scholarly journals Antidisturbance Control for Helicopter Stochastic Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-28
Author(s):  
Dongping Li ◽  
Yankai Li
Keyword(s):  
Nonlinear Control ◽  
Stochastic Systems ◽  
Control Method ◽  
Stochastic Theory ◽  
Nonlinear Controller ◽  
Closed Loop System ◽  
Nonlinear Disturbance Observer ◽  
Control Techniques ◽  
Control Scheme ◽  
Nonlinear Control Method

In this paper, an antidisturbance controller is presented for helicopter stochastic systems under disturbances. To enhance the antidisturbance abilities, the nonlinear disturbance observer method is applied to reject the time-varying disturbances. Then, the antidisturbance nonlinear controller is designed by combining the backstepping control scheme. And the stochastic theory is used to guarantee that the closed-loop system is asymptotically bounded in mean square while the proposed control method is shown via some traditional nonlinear control techniques, which still show some common issues such as “dimension explosion” or others. The result of this paper can be regarded as a typical case of the nonlinear control method to help and promote the generation of advanced methods.

scholarly journals Adaptive Nonlinear Control of A Synchronous Generator

2018 ◽  
Vol 11 (2) ◽  
pp. 39-43
Author(s):  
Moulay Fatima ◽  
Habbatti Assia ◽  
Hamdaoui Habib
Keyword(s):  
Nonlinear Control ◽  
State Feedback ◽  
Control Method ◽  
Dynamic Performance ◽  
Synchronous Generator ◽  
Adaptive Nonlinear Control ◽  
Control Scheme ◽  
High Dynamic ◽  
Nonlinear Control Method ◽  
Initial Results

Abstract In this work, an adaptive nonlinear control method, was applied to a synchronous generator and we give some initial results on the adaptive control of nonlinear systems which are exactly input-output linearizable by state feedback. Parameters adaptation is used as a technique to robustify the exact cancelation of nonlinear terms, which is called for the linearization technique. The performance of the proposed adaptive nonlinear control scheme is demonstrated by simulation results. These results show that the proposed method achieves the same high dynamic performance as vector control.

scholarly journals Design and Nonlinear Control of a 2-DOF Flexible Parallel Humanoid Arm Joint Robot

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Leijie Jiang ◽  
Bingtuan Gao ◽  
Zhenyu Zhu
Keyword(s):  
Nonlinear Control ◽  
Shoulder Joint ◽  
Control Method ◽  
Parallel Robot ◽  
Control Scheme ◽  
Flexible Parts ◽  
Parallel Robot Platform ◽  
Flexible Deformation ◽  
Nonlinear Control Method ◽  
Robot Platform

The paper focuses on the design and nonlinear control of the humanoid wrist/shoulder joint based on the cable-driven parallel mechanism which can realize roll and pitch movement. In view of the existence of the flexible parts in the mechanism, it is necessary to solve the vibration control of the flexible wrist/shoulder joint. In this paper, a cable-driven parallel robot platform is developed for the experiment study of the humanoid wrist/shoulder joint. And the dynamic model of the mechanism is formulated by using the coupling theory of the flexible body’s large global motion and small flexible deformation. Based on derived dynamics, antivibration control of the joint robot is studied with a nonlinear control method. Finally, simulations and experiments were performed to validate the feasibility of the developed parallel robot prototype and the proposed control scheme.

scholarly journals The Adaptive Neural Control for a Class of High-Order Uncertain Stochastic Nonlinear Systems

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Xiaoyan Qin
Keyword(s):  
Nonlinear Systems ◽  
Neural Control ◽  
Closed Loop ◽  
Control Method ◽  
High Order ◽  
Stochastic Nonlinear Systems ◽  
Closed Loop System ◽  
Adaptive Neural Control ◽  
Control Scheme ◽  
Approximation Capability

This paper studies the problem of the adaptive neural control for a class of high-order uncertain stochastic nonlinear systems. By using some techniques such as the backstepping recursive technique, Young’s inequality, and approximation capability, a novel adaptive neural control scheme is constructed. The proposed control method can guarantee that the signals of the closed-loop system are bounded in probability, and only one parameter needs to be updated online. One example is given to show the effectiveness of the proposed control method.

scholarly journals Experimental Implementation of a Nonlinear Control Method for Magnetostrictive Transducers

2006 ◽  
Author(s):  
William S. Oates ◽  
Phillip Evans ◽  
Ralph C. Smith ◽  
Marcelo J. Dapino
Keyword(s):  
Nonlinear Control ◽  
Control Method ◽  
Experimental Implementation ◽  
Nonlinear Control Method

A Nonlinear Control Method for Bumpless Mode Transition in Noninverting Buck–Boost Converter

2021 ◽  
Vol 36 (2) ◽  
pp. 2166-2178
Author(s):  
Xing Weng ◽  
Zhengming Zhao ◽  
Kainan Chen ◽  
Liqiang Yuan ◽  
Ye Jiang
Keyword(s):  
Nonlinear Control ◽  
Control Method ◽  
Boost Converter ◽  
Mode Transition ◽  
Nonlinear Control Method

Composite hierarchical anti-disturbance control for stochastic systems with multiple disturbances

2017 ◽  
Vol 40 (6) ◽  
pp. 1950-1955 ◽  
Author(s):  
Shixiang Sun ◽  
Xinjiang Wei ◽  
Huifeng Zhang
Keyword(s):  
Disturbance Observer ◽  
Closed Loop ◽  
Stochastic Systems ◽  
Time Derivative ◽  
Closed Loop System ◽  
Stochastic Disturbance ◽  
Multiple Disturbances ◽  
Control Scheme ◽  
Bounded Disturbance ◽  
White Noises

A class of stochastic systems with multiple disturbances, which includes white noises and disturbances whose time derivative is bounded, is considered in this paper. To estimate the unknown bounded disturbance, a stochastic disturbance observer is proposed. Based on the observer, a disturbance observer-based disturbance control scheme is constructed such that the composite closed-loop system is asymptotically bounded. Finally, a simulation example is given to demonstrate the feasibility and effectiveness of the proposed scheme.

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