scholarly journals Robust Adaptive Self-Organizing Wavelet Fuzzy CMAC Tracking Control for De-icing Robot Manipulator

2015 ◽  
Vol 10 (4) ◽  
pp. 567 ◽  
Author(s):  
ThanhQuyen Ngo ◽  
TaVan Phuong
Keyword(s):  
Robot Manipulator ◽  
Learning Ability ◽  
Cerebellar Model Articulation Controller ◽  
Robust Controller ◽  
Fast Learning ◽  
Self Organized ◽  
Fuzzy Cmac ◽  
Robust Adaptive ◽  
The Stability ◽  
Self Organizing

In this paper, a robust adaptive self-organizing control system based on a novel wavelet fuzzy cerebellar model articulation controller (WFCMAC) is developed for an n-link robot manipulator to achieve the high-precision position tracking. This proposed controller consists of two parts: one is the WFCMAC approach which is implemented to cope with nonlinearities, due to the novel WFCMAC not only incorporates the wavelet decomposition property with fuzzy CMAC fast learning ability but also it will be self-organized; that is, the layers of WFCMAC will grow or prune systematically. Therefore, dimension of WFCMAC can be simplified. The second is the order which is the adaptive robust controller which is designed to achieve robust tracking performance of the system. The adaptive tuning laws of WFCMAC parameters and error estimation of adaptive robust controller are derived through the Lyapunov function so that the stability of the system can be guaranteed. Finally, the simulation and experimental results of novel three-link deicing robot manipulator are applied to verify the effectiveness of the proposed control methodology.

scholarly journals Self-Organizing Adaptive Wavelet Backstepping Control Research for AC Servo System

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Run-min Hou ◽  
Yuan-long Hou ◽  
Qiang Gao ◽  
Chao Wang
Keyword(s):  
Servo System ◽  
Cerebellar Model Articulation Controller ◽  
Adaptive Wavelet ◽  
Ac Servo System ◽  
Ac Servo ◽  
Fast Learning ◽  
Prototype Test ◽  
Control Research ◽  
The Stability ◽  
Self Organizing

A novel self-organizing adaptive wavelet cerebellar model articulation controller backstepping (SOWCB) control is proposed, aiming at some nonlinear and uncertain factors that caused difficulties in controlling the AC servo system. This controller consists of self-organizing wavelet cerebellar model articulation controller (CMAC) and robust compensator. It absorbs fast learning and precise approaching advantage of self-organizing wavelet CMAC to mimic a backstepping controller, and then robust compensator is added to inhibit influence of the uncertainties on system performance effectively and realize high accuracy position tracking for AC servo system. Moreover, the stability of the control system can be guaranteed by using Lyapunov method. The results of the simulation and the prototype test prove that the proposed approach can improve the steady state performance and control accuracy and possess a strong robustness to both parameter perturbation and load disturbance.

A PD Robust Controller Design and Simulation Based on Two-Link Manipulator under Given Upper Bound Disturbance

2012 ◽  
Vol 503-504 ◽  
pp. 1540-1544
Author(s):  
Ji Yan Wang ◽  
Yu Xia Zhuang
Keyword(s):  
Upper Bound ◽  
Controller Design ◽  
Robot Manipulator ◽  
Industrial Robot ◽  
Stability And Convergence ◽  
Robust Controller ◽  
Simulation Based ◽  
The Stability ◽  
Driving Torque ◽  
Robust Controller Design

For industrial robot manipulator system, PD control theory is extensively used in the dynamic characteristics controlling. A PD robust controller is introduced to optimize the stability and convergence of traditional PD controller and avoid excess initial driving torque for two-link industrial manipulator system. By the co-simulation on ADAMS and Matlab/ Simulink, the paper designs a PD robust controller under given upper bound disturbance and completes track control and driving torque trial. Through result comparison and analysis, the superiority of the PD robust controller for two-link manipulator is verified.

