scholarly journals Adaptive Output Feedback Tracking Controller Design of Stochastic Nonlinear Systems with Parameter Uncertainty for Polynomial Function Growth Conditions

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Long-Chuan Guo
Keyword(s):  
Nonlinear Systems ◽  
Output Feedback ◽  
Controller Design ◽  
Polynomial Function ◽  
Tracking Error ◽  
Parametric Uncertainty ◽  
Growth Conditions ◽  
Stochastic Nonlinear Systems ◽  
Tracking Controller ◽  
Feedback Tracking

This paper mainly focuses on output feedback practical tracking controller design for stochastic nonlinear systems with polynomial function growth conditions. Mostly, there are some studies on output feedback tracking control problem for general nonlinear systems with parametric certainty in existing achievements. Moreover, we extend it to stochastic nonlinear systems with parametric uncertainty and system nonlinear terms are assumed to satisfy polynomial function growth conditions which are more relaxed than linear growth conditions or power growth conditions. Due to the presence of unknown parametric uncertainty, an output feedback practical tracking controller with dynamically updated gains is constructed explicitly so that all the states of the closed-loop systems are globally bounded and the tracking error belongs to arbitrarily small interval after some positive finite time. An example illustrates the efficiency of the theoretical results.

scholarly journals Design of Constructive Controller of Nonlinear System Based on Polynomial Function Growth Condition and Its Application in Deep Subsea Energy Mining and Production Control System

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Longchuan Guo ◽  
Chuanping Zhou ◽  
Xiaoqing Tian ◽  
Huawei Ji ◽  
Yudong Peng
Keyword(s):  
Control System ◽  
Nonlinear System ◽  
Control Problem ◽  
Growth Condition ◽  
Output Feedback ◽  
Controller Design ◽  
Polynomial Function ◽  
Growth Conditions ◽  
Simulation Software ◽  
Tracking Controller

This paper mainly studies the output feedback control problem of the stochastic nonlinear system based on loose growth conditions and applies the research results to the valve control system of underwater oil and gas pipelines, which can improve the speed and stability of the equipment system. First, the concept of randomness is introduced to study the actual tracking control problem of output feedback of stochastic nonlinear systems, remove the original harsher growth conditions, make it meet the more general polynomial function growth conditions, and propose a combination of static and dynamic output feedback practices. The design of the tracking controller makes all the states of the system meet boundedness and ensures that the tracking error of the system converges to a small neighborhood of zero. Second, the system is extended to the parameter-uncertain system, and the output feedback tracking controller with complete dynamic gain is constructed by proving the boundedness of the system state and gain. Further, the time-delay factor is introduced, and the nonlinear term of the system satisfies the more relaxed power growth condition, combined with the inverse method to cleverly construct a set of Lyapunov functions and obtain the output controller to ensure that the system is asymptotically probabilistic in the global scope. Stability. Finally, through the ocean library in the Simulation X simulation software, the controller design results are imported into the underwater electro-hydraulic actuator model to verify the effectiveness of the controller design.

scholarly journals Output Tracking Control for High-Order Nonlinear Systems with Time Delay via Output Feedback Design

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 675
Author(s):  
Keylan Alimhan ◽  
Orken J. Mamyrbayev ◽  
Gaukhar A. Abdenova ◽  
Almira Akmetkalyeva
Keyword(s):  
Time Delay ◽  
Nonlinear Systems ◽  
Output Feedback ◽  
Tracking Error ◽  
High Order ◽  
Output Controller ◽  
Output Tracking ◽  
Output Tracking Control ◽  
Tracking Controller ◽  
Feedback Tracking

Design approach of an output feedback tracking controller is proposed for a class of high-order nonlinear systems with time delay. To deal with the time delays, an appropriate Lyapunov–Krasovskii the tracking analysis is ingeniously constructed, and an output feedback tracking controller is designed by using a homogeneous domination method. It is shown that the proposed output controller independent of time delay can make the tracking error be adjusted to be sufficiently small and render all the trajectory of the closed-loop system as bounded. An example is given to illustrate the effectiveness of the proposed method.

Optimal output-feedback tracking of SISO stochastic nonlinear systems using multi-dimensional Taylor network

2017 ◽  
Vol 40 (10) ◽  
pp. 3049-3058 ◽  
Author(s):  
Hong-Sen Yan ◽  
Yu-Qun Han ◽  
Qi-Ming Sun
Keyword(s):  
Nonlinear Systems ◽  
Real Time ◽  
Output Feedback ◽  
Learning Algorithm ◽  
Tracking Error ◽  
Tracking Performance ◽  
Stochastic Nonlinear Systems ◽  
Approximation Properties ◽  
Optimal Output ◽  
Feedback Tracking

