Optimal v/s robust control: A study and comparison for articulated manipulator

Highly nonlinear and coupled dynamics of a robotic manipulator demands sophisticated control strategies. These strategies must have the ability to handle the uncertainties and external disturbances that can significantly deviate the system from its desired response. Considering a 6 Degree Of Freedom (DOF) serial robotic manipulator, this paper presents the design and realisation of Linear Quadratic Regulator (LQR) and Variable Structure Control (VSC) which are respectively optimal and robust control strategies. The novelty of the present research lies in the hardware implementation of both strategies on an in-house developed AU-Tonomous Articulated Robotic Educational Platform (AUTAREP). The platform is subjected to various test inputs to characterise the tracking performance of the derived control laws. The comparative results demonstrate that VSC outperforms than LQR

A comprehensive state-of-the-art on control of industrial articulated robots

Incredible applications of robotic manipulators especially in the industrial sector have drawn attention to substitute classical control techniques with more sophisticated intelligent approaches. This, consequently, has motivated robotics community to formulate a multi-disciplinary domain of 'robot control'. Highlighting the authors' contributions in this domain, this paper presents a systematic review of control strategies for multi-Degree Of Freedom (DOF) robotic manipulators. Trivial linear approach, i.e. Proportional-Integral-Derivative (PID) control is briefly commented. Given the fact that a manipulator has a complex structure because of associated nonlinear dynamics and uncertain parameters, robust and nonlinear control techniques have been discussed in detail. These mainly include Computed Torque Control (CTC), Sliding Mode Control (SMC), Disturbance Observer Based Control (DOBC), Model Predictive Control (MPC), Linear Quadratic Regulator (LQR), H∞ control and Passivity Based Control (PBC). With a tabulated pros and cons of each of these techniques, it is expected that the survey will directly boost cutting-edge research on the subject topic by facilitating engineers, researchers and industrial-interns to realize control laws for sophisticated applications that demand accuracy, precision, repeatability, mass production and quality

Development of vision-based object tracking fish robot

This paper focuses on the development and vision-based object tracking control of a fish robot. Its efficiency towards target tracking is demonstrated in a water tank. Inspired by the maneuvering and stability of Tuna fish, the fish robot is designed by a single actuator located at the rare part of the fish body. The precise maneuverability characteristics of the fish robot is achieved by the motion of a caudal fin. A servomotor is involved to control the oscillation of the caudal fin. A vision-sensor is integrated into fish robot to gain information related to Cartesian coordinates of the targeted object by implementing a color-based filtering algorithm. An object tracking algorithm is designed which performs the decision-making task for the fish robot while identifying and following the targeted object. The locomotion of the fish robot in various directions is tested experimentally by achieving effective performance of the proposed targeted object following task