scholarly journals Design of Adaptive TSK Fuzzy Self-Organizing Recurrent Cerebellar Model Articulation Controller for Chaotic Systems Control

2021 ◽  
Vol 11 (4) ◽  
pp. 1567
Author(s):  
Shun-Yuan Wang ◽  
Chuan-Min Lin ◽  
Chen-Hao Li
Keyword(s):  
Chaotic Systems ◽  
Tracking Error ◽  
Extensive Study ◽  
Fuzzy Rules ◽  
Cerebellar Model Articulation Controller ◽  
Control Performance ◽  
Fuzzy Cmac ◽  
Structure Complexity ◽  
Takagi Sugeno ◽  
Self Organizing

The synchronization and control of chaos have been under extensive study by researchers in recent years. In this study, an adaptive Takagi–Sugeno–Kang (TSK) fuzzy self-organizing recurrent cerebellar model articulation controller (ATFSORC) is proposed, which is composed of a set of TSK fuzzy rules, a cerebellar model articulation controller (CMAC), a recurrent CMAC (RCMAC), a self-organizing CMAC (SOCMAC), and a compensation controller. Specifically, SOCMAC, RCMAC, and adaptive laws are adopted so that the association memory layers of ATFSORC can be modulated in accordance with the layer decision-making mechanism in order to reduce the structure complexity and improve the control performance of ATFSORC. Moreover, the Takagi–Sugeno–Kang fuzzy rules are introduced to increase the learning speed of ATFSORC, and the improved compensating controller is designed to dispel the errors between an ideal controller and the TFSORC. Moreover, the proposed ATFSORC is applied to chaotic systems in order to validate its performance and feasibility. Several simulation schemes are demonstrated to show the effectiveness of the proposed method. Simulation results show that the proposed ATFSORC can obtain a favorable control performance when the chaotic systems are operated at different parameters. Specifically, ATFSORC can achieve faster convergence of the tracking error than fuzzy CMAC (FCMAC) and CMAC.

Robust Hybrid Fractional Order Proportional Derivative Sliding Mode Controller for Robot Manipulator Based on Extended Grey Wolf Optimizer

Robotica ◽  
2019 ◽  
Vol 38 (4) ◽  
pp. 605-616 ◽  
Author(s):  
Hossein Komijani ◽  
Mojtaba Masoumnezhad ◽  
Morteza Mohammadi Zanjireh ◽  
Mahdi Mir
Keyword(s):  
Fractional Order ◽  
Sliding Mode ◽  
Robot Manipulator ◽  
Lyapunov Theory ◽  
Grey Wolf Optimizer ◽  
Sliding Mode Controller ◽  
Grey Wolf ◽  
Robust Controller ◽  
The Stability ◽  
Proportional Derivative Controller

SUMMARYThis paper presents a novel robust hybrid fractional order proportional derivative sliding mode controller (HFOPDSMC) for 2-degree of freedom (2-DOF) robot manipulator based on extended grey wolf optimizer (EGWO). Sliding mode controller (SMC) is remarkably robust against the uncertainties and external disturbances and shows the valuable properties of accuracy. In this paper, a new fractional order sliding surface (FOSS) is defined. Integrating the fractional order proportional derivative controller (FOPDC) and a new sliding mode controller (FOSMC), a novel robust controller based on HFOPDSMC is proposed. The bounded model uncertainties are considered in the dynamics of the robot, and then the robustness of the controller is verified. The Lyapunov theory is utilized in order to show the stability of the proposed controller. In this paper, the EGWO is developed by adding the emphasis coefficients to the typical grey wolf optimizer (GWO). The GWO and EGWO, then, are applied to optimize the proposed control parameters which result in the optimized GWO-HFOPDSMC and EGWO-HFOPDSMC, respectively. The effectivenesses of the optimized controllers (GWO-HFOPDSMC and EGWO-HFOPDSMC) are completely verified by comparing the simulation results of the optimized controllers with the typical FOSMC and HFOPDSMC.

On Operational Space Tracking Control of Robotic Manipulators With Uncertain Dynamic and Kinematic Terms

2018 ◽  
Vol 141 (1) ◽  
Author(s):  
Kamil Cetin ◽  
Enver Tatlicioglu ◽  
Erkan Zergeroglu
Keyword(s):  
Tracking Control ◽  
Joint Space ◽  
Robot Dynamics ◽  
Robust Controller ◽  
Operational Space ◽  
Asymptotic Tracking ◽  
Robust Adaptive ◽  
And Performance ◽  
The Stability ◽  
Velocity Level

In this study, a continuous robust-adaptive operational space controller that ensures asymptotic end-effector tracking, despite the uncertainties in robot dynamics and on the velocity level kinematics of the robot, is proposed. Specifically, a smooth robust controller is applied to compensate the parametric uncertainties related to the robot dynamics while an adaptive update algorithm is used to deal with the kinematic uncertainties. Rather than formulating the tracking problem in the joint space, as most of the previous works on the field have done, the controller formulation is presented in the operational space of the robot where the actual task is performed. Additionally, the robust part of the proposed controller is continuous ensuring the asymptotic tracking and relatively smooth controller effort. The stability of the overall system and boundedness of the closed loop signals are ensured via Lyapunov based arguments. Experimental results are presented to illustrate the feasibility and performance of the proposed method.

Design of Robust Controller for 2-DOF Flexible Link Robot Manipulator

2021 ◽  
Author(s):  
Renukadas Pimpalgaonkar ◽  
Prathamesh Khare ◽  
Anagha Chikhalthankar ◽  
Sandeep Hanwate ◽  
M. D. Jaybhaye
Keyword(s):  
Robot Manipulator ◽  
Flexible Link ◽  
Robust Controller

Multi-loop model-based control structure for robot manipulators

Robotica ◽  
2005 ◽  
Vol 23 (4) ◽  
pp. 491-499 ◽  
Author(s):  
Rafael Osypiuk ◽  
Bernd Finkemeyer ◽  
Friedrich M. Wahl
Keyword(s):  
Control Structure ◽  
Robot Manipulator ◽  
Loop Model ◽  
Loop Control ◽  
Model Based Control ◽  
Model Following Control ◽  
Model Following ◽  
Theoretical Assumptions ◽  
Quantitative Results ◽  
The Stability

Most nonlinear control concepts used in robotics are based on a more or less accurate inverse model of the robot. In contrast to this, the design and properties of a general $n$-loop control structure based on a divided forward model of the robot, the so-called multi-loop Model Following Control Structure ($n$-MFC), is presented in this paper. Its theoretical basics and its concept are explained. The stability and robustness of the proposed control structure is analyzed. The theoretical assumptions are verified in many experiments with a two-joint robot manipulator. Qualitative as well as quantitative results of the experiments are presented and discussed.

The Design and Simulation for Two-Link Manipulators PD Robust Controller under Uncertain Upper Bound Disturbance

2013 ◽  
Vol 694-697 ◽  
pp. 1652-1655
Author(s):  
Ji Yan Wang
Keyword(s):  
Dynamic Characteristics ◽  
Upper Bound ◽  
Control Method ◽  
Robot Manipulator ◽  
Industrial Robot ◽  
Pd Controller ◽  
Robust Controller ◽  
Convergence And Stability ◽  
Comparison And Analysis ◽  
Driving Torque

PD control method is widely utilized for the dynamic characteristics controlling in industrial robot manipulator area. The disturbance is usually uncertain in reality; the traditional PD controller is limited in that case. In this paper, a PD robust controller is introduced to optimize the convergence and stability of PD controller and avoid the extreme initial driving torque for two-link manipulator system. Using the co-simulation on Matlab/ Simulink and ADAMS, the paper designs a PD robust controller under uncertain upper bound disturbance and completes track control and driving torque simulation trial. The superiority of the two-link manipulators PD robust controller is verified through result comparison and analysis.

Sign in / Sign up

Export Citation Format

Share Document