Modified Model-Free Adaptive Control using Compact-Form Dynamic Linearization Technique

The design of an accurate model often appears as the most challenging tasks for control engineers especially focusing to the control of nonlinear systems with unknown parameters or effects to be identified in parallel. For this reason, development of model-free control methods is of increasing importance. The class of model-free control approaches is defined by the non-use of any knowledge about the underlying structure and/or related parameters of the dynamical system. Therefore the major criteria to evaluate model-free control performance are aspects regarding robustness against unknown inputs and disturbances to achieve a suitable tracking performance including ensuring stability. Consequently it is assumed that the system plant model to be controlled is unknown, only the inputs and outputs are used as measurements. In this contribution a modified model-free adaptive approach is given as the extended version of existing model-free adaptive control to improve the performance according to the tracking error at each sample time. Using modified model-free adaptive controller, the control goal can be achieved efficiently without an individual control design process for different kinds unknown nonlinear systems. The main contribution of this paper is to extend the modified model-free adaptive control method to unknown nonlinear multi-input multi-output (MIMO) systems. A numerical example is shown to demonstrate the successful application and performance of this method.

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Unmanned surface vessel heading control of model-free adaptive method with variable integral separated and proportion control

International Journal of Advanced Robotic Systems ◽

10.1177/1729881419831584 ◽

2019 ◽

Vol 16 (3) ◽

pp. 172988141983158

Author(s):

Quanquan Jiang ◽

Yulei Liao ◽

Ye Li ◽

Yugang Miao ◽

Wen Jiang ◽

...

Keyword(s):

Adaptive Control ◽

Separation Factor ◽

Control Method ◽

Compact Form ◽

Proportional Control ◽

Model Free ◽

Heading Control ◽

Unmanned Surface Vessel ◽

Integral Separation ◽

Surface Vessel

Based on model-free adaptive control theory, the heading control problem of unmanned surface vessels under uncertain influence is explored. Firstly, the problems of compact form dynamic linearization model-free adaptive control method applied to unmanned surface vessel heading control are analyzed. Secondly, by introducing proportional control and variable integral separation factor, an variable integral separation model-free adaptive control algorithm with proportional control is proposed. The introduction of proportional control and variable integral separation factor solves the problems of oscillation, instability, and integral saturation when rudder angle is controlled directly to control the heading of unmanned surface vessel with compact form dynamic linearization model-free adaptive control method. Finally, the effectiveness of the method is verified by the simulation and field experiments results of heading control with model perturbation and system time delay in unmanned surface vessel heading subsystem.

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