Implementation of Nonlinear Adaptive U-Model Control Synthesis Using a Robot Operating System for an Unmanned Underwater Vehicle

Nur Afande Ali Hussain,Syed Saad Azhar Ali,Ubaid M Al-Saggaf,Patryk Cieslak,Pere Ridao

doi:10.1109/access.2020.3037122

Nur Afande Ali Hussain, Syed Saad Azhar Ali + Show 3 more

Open Access

https://doi.org/10.1109/access.2020.3037122

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Abstract

This paper presents the development of unmanned marine robotic control modelling and control synthesis using a coupled multivariable underactuated nonlinear adaptive U-model approach. The proposed controller was developed using thru an open source robot operating system (ROS) platform. The new adaptive coupled U-model based internal model control (IMC) node was successfully developed and tested. The proposed controller demonstrated the simplicity of the control synthesis process and the implementation of the mathematical algorithm in real-time. The controller was compared with the proven existing GIRONA 500 UUV for real-time performance. The ROS environment provides fast and reliable controller design and development compared to conventional software architecture. Simulation and real-time experiment were conducted using ROS via the GIRONA 500 UUV platform and compared with a PID mission controller. A new ROS node of nonlinear adaptive U-model based IMC was developed using ROS. The results showed good control signal convergence and tracking performance between the plant or system model with the proposed method.

Highlights

Most of the autonomous unmanned underwater vehicle (UUV) control systems are multivariable
SIMULATION RESULTS The simulation results of the GIRONA 500 UUV implementing an adaptive nonlinear internal model control (IMC)-based U-model algorithm and a comparison with the existing GIRONA 500 UUV workable mission PID controller are shown in Fig. 9 to Fig. 12
The nonlinear IMC based U-model approach only required a suitable initial condition range from 0 to 1 for all the parameters, weights, and appropriate learning rate values for better stability and convergence speed. This nonlinear control approach can minimise the time duration of the controller design by implementing an adaptive learning rate method for the unknown control system compared with the PID control approach

Summary

INTRODUCTION

Most of the autonomous unmanned underwater vehicle (UUV) control systems are multivariable. It is desirable to have a control structure that is capable of overcoming external disturbances without involving a complex mathematical and modelling approach that can be demonstrated through simulation but in real-time implementation as well. An adaptive fuzzy sliding mode controller was proposed to estimate the nonlinearity of MIMO underwater vehicles in [11] through a simulation approach This method was the combination of two different nonlinear controllers aimed to counter the dynamics and chatter effect from the sliding mode control and from external disturbances. In [4], a trajectory 3-D tracking control system was addressed for an UUV with a prescribed performance under model uncertainties and external disturbances through simulation and real-time implementation. The controller was compared with the proven existing GIRONA 500 UUV controller for the validation process

APPROACH AND METHODS

DOF position update

CONCLUSION