Model Predictive Control Of 3-Dof Articulated Robotic Manipulator

Abstract

Many Researches Has Been Done On Robotic Manipulator. Robotic Manipulators Are Used For Jobs That Are Too Dirty, Dangerous, Repetitive For Humans To Perform. Due To These Reasons, Robotic Manipulator Research Is One Of The Most Fascinating And Exiting Fields In Industrial Technology. Robotic Manipulators Are Nonlinear Systems With Many Inputs And Outputs, Parametric Variation, External Disturbance, And A Dynamic Capability That Changes Rapidly. The Most Difficult Difficulties To Control And Track In Robotic Trajectory Tracking Are Uncertainty And Time-Varying Dynamic Systems. Denavit-Hartenberg Parameters And Rotation Matrix Around Axis?�?S Are Employed For Forward Kinematics In This Thesis, Whereas Algebraic Technique Is Used For Inverse Kinematics Of Three Degree Of Freedom (3-DOF) Robots. The Non-Linear Dynamics Equation Of Motion Of The 3-DOF Industrial Articulated Robot Is Examined Using The Euler-Lagrange Equation Of Motion. Because Of The System's Dynamic Model Is Nonlinear, The Feedback Linearization Approach Is Used To Create A Linear System. A Predictive Control Law With A Minimizing Objection Function Is Then Built For The Obtained Linear Model. The Settings Of The Model Predictive Control (MPC) Controller Were Fine-Tuned Utilizing Torque Constraint Analytic Studies, And A Second Order System Was Considered For It. The Controller Obtained The Intended Outcome In MATLAB/Simulink Software. Step, Ramp And Sine Wave Tracking Are Discussed For Proposed MPC Controller. The Suggested Controller Is An Improved Approach Of Process Control That Uses Little Effort To Track A Process With Optimum Parameter While Satisfying Input Constraints And Reduced Tracking Error. To Evaluate The Applicability Of The Recommended Control Technique With Proportional Integral Derivative Genetic Algorithm (PIDGA) Controller, A Simulation And Results Analysis Are Provided. For The 1st, 2nd And 3rd Joint, The Maximum Energy Required To Track The Desired Signal For PIDGA And MPC Is 24.8649 Nm, -8.8917 Nm, -7.3159 Nm And 22.9040 Nm, -8.4805 Nm, -6.3049 Nm Respectively. The Maximum Overshoot Happened To Control The 1st, 2nd And 3rd Joint Articulation For PIDGA And MPC Controller Is 3.7214%, 5.9657%, 4.0252% And 0.275%, 0.275%, 0.275% Respectively. According To The Results, The Proposed MPC Controller Outperforms The PIDGA Controller In Terms Of Performance Tracking And Energy Used.