Cross-Coupling Controller for Five Degree-of-Freedom Coplanar Nanostage

2013 ◽  
Vol 284-287 ◽  
pp. 1788-1793
Author(s):  
Van Tsai Liu
Keyword(s):  
Tracking Control ◽  
Tracking Error ◽  
Cross Coupling ◽  
Degree Of Freedom ◽  
Creep Model ◽  
Contour Error ◽  
Viscoelastic Creep ◽  
Control Scheme ◽  
Optimization Parameters ◽  
Cross Coupling Control

The proposed approach is to design a tracking controller for five degree-of-freedom coplanar nanostage which can provide high precision applications. This study propose a viscoelastic creep model, it was modeled as a series connection of springs and dampers to describe the creep effect. Then, utilize a PI controller using Taguchi method to search the optimization parameters to suppress the tracking error. Finally, a cross-coupling control scheme is proposed to eliminate the contour error which is typical in dual-axes tracking control problem. The developed approaches are numerically and experimentally verified which demonstrate performance and applicability.

New Cross-Coupling Control of Independent Linear Contour Errors Based on Backlash

2010 ◽  
Vol 663-665 ◽  
pp. 902-905
Author(s):  
Sheng Bao Wang ◽  
Xiao Hong Liu
Keyword(s):  
Error Control ◽  
Cross Coupling ◽  
Contour Error ◽  
Contour Tracking ◽  
Control Scheme ◽  
New Strategy ◽  
Cross Coupling Control ◽  
Simulation Results ◽  
Contour Machining ◽  
Contour Error Control

On the basis of analysis of linear contour errors model, a new strategy of independent contour error control was presented for high precision contour machining. The proposed control scheme, in which the equations of the well-known cross-coupling controller were implemented, is shown to be able to diminish the linear contour error without using any cross-feeding signals between the driving axes. The simulation results show that the proposed control scheme is effective and that better effect of the contour tracking can be obtained. As a result, the contour machining precision is improved greatly.

Practical Tracking Control of a Class of Uncertain Surface Vessels Under Weak Assumptions on Uncertainties and Reference Trajectories

2021 ◽  
Author(s):  
Jian Li ◽  
Wenqing Xu ◽  
Zhaojing Wu ◽  
Yungang Liu
Keyword(s):  
Tracking Control ◽  
Broad Class ◽  
Tracking Error ◽  
Reference Trajectory ◽  
Unknown Parameters ◽  
Related Literature ◽  
Surface Vessels ◽  
Control Scheme ◽  
Reference Trajectories ◽  
Theoretical Results

Abstract This paper is devoted to the tracking control of a class of uncertain surface vessels. The main contributions focus on the considerable relaxation of the severe restrictions on system uncertainties and reference trajectory in the related literature. Specifically, all the system parameters are unknown and the disturbance is not necessarily to be differentiable in the paper, but either unknown parameters or disturbance is considered but the other one is excluded in the related literature, or both of them are considered but the disturbance must be continuously differentiable. Moreover, the reference trajectories in the related literature must be at least twice continuously differentiable and themselves as well as their time derivatives must be known for feedback, which are generalized to a more broad class ones that are unknown and only one time continuously differentiable in the paper. To solve the control problem, a novel practical tracking control scheme is presented by using backstepping scheme and adaptive technique, and in turn to derive an adaptive state-feedback controller which guarantees that all the states of the resulting closed-loop system are bounded while the tracking error arrives at and then stay within an arbitrary neighborhood of the origin. Finally, simulation is provided to validate the effectiveness of the proposed theoretical results.

Adaptive multi-dimensional Taylor network tracking control for a class of switched nonlinear systems with input nonlinearity

2020 ◽  
Vol 42 (13) ◽  
pp. 2482-2491
Author(s):  
Shan-Liang Zhu ◽  
De-Yu Duan ◽  
Lei Chu ◽  
Ming-Xin Wang ◽  
Yu-Qun Han ◽  
...  
Keyword(s):  
Nonlinear Systems ◽  
Tracking Control ◽  
Low Cost ◽  
Tracking Error ◽  
Switched Nonlinear Systems ◽  
Nonlinear Functions ◽  
Input Nonlinearity ◽  
Control Approach ◽  
Adaptive Tracking Control ◽  
Control Scheme

In this paper, a multi-dimensional Taylor network (MTN)-based adaptive tracking control approach is proposed for a class of switched nonlinear systems with input nonlinearity. Firstly, the input nonlinearity is assumed to be bounded by a sector interval. Secondly, with the help of MTNs approximating the unknown nonlinear functions, a novel adaptive MTN control scheme has the advantages of low cost, simple structure and real time feature is developed via backstepping technique. It is shown that the tracking error finally converges to a small domain around the origin and all signals in the closed-loop system are bounded. Finally, two examples are given to demonstrate the effectiveness of the proposed control scheme.