The randomness and nonlinearity of stochastic nonlinear systems increase computational complexity and impede their tracking performance. However, randomness and nonlinearity are inevitable in practical applications, and the existing methods can hardly achieve the desirable control effect, especially in real-time control. For this end, a new network control strategy based on multi-dimensional Taylor network (MTN), whose design depends only on the system output, is put forward to solve the optimal output-feedback tracking problem of the SISO stochastic nonlinear systems. The network structure of the MTN is given first, and its approximation properties are proven. Based on the quadratic cost function design learning algorithm, the tracking error is minimized to update the controller parameters, and the desired tracking performance is obtained. Using the Lyapunov stability theorem, it is proved that the corresponding closed-loop system is bounded in the sense of probability and it can be ensured that the output tracking error converges to a small residual set around the origin in the sense of probability. An example is provided to illustrate the effectiveness of the proposed design approach. Comparative simulation study reveals that the proposed solution promises desirable real-time dynamic performance.

scholarly journals Direct Adaptive Tracking Control for a Class of Pure-Feedback Stochastic Nonlinear Systems Based on Fuzzy-Approximation

2014 ◽  
Vol 2014 ◽  
pp. 1-10
Author(s):  
Huanqing Wang ◽  
Xiaoping Liu ◽  
Qi Zhou ◽  
Hamid Reza Karimi
Keyword(s):  
Nonlinear Systems ◽  
Tracking Control ◽  
Controller Design ◽  
Tracking Error ◽  
Small Neighborhood ◽  
Adaptive Controller ◽  
Stochastic Nonlinear Systems ◽  
Fuzzy Logic Systems ◽  
Adaptive Tracking Control ◽  
Adaptive Tracking

The problem of fuzzy-based direct adaptive tracking control is considered for a class of pure-feedback stochastic nonlinear systems. During the controller design, fuzzy logic systems are used to approximate the packaged unknown nonlinearities, and then a novel direct adaptive controller is constructed via backstepping technique. It is shown that the proposed controller guarantees that all the signals in the closed-loop system are bounded in probability and the tracking error eventually converges to a small neighborhood around the origin in the sense of mean quartic value. The main advantages lie in that the proposed controller structure is simpler and only one adaptive parameter needs to be updated online. Simulation results are used to illustrate the effectiveness of the proposed approach.

scholarly journals Bounded Analysis and Practical Tracking Control of Complex Stochastic Nonlinear Systems with Unknown Control Coefficients

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Long-Chuan Guo ◽  
Xiang-Kun Fang
Keyword(s):  
Nonlinear Systems ◽  
Tracking Error ◽  
Upper And Lower Bounds ◽  
Design Parameters ◽  
Stochastic Nonlinear Systems ◽  
Tracking Controller ◽  
Unknown Control Coefficients ◽  
Unknown Control ◽  
Theoretical Results ◽  
Control Coefficients

This paper mainly focuses on the output practical tracking controller design for a class of complex stochastic nonlinear systems with unknown control coefficients. In the existing research results, most of the complex systems are controlled in a certain direction, which leads to the disconnection between theoretical results and practical applications. The authors introduce unknown control coefficients, and the values of the upper and lower bounds of the control coefficients are generalized by constants to allow arbitrary values to be arbitrarily large or arbitrarily small. In the control design program, the design problem of the controller is transformed into a parameter construction problem by introducing appropriate coordinate transformation. Moreover, we construct an output feedback practical tracking controller based on the dynamic and static phase combined by Ito stochastic differential theory and selection of appropriate design parameters, ensuring that the system tracking error can be made arbitrarily small after some large enough time. Finally, a simulation example is provided to illustrate the efficiency of the theoretical results.

scholarly journals Adaptive Fuzzy Fault-Tolerant Output Feedback Tracking Control of Uncertain Stochastic Nonlinear Systems with Unknown Time-Delay and Tracking Error Constrained

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Shuai Sui ◽  
Shaocheng Tong ◽  
Yongming Li
Keyword(s):  
Time Delay ◽  
Feedback Control ◽  
Nonlinear Systems ◽  
Output Feedback ◽  
Tracking Error ◽  
Output Feedback Control ◽  
Adaptive Observer ◽  
Stochastic Nonlinear Systems ◽  
Adaptive Fuzzy ◽  
Fuzzy Adaptive

The problem of tracking error constrained adaptive fuzzy output feedback control is investigated for a class of single-input and single-output (SISO) stochastic nonlinear systems with actuator faults, unknown time-delay, and unmeasured states. The considered faults are modeled as both loss of effectiveness and lock-in-place. The fuzzy logic systems are used to approximate the unknown nonlinear functions, and a fuzzy adaptive observer is designed for estimating the unmeasured states. By transforming the tracking errors into new virtual error variables and based on backstepping recursive design technique, a new fuzzy adaptive output feedback control method is developed. It is shown that all the signals of the resulting closed-loop system are bounded in probability and the tracking error remains an adjustable neighborhood of the origin within the prescribed bounds. The simulation results are provided to show the effectiveness of the proposed approach.

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