Modern Control Laws for an Articulated Robotic Arm: Modeling and Simulation

Abstract

The robotic manipulator has become an integral component of modern industrial automation. The current paper deals with the mathematical modeling and non-linear control of this manipulator. DH-parameters are used to derive kinematic model while the dynamics is based on Euler-Lagrange equation. Two modern control strategies, H∞ and model predictive control (MPC), are investigated to develop the control laws. For an optimal performance, the controllers have been fine-tuned through a simulation conducted in MATLAB/Simulink environment. The designed control laws are subjected to various inputs and tested for effectiveness in transient parameters like settling time and overshoot as well as steady state error. Simulation results confirm the effectiveness of the developed controllers by precisely tracking the reference motion trajectories.

Response Time Estimation in Robotics Using Hierarchical Performance Modeling Approