scholarly journals Robust Tracking Control for Robotic Manipulator via Fuzzy Logic System andH∞Approaches

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Kun Mu ◽  
Cong Liu ◽  
Jinzhu Peng
Keyword(s):  
Fuzzy Logic ◽  
Tracking Control ◽  
Robotic Manipulator ◽  
Fuzzy Logic System ◽  
Torque Control ◽  
Robust Tracking ◽  
Robust Tracking Control ◽  
External Disturbances ◽  
Control Scheme ◽  
Logic System

Based on fuzzy logic system (FLS) andH∞control methodologies, a robust tracking control scheme is proposed for robotic system with uncertainties and external disturbances. FLS is employed to implement the framework of computed torque control (CTC) method via its approximate capability which is used to attenuate the nonlinearity of robotic manipulator. The robustH∞control can guarantee robustness to parametric and dynamics uncertainties and also attenuate the effect of immeasurable external disturbances entering the system. Moreover, a quadratic stability approach is used to reduce the conservatism of the conventional robust control approach. It can be guaranteed that all signals in the closed-loop are bounded by employing the proposed robust tracking control. The validity of the proposed control scheme is shown by simulation of a two-link robotic manipulator.

scholarly journals Antidisturbance Control for AUV Trajectory Tracking Based on Fuzzy Adaptive Extended State Observer

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7084
Author(s):  
Song Kang ◽  
Yongfeng Rong ◽  
Wusheng Chou
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic System ◽  
Entire System ◽  
Actuator Faults ◽  
Extended State ◽  
Parameter Uncertainties ◽  
External Disturbances ◽  
Measurement Noises ◽  
Fuzzy Adaptive ◽  
Logic System

In this paper, an output-feedback fuzzy adaptive dynamic surface controller (FADSC) based on fuzzy adaptive extended state observer (FAESO) is proposed for autonomous underwater vehicle (AUV) systems in the presence of external disturbances, parameter uncertainties, measurement noises and actuator faults. The fuzzy logic system is incorporated into both the observers and controllers to improve the adaptability of the entire system. The dynamics of the AUV system is established first, considering the external disturbances and parameter uncertainties. Based on the dynamic models, the ESO, combined with a fuzzy logic system tuning the observer bandwidth, is developed to not only adaptively estimate both system states and the lumped disturbances for the controller, but also reduce the impact of measurement noises. Then, the DSC, together with fuzzy logic system tuning the time constant of the low-pass filter, is designed using estimations from the FAESO for the AUV system. The asymptotic stability of the entire system is analyzed through Lyapunov’s direct method in the time domain. Comparative simulations are implemented to verify the effectiveness and advantages of the proposed method compared with other observers and controllers considering external disturbances, parameter uncertainties and measurement noises and even the actuator faults that are not considered in the design process. The results show that the proposed method outperforms others in terms of tracking accuracy, robustness and energy consumption.

Robust Tracking Control of a Direct Drive Robot

1999 ◽  
Vol 121 (2) ◽  
pp. 261-269 ◽  
Author(s):  
Bong Soo Kang ◽  
Soo Hyun Kim ◽  
Yoon Keun Kwak ◽  
Craig C. Smith
Keyword(s):  
Tracking Control ◽  
Torque Control ◽  
Joint Control ◽  
Robust Tracking ◽  
Direct Drive ◽  
Robust Tracking Control ◽  
Tracking Errors ◽  
Robust Controller ◽  
Residual Errors ◽  
Computed Torque

This paper presents a robust controller for tracking control of a direct-drive robot. The proposed controller consists of two portions: a computed torque method which precompensates for dynamics of the modeled plant and an H∞ controller which postcompensates for residual errors which are not completely removed by the computed torque method. Experimental methods for identifying appropriate model structure and parameters are presented, and three specific controller types are compared. Using the robot designed in our laboratory, the combined controller reduced tracking errors by one half compared to computed torque control alone, and by one sixth compared to conventional independent joint control.

scholarly journals Suppression the Disturbance of Robotic Manipulators Based on Nonlinear Disturbance Observer and Fuzzy Logic System

2020 ◽  
Vol 24 (7) ◽  
pp. 846-854
Author(s):  
Wangyong He ◽  
Haogui Li ◽  
Yuanjiang Wang ◽  
Sanqiu Liu ◽  
◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Disturbance Observer ◽  
Robot Manipulator ◽  
Robotic Manipulators ◽  
Fuzzy Logic System ◽  
External Disturbances ◽  
Nonlinear Disturbance Observer ◽  
Coupling System ◽  
Nonlinear Disturbance ◽  
Logic System

Robotic Manipulators (RM) are nonlinear and coupling system with time-variant and model uncertainties. In addition, RM are subject to different types of disturbances in practice, such as joint frictions, unknown payloads, and interferences from external systems. In this paper, these adverse factors are regarded as disturbance, and classifies them into internal disturbances and external disturbances. In order to achieve high-precision control, a Nonlinear Disturbance Observer (NDO) is designed to suppress external disturbances, and a Fuzzy Logic System (FLS) is designed to compensate internal disturbances. The scheme can effectively suppress the disturbance and improve the control accuracy. The validity of the scheme is shown by computer simulations of a two-link robot manipulator.

scholarly journals An Adaptive Control of Fractional-Order Nonlinear Uncertain Systems with Input Saturation

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Changhui Wang ◽  
Mei Liang ◽  
Yongsheng Chai
Keyword(s):  
Fuzzy Logic ◽  
Fractional Order ◽  
Uncertain Systems ◽  
Input Saturation ◽  
Fuzzy Logic System ◽  
Distributed Model ◽  
Unknown Parameters ◽  
External Disturbances ◽  
Nonlinear Uncertain Systems ◽  
Logic System

This paper develops a fractional-order adaptive fuzzy backstepping control scheme for incommensurate fractional-order nonlinear uncertain systems with external disturbances and input saturation. Based on backstepping algorithm, the fuzzy logic system is used to approximate the unknown nonlinear uncertainties in each step of the backstepping, and the fractional-order parameters update laws for fuzzy logic system, unknown parameters, and the external disturbances are proposed. With the aids of the frequency distributed model of fractional integrator for the fractional-order systems in the procedure of controller design, the stability of the closed-loop system is established. To verify the effectiveness and robustness of the proposed controller, two simulation examples are demonstrated at last.

Robust fuzzy tracking control for flexible air-breathing hypersonic vehicles with measurement noises

2019 ◽  
Vol 41 (13) ◽  
pp. 3818-3835
Author(s):  
Yifan Liu ◽  
Jinlin Sun ◽  
Zhiqiang Pu ◽  
Jianqiang Yi ◽  
Shiliang Pu
Keyword(s):  
Tracking Control ◽  
Fuzzy Logic System ◽  
Adaptive Technique ◽  
Control Scheme ◽  
State Estimators ◽  
Tracking Controllers ◽  
Measurement Noises ◽  
Fuzzy Adaptive ◽  
Logic System

Measurement noise is an obstacle to the performance improvement of a flexible air-breathing hypersonic vehicle. This paper explores a robust fuzzy tracking control scheme for the longitudinal dynamics of the hypersonic vehicle, which is constructed by utilizing type-2 fuzzy adaptive technique and dynamic surface control (DSC) approach. The control scheme is comprised of two parts: the state estimators and tracking controllers of velocity and altitude. The state estimators are designed by using the type-2 fuzzy logic system-based approximators, which guarantees the estimation of real states from measurement signals with noises. Furthermore, on the basis of the designed state estimators, the velocity and altitude tracking controllers are constructed by using the adaptive fuzzy DSC approach. On one hand, DSC approach can filter the virtual control law and avoid the amplification of the measurement noise. On the other hand, since the antecedent of the type-2 fuzzy logic system is based on the type-2 fuzzy sets and the consequent parameters are adjusted by an integral calculation in the adaptive law, the type-2 fuzzy adaptive technique in the adaptive fuzzy DSC tracking controller has the ability to further reduce the impact of the measurement noises. A Lyapunov-based stability analysis shows the tracking ability of the proposed control scheme. Nominal and comparison simulation considering the measurement noises are carried out for demonstrating the effectiveness of the proposed method.

scholarly journals Adaptive Fuzzy H∞ Robust Tracking Control for Nonlinear MIMO Systems

2015 ◽  
Vol 15 (1) ◽  
pp. 34-45
Author(s):  
Sanxiu Wang ◽  
Kexin Xing ◽  
Zhengchu Wang
Keyword(s):  
Tracking Control ◽  
Mimo Systems ◽  
Tracking Error ◽  
Approximation Error ◽  
Nonlinear Function ◽  
Robust Tracking ◽  
Robust Tracking Control ◽  
Fuzzy Logic Systems ◽  
Adaptive Fuzzy ◽  
Control Scheme

Abstract In this paper an adaptive fuzzy H∞ robust tracking control scheme is developed for a class of uncertain nonlinear Multi-Input and Multi-Output (MIMO) systems. Firstly, fuzzy logic systems are introduced to approximate the unknown nonlinear function of the system by an adaptive algorithm. Next, a H∞ robust compensator controller is employed to eliminate the effect of the approximation error and external disturbances. Consequently, a fuzzy adaptive robust controller is proposed, such that the tracking error of the resulting closed-loop system converges to zero and the tracking robustness performance can be guaranteed. The simulation results performed on a two-link robotic manipulator demonstrate the validity of the proposed control scheme.

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