A Novel Higher-Order Model-Free Adaptive Control for a Class of Discrete-Time SISO Nonlinear Systems

2013 ◽  
Vol 135 (4) ◽  
Author(s):  
Shangtai Jin ◽  
Zhongsheng Hou ◽  
Ronghu Chi
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Discrete Time ◽  
Higher Order ◽  
Control Input ◽  
Order Model ◽  
Control Approach ◽  
Model Free ◽  
Input And Output ◽  
Control Scheme

In this work, a novel higher-order model-free adaptive control scheme is presented based on a dynamic linearization approach for a class of discrete-time single input and single output (SISO) nonlinear systems. The control scheme consists of an adaptive control law, a parameter estimation law, and a reset mechanism. The design and analysis of the proposed control approach depends merely on the measured input and output data of the controlled plant. The control performance is improved by using more information of control input and output error measured from previous sampling time instants. Rigorous mathematical analysis is developed to show the bounded input and bounded output (BIBO) stability of the closed-loop system. Two simulation comparisons show the effectiveness of the proposed control scheme.

scholarly journals A New Data-Driven Model-Free Adaptive Control for Discrete-Time Nonlinear Systems

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 126224-126233
Author(s):  
Kai Deng ◽  
Fanbiao Li ◽  
Chunhua Yang
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Discrete Time ◽  
Data Driven ◽  
Model Free

scholarly journals Compact Model-Free Adaptive Control Algorithm for Discrete-Time Nonlinear Systems

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 141062-141071 ◽  
Author(s):  
Xiaofei Zhang ◽  
Hongbin Ma ◽  
Xinghong Zhang ◽  
You Li
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Discrete Time ◽  
Control Algorithm ◽  
Compact Model ◽  
Model Free ◽  
Adaptive Control Algorithm

Modified Model-Free Adaptive Control Method Applied to Vibration Control of an Elastic Crane

2019 ◽  
Author(s):  
Hoang Anh Pham ◽  
Dirk Söffker
Keyword(s):  
Adaptive Control ◽  
Control Method ◽  
Structural Information ◽  
Control Strategies ◽  
Control Input ◽  
Tracking Errors ◽  
Adaptive Controllers ◽  
Control Approach ◽  
Model Free ◽  
Controlled Systems

Abstract Model-free adaptive control (MFAC) is a data-driven control approach receiving increased attention in the last years. Different model-free-based control strategies are proposed to design adaptive controllers when mathematical models of the controlled systems should not be used or are not available. Using only measurements (I/O data) from the system, a feedback controller is generated without the need of any structural information about the controlled plant. In this contribution an improved MFAC is discussed for control of unknown multivariable flexible systems. The main improvement in control input calculation is based on the consideration of output tracking errors and its variations. A new updated control input algorithm is developed. The novel idea is firstly applied for controlling vibrations of a MIMO ship-mounted crane. The control efficiency is verified via numerical simulations. The simulation results demonstrate that vibrations of the elastic boom and the payload of the crane can be reduced significantly and better control performance is obtained when using the proposed controller compared to standard model-free adaptive and PI controllers.

scholarly journals Design of decentralized adaptive control approach for large-scale nonlinear systems subjected to input delays under prescribed performance

2021 ◽  
Author(s):  
Yu-Qun Han
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
Large Scale ◽  
Control Method ◽  
Performance Control ◽  
Prescribed Performance ◽  
Control Approach ◽  
Prescribed Performance Control ◽  
Control Scheme ◽  
Input Delays

Abstract For the first time, the issue of input delays and prescribed performance control is investigated in the same framework for large-scale nonlinear systems in this study, and a original adaptive decentralized control method is proposed take advantage of multi-dimensional Taylor network (MTN) method. Firstly, the problem of input delays is solved by introducing new variables, and a new form of coordinate transformation is introduced before controller design, which simplified the control system. Secondly, the problem of prescribed performance control is coped with by integrating the idea of prescribed performance into the Lyapunov functions of first step of backstepping of each subsystem. Thirdly, MTNs are employed to evaluate the combination of unknown functions, and then a decentralized MTN-based adaptive control scheme is developed by way of backstepping technology. The theoretical analysis indicates that the proposed control scheme can implement the expected tracking goals under the condition of meeting the prescribed performance control. Finally, one numerical example is given to show the validity and rationality of the proposed control method.

Sign in / Sign up

Export Citation Format

Share Document