Servo Control System of NC Modifying Forming Grinding Wheel Based on Cross Coupling Theory

2013 ◽  
Vol 823 ◽  
pp. 80-83
Author(s):  
Hong Lu ◽  
Shi Tong Xie ◽  
You Wang
Keyword(s):  
High Precision ◽  
Dynamic Performance ◽  
External Disturbance ◽  
Servo System ◽  
Cross Coupling ◽  
Coupled System ◽  
Synchronization Control ◽  
Grinding Wheel ◽  
Control Scheme ◽  
Cross Coupling Control

This paper studies the synchronous control strategy which can meet certain dynamic performance and the closed loop robustness to external disturbance in servo system. This servo system has two same PMSMs which are used in a new CNC molding machine for forming grinding wheel. To achieve high-precision of the machine, we designed the hardware construction of the servo system. At the same time, this paper proposes a synchronization control scheme based on cross coupling control algorithms. The performance of the cross-coupled system is theoretically analyzed and simulated. It was proved that this synchronization control scheme has quick response, robustness and small dynamic process synchronization error, which could meet requirements of the high-precision synchronization control.

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.

Robust neural network control of MEMS gyroscope using adaptive sliding mode compensator

Robotica ◽  
2014 ◽  
Vol 34 (3) ◽  
pp. 497-512 ◽  
Author(s):  
Juntao Fei ◽  
Yuzheng Yang
Keyword(s):  
Neural Network ◽  
Upper Bound ◽  
Tracking Control ◽  
Sliding Mode ◽  
Tracking Error ◽  
Modeling Error ◽  
External Disturbances ◽  
Mems Gyroscope ◽  
Control Scheme ◽  
The Impact

SUMMARYA new robust neural sliding mode (RNSM) tracking control scheme using radial basis function (RBF) neural network (NN) is presented for MEMS z-axis gyroscope to achieve robustness and asymptotic tracking error convergence. An adaptive RBF NN controller is developed to approximate and compensate the large uncertain system dynamics, and a robust compensator is designed to eliminate the impact of NN modeling error and external disturbances for guaranteeing the asymptotic stability property. Moreover, another RBF NN is employed to learn the upper bound of NN modeling error and external disturbances, so the prior knowledge of the upper bound of system uncertainties is not required. All the adaptive laws in the RNSM control system are derived in the same Lyapunov framework, which can guarantee the stability of the closed loop system. Comparative numerical simulations for an MEMS gyroscope are investigated to verify the effectiveness of the proposed RNSM tracking control scheme.

scholarly journals Partial-State-Constrained Adaptive Intelligent Tracking Control of Nonlinear Nonstrict-Feedback Systems with Unmodeled Dynamics and Its Application

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yuzhuo Zhao ◽  
Ben Niu ◽  
Xiaoli Jiang ◽  
Ping Zhao ◽  
Huanqing Wang ◽  
...  
Keyword(s):  
Tracking Control ◽  
Tracking Error ◽  
Small Neighborhood ◽  
Unmodeled Dynamics ◽  
Feedback Systems ◽  
Feedback Form ◽  
Design Algorithm ◽  
Adaptive Tracking Control ◽  
Control Scheme ◽  
Nonlinear Uncertainties

In this paper, an adaptive intelligent control scheme is presented to investigate the problem of adaptive tracking control for a class of nonstrict-feedback nonlinear systems with constrained states and unmodeled dynamics. By approximating the unknown nonlinear uncertainties, utilizing Barrier Lyapunov functions (BLFs), and designing a dynamic signal to deal with the constrained states and the unmodeled dynamics, respectively, an adaptive neural network (NN) controller is developed in the frame of the backstepping design. In order to simplify the design process, the nonstrict-feedback form is treated by using the special properties of Gaussian functions. The proposed adaptive control scheme ensures that all variables involved in the closed-loop system are bounded, the corresponding state constraints are not violated. Meanwhile, the tracking error converges to a small neighborhood of the origin. In the end, the proposed intelligent design algorithm is applied to one-link manipulator to demonstrate the effectiveness of the obtained method.

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