Enhanced the Control Strategy of a Triple Link Robotic System (Robogymnast)

This research aims to optimise performance in a Fuzzy Linear Quadratic Regulator controller by implementing 2 types of algorithm to stabilise the triple-link 'Robogymnast' robotic system. The Robogymnast recreates the movements of a human gymnast, with the hand/arm element of the system securely attached to a high bar with ball0bearing mountings, which can rotate freely. This article explores the complex factors involved in swing-up control in the underactuated Robogymnast and presents a linearisation of the mathematical modelling for the system, considering methods which apply Lagrangian equations in defining state space in such systems. Both the Teaching-Learning-Based Optimization (TLBO) and Particle Swarm Optimization (PSO) algorithm were used for tuning the hybrid Fuzzy Linear Quadratic Regulator controller for later application with the robot and assessment of response stability. In addition, MATLAB Simulink was used to simulate performance and show the effect of altering parameters including time for rising, settling and overshoot. This work aims primarily to explore how a Linear Quadratic Regulator/Fuzzy Logic controller can be applied with acrobatic robots.

Automated summary

This research aims to optimize the performance of a Fuzzy Linear Quadratic Regulator controller in a triple-link 'Robogymnast' robotic system. The study explores the complex factors involved in swing-up control and presents a linearized mathematical model for the system. Two algorithms, Teaching-Learning-Based Optimization (TLBO) and Particle Swarm Optimization (PSO), were used to tune the hybrid controller for stability assessment. MATLAB Simulink was also employed for performance simulation. The work primarily focuses on applying a Linear Quadratic Regulator/Fuzzy Logic controller in acrobatic robots.