
Control of master slave robotics system using optimal control schemes
Author(s) -
Sara A. Rashad,
Mohamed Sallam,
A. M. Bassiuny,
Α. M. Abdel Ghany
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/610/1/012056
Subject(s) - pid controller , control theory (sociology) , teleoperation , settling time , computer science , genetic algorithm , control engineering , matlab , robotics , stability (learning theory) , tracking error , scheme (mathematics) , control system , robot , control (management) , engineering , artificial intelligence , mathematics , step response , temperature control , electrical engineering , machine learning , operating system , mathematical analysis
This paper presents application of Proportional Integral Derivative (PID) and Non-linear PID (NPID) controllers to optimally operate the master slave robotic system. Teleoperation is widely used in different applications, such as surgical robots, underwater vehicles, power lines and even in space. However there are problems in teleoperation systems that may lead to degradation in system performance or even to system instability. This paper presents new and optimal control schemes that can satisfy the required performance, insure system stability and achieve zero tracking error in presence of constant time delay and model approximation. Optimal gains are obtained using the Genetic Algorithm in a systematic way that could be applied to other control schemes. The results proved the effectiveness of both control schemes than the previously applied scheme. The NPID control scheme has better performance, provided position tracking and achieved zero tracking error in less settling time than PID one. The results obtained by the presented control schemes are evaluated based on comparing the system performance using three different types of controllers which are P-like, Genetic PID and Genetic NPID. The study was carried out using MATLAB/SIMULINK 2017a.