scholarly journals Tracking Control of High Order Input Reference Using Integrals State Feedback and Coefficient Diagram Method Tuning

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 182731-182741
Author(s):  
Alfian Ma'Arif ◽  
Adha Imam Cahyadi ◽  
Samiadji Herdjunanto ◽  
Oyas Wahyunggoro
Keyword(s):  
Tracking Control ◽  
State Feedback ◽  
High Order ◽  
Diagram Method ◽  
Coefficient Diagram Method

scholarly journals Aircraft Flight Stabilizer System by CDM Designed Servo State-Feedback Controller

Aerospace ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 45
Author(s):  
Ekachai Asa ◽  
Yoshio Yamamoto
Keyword(s):  
Flight Control ◽  
State Feedback ◽  
Controller Design ◽  
Nonlinear Models ◽  
Feedback System ◽  
Flight Control System ◽  
Diagram Method ◽  
Performance Requirement ◽  
Directional Motion ◽  
Coefficient Diagram Method

This research presents an automatic flight control system whose advantage is its ease of modification or maintenance while still effectively meeting the system’s performance requirement. This research proposes a mixed servo state-feedback system for controlling aircraft longitudinal and lateral-directional motion simultaneously based on the coefficient diagram method or CDM as the controller design methodology. The structure of this mixed servo state-feedback system is intuitive and straightforward, while CDM’s design processes are clear. Simulation results with aircraft linear and nonlinear models exhibit excellent performance in stabilizing and tracking the reference commands for both longitudinal and lateral-directional motion.

scholarly journals Prescribed Performance Tracking Control for High-Order Uncertain Nonlinear Systems

2022 ◽  
Author(s):  
Jiling Ding ◽  
Weihai Zhang
Keyword(s):  
Nonlinear Systems ◽  
Tracking Control ◽  
State Feedback ◽  
Low Complexity ◽  
High Order ◽  
State Feedback Control ◽  
Uncertain Nonlinear Systems ◽  
Prescribed Performance ◽  
Approximation Techniques ◽  
Performance Tracking

Abstract This paper considers the prescribed performance tracking control for high-order uncertain nonlinear systems. For any initial system condition, a state feedback control is designed, which guarantees the prescribed tracking performance and the boundedness of closed-loop signals. The proposed controller can be implemented without using any approximation techniques for estimating unknown nonlinearities. In this respect, a significant advantage of this article is that the explosion of complexity is avoided, which is raised by backstepping-like approaches that are typically employed to the control of uncertain nonlinear systems, and a low-complexity controller is achieved. Moreover, contrary to the existing results in existing literature, the restrictions on powers of high-order nonlinear systems are relaxed to make the considered problem having stronger theoretical and practical values. The effectiveness of the proposed scheme is verified by some simulation results.

Decentralized adaptive tracking control for high-order interconnected stochastic nonlinear time-varying delay systems with stochastic input-to-state stable inverse dynamics by neural networks

2019 ◽  
Vol 41 (13) ◽  
pp. 3612-3625 ◽  
Author(s):  
Wang Qian ◽  
Wang Qiangde ◽  
Wei Chunling ◽  
Zhang Zhengqiang
Keyword(s):  
Neural Networks ◽  
Tracking Control ◽  
Large Scale ◽  
Inverse Dynamics ◽  
Small Neighborhood ◽  
High Order ◽  
Interconnected Systems ◽  
Delay Systems ◽  
Rbf Neural Networks ◽  
Stochastic Input

The paper solves the problem of a decentralized adaptive state-feedback neural tracking control for a class of stochastic nonlinear high-order interconnected systems. Under the assumptions that the inverse dynamics of the subsystems are stochastic input-to-state stable (SISS) and for the controller design, Radial basis function (RBF) neural networks (NN) are used to cope with the packaged unknown system dynamics and stochastic uncertainties. Besides, the appropriate Lyapunov-Krosovskii functions and parameters are constructed for a class of large-scale high-order stochastic nonlinear strong interconnected systems with inverse dynamics. It has been proved that the actual controller can be designed so as to guarantee that all the signals in the closed-loop systems remain semi-globally uniformly ultimately bounded, and the tracking errors eventually converge in the small neighborhood of origin. Simulation example has been proposed to show the effectiveness of our results.

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