Synchronous tracking control of gantry stage using adaptive fuzzy moving sliding mode approach

2016 ◽  
Author(s):  
Yu-Chen Lin ◽  
Tsung-Chih Lin ◽  
Yi-Chao Chen ◽  
Tai-Yi Liu
Keyword(s):  
Tracking Control ◽  
Sliding Mode ◽  
Adaptive Fuzzy

Direct Adaptive Fuzzy Moving Sliding Mode Proportional Integral Tracking Control of a Three-Dimensional Overhead Crane

2016 ◽  
Vol 138 (10) ◽  
Author(s):  
Tsung-Chih Lin ◽  
Yu-Chen Lin ◽  
Majid Moradi Zirkohi ◽  
Hsi-Chun Huang
Keyword(s):  
Tracking Control ◽  
Sliding Mode ◽  
Three Dimensional ◽  
Overhead Crane ◽  
Nonlinear Controller ◽  
Proportional Integral ◽  
Adaptive Fuzzy ◽  
Highly Nonlinear ◽  
Position Regulation ◽  
Robust Regulation

In this paper, a novel direct adaptive fuzzy moving sliding mode proportional integral (PI) tracking control of a three-dimensional (3D) overhead crane which is modeled by five highly nonlinear second-order ordinary differential equations is proposed. The fast and robust position regulation and antiswing control can be achieved based on the proposed approach. Due to universal approximation theorem, fuzzy control provides nonlinear controller, i.e., fuzzy logic controllers, to perform the unknown nonlinear control actions. Simultaneously, in order to achieve fast and robust regulation and to enhance robustness in the presence of disturbance and parameter variations, moving sliding mode control (SMC) is introduced to tradeoff between reaching phase and sliding phase. Hence, the sliding surface is moved by changing the magnitude of the slope by adaptive law and varying the intercept by tuning algorithm. Simulations performed using a scaled 3D mathematical model of the crane confirm that the proposed control scheme can keep the horizontal position of the payload invariable and suppress the swing of the payload effectively during the hoisting or lowing process.

scholarly journals Adaptive Fuzzy Sliding Mode and Robust Tracking Control for Manipulators with Uncertain Dynamics

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Sanxiu Wang
Keyword(s):  
Sliding Mode Control ◽  
Trajectory Tracking ◽  
Tracking Control ◽  
Sliding Mode ◽  
External Disturbance ◽  
Robotic Manipulator ◽  
Trajectory Tracking Control ◽  
Adaptive Fuzzy ◽  
Adaptive Fuzzy Sliding Mode ◽  
Fuzzy Sliding Mode

In response to the issue of the trajectory tracking control problem of manipulators with uncertain parameters and external disturbance, an adaptive fuzzy sliding mode robust control algorithm is proposed. Sliding mode control (SMC) is adopted to perform robotic manipulator trajectory tracking control. Then, a fuzzy logic system is used for adaptive adjustment of switching gain of the SMC and to reduce the buffeting problem. Next, compensation is made by using the robust controller in consideration of the impacts of unmodeled dynamics and external disturbance. The simulation experiment on a two axes robotic manipulator shows that, with the proposed control method, the sliding mode control input signal is kept smooth, and the manipulator has high trajectory tracking precision.

Adaptive fuzzy radial basis function neural network integral sliding mode tracking control for heavy vehicle electro-hydraulic power steering systems

2019 ◽  
Vol 234 (2-3) ◽  
pp. 872-886
Author(s):  
Heng Du ◽  
Lin Wang ◽  
Jinda Chen ◽  
Hui Huang ◽  
Yunchao Wang
Keyword(s):  
Sliding Mode Control ◽  
Tracking Control ◽  
Sliding Mode ◽  
Hydraulic Power ◽  
Integral Sliding Mode Control ◽  
Integral Sliding Mode ◽  
Adaptive Fuzzy ◽  
Mode Control ◽  
Power Steering ◽  
Hydraulic Power Steering

Due to parametric uncertainties, unknown nonlinearities, and dynamic external disturbances, it is a challenging and valuable task for heavy vehicle electro-hydraulic power steering systems to realize high-precision tracking control. To cope with this complex nonlinear tracking control problem, the integral sliding mode control is an extremely potential control method, which has strong robustness to model uncertainties and unknown disturbances, and can effectively reduce the steady-state error in tracking control process. However, the inherent chattering phenomenon of integral sliding mode control seriously affects its control performance. In order to suppress the chattering while ensuring robustness, adaptive fuzzy technique is adopted as an effective auxiliary means, which can not only deal with the inherent chattering problem of integral sliding mode control and a priori knowledge of the disturbance upper bound in controller design but also dynamically adjust the parameters in the fuzzy rules. Moreover, the designed adaptive fuzzy–integral sliding mode control scheme still needs the precise mathematical models of the control systems. But it is difficult to obtain the model for heavy vehicle electro-hydraulic power steering systems with highly complex and coupling properties. Therefore, to further improve the method, this paper presents a novel adaptive fuzzy–radial basis function neural network–integral sliding mode control method for the complex systems to achieve timely and accurate steering angle tracking control. In addition to the advantages of adaptive fuzzy–integral sliding mode control, the modified controller no longer requires the precise mathematical models of heavy vehicle electro-hydraulic power steering systems and realizes the continuous adaptive updating of weights. Finally, the effectiveness and superiority of the proposed control scheme is illustrated by comparisons and extensive simulations.

scholarly journals Robust Full Tracking Control Design of Disturbed Quadrotor UAVs with Unknown Dynamics

Aerospace ◽  
2018 ◽  
Vol 5 (4) ◽  
pp. 115 ◽  
Author(s):  
Nabil Nafia ◽  
Abdeljalil El Kari ◽  
Hassan Ayad ◽  
Mostafa Mjahed
Keyword(s):  
Tracking Control ◽  
Adaptive Systems ◽  
Sliding Mode ◽  
Physical Parameters ◽  
Control Law ◽  
Control Approach ◽  
Adaptive Fuzzy ◽  
Unknown Disturbances ◽  
The Stability ◽  
Interval Type

In this study, we develop a rigorous tracking control approach for quadrotor unmanned aerial vehicles (UAVs) with unknown dynamics, unknown physical parameters, and subject to unknown and unpredictable disturbances. In order to better estimate the unknown functions, seven interval type-2-adaptive fuzzy systems (IT2-AFSs) and five adaptive systems are designed. Then, a new IT2 adaptive fuzzy reaching sliding mode system (IT2-AFRSMS) which generates an optimal smooth adaptive fuzzy reaching sliding mode control law (AFRSMCL) using IT2-AFSs is introduced. The AFRSMCL is designed a way that ensures that its gains are efficiently estimated. Thus, the global proposed control law can effectively achieve the predetermined performances of the tracking control while simultaneously avoiding the chattering phenomenon, despite the approximation errors and all disturbances acting on the quadrotor dynamics. The adaptation laws are designed by utilizing the stability analysis of Lyapunov. A simulation example is used to validate the robustness and effectiveness of the proposed method of control. The obtained results confirm the results of the mathematical analysis in guaranteeing the tracking convergence and stability of the closed loop dynamics despite the unknown dynamics, unknown disturbances, and unknown physical parameters of the controlled system.

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