function. The resulting gains are now defined as…”

Section: Pi Controllersmentioning

confidence: 99%

“…Also, other adaptive control structures have been used in manipulator robots. [9][10][11] Academic interest in PID controllers has gradually decreased, giving space to other control strategies, for example, fuzzy controllers, neuro-fuzzy controllers, sliding mode controllers, nonlinear controller and adaptive controllers, among others; however, these other control strategies have not been able to gain significant presence in industrial processes. The gap between research conducted by the industrial and the academic sectors on PID controllers and other control methods has received lot of attention in literature.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive proportional–integral controller using OLE for process control for industrial applications

Paz

Ramírez-delReal

Garibo

et al. 2017

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

This article presents an implementation of an adaptive control architecture, which provides the combined advantages of better dynamic performance compared to other conventional industrial controllers, and the use of widely available hardware in process industry. Adaptive control architecture uses proportional-integral action and dynamic computation of the controller's gains (self-tuning regulator), to maintain performance specifications, even in the presence of parametric disturbances. This architecture offers advantages over other advanced embedded control systems implemented on industrial programmable logic controllers and other hardware platforms. Implementation of controllers on industrial hardware platforms is possible through the Object Linking and Embedding (OLE) for process control communication standard. The implementation for an adaptive controller here proposed was evaluated through experiments using firstorder and overdamped second-order systems emulated by hardware-in-the-loop, with a programmable automation controller. Performance of the adaptive controllers was compared to that of conventional proportional-integral controllers, and effectiveness of the former over the latter was demonstrated through the experiments carried out.

show abstract

Section: Pi Controllersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive proportional–integral controller using OLE for process control for industrial applications

Paz

Ramírez-delReal

Garibo

et al. 2017

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

show abstract

“…Focusing on the trajectory tracking control problem of a manipulator system, various control strategies have been studied in related fields, such as PD control with feedforward compensation [3,4], adaptive control [5][6][7], fuzzy control [8,9], neural network control [10][11][12][13], and sliding mode control [14]. Chen et al [3] proposed a modified PD feedforward compensation control.…”

Section: Introductionmentioning

confidence: 99%

“…According to the ASL-PD method, the convergence rate of manipulator trajectory tracking is effectively increased. e control of an uncertain robotic manipulator with input saturation was studied by Tran and Sam [7].…”

Section: Introductionmentioning

confidence: 99%

Linear Active Disturbance Rejection Control of a Two-Degrees-of-Freedom Manipulator

Liu

Gao

Chen

et al. 2020

Mathematical Problems in Engineering

View full text Add to dashboard Cite

This paper presents linear active disturbance rejection control (LADRC) for a two-degrees-of-freedom (2-DOF) manipulator system to achieve trajectory tracking. The system is widely used in engineering applications and exhibits the characteristics of high nonlinearity, strong coupling, and large uncertainty with two inputs and two outputs. First, the problem of dynamic coupling in the model of the 2-DOF manipulator is addressed by considering the dynamic coupling, model uncertainties, and external disturbances as total disturbances. Second, a linear extended state observer is designed to estimate the total disturbances, while a linear state error feedback control law is designed to compensate these disturbances. The main contribution is that the stability of the closed-loop system with two inputs and two outputs is analyzed, and the relationship between the performance of the closed-loop system and the controller parameters is established. The joint simulation of SolidWorks and Matlab/Simulink is conducted. The simulation and experimental results clearly indicate the superiority of LADRC over the PID for trajectory tracking and dynamic performance.

show abstract

“…However, the non-linear of the mobile robots itself and the disturbance of the external environment make a great difficulty on the mobile robots trajectory tracking control. Based on the research of this problem, sliding mode variable structure control [5], neural network control [6], [7], adaptive control [8]- [11] and other methods have been applied to the trajectory tracking control…”

Section: Introductionmentioning

confidence: 99%

Disturbance Observer Based on Biologically Inspired Integral Sliding Mode Control for Trajectory Tracking of Mobile Robots

Yang¹,

Peng²,

Zhang³

et al. 2019

IEEE Access

View full text Add to dashboard Cite

This paper proposes an integral sliding control system based on the nonlinear disturbance observer, aiming to the trajectory tracking of the mobile robot under the external disturbance. First, a kinematic model of mobile robot was built, besides, the position error signal was gained by the biological membrane potential model, and the problem of velocity oscillation was solved by the design of the backstepping controller. Then, an integral sliding control system was designed in accordance with the kinematic model of the mobile robot, meanwhile, a disturbance observer was designed in consideration of external disturbance to do the real-time observation on the disturbance occurring in the system with an addition of feedforward compensation and the observation error was converged by selecting the design parameters. The Lyapunov function was used to prove the stability of the system. Finally, the simulation of tracking circularity trajectory was utilized, with the comparison of trajectory without the use of jammer, to prove that this method can well overcome the nonlinear and uncertainty originated from external, thereby improving the control performance and increasing the robustness.INDEX TERMS Mobile robots, trajectory tracking, disturbance observer, integral sliding mode variable structure, back-stepping control.

show abstract

Adaptive control for an uncertain robotic manipulator with input saturations

Cited by 22 publications

References 30 publications

Adaptive proportional–integral controller using OLE for process control for industrial applications

Adaptive proportional–integral controller using OLE for process control for industrial applications

Linear Active Disturbance Rejection Control of a Two-Degrees-of-Freedom Manipulator

Disturbance Observer Based on Biologically Inspired Integral Sliding Mode Control for Trajectory Tracking of Mobile Robots

Contact Info

Product

Resources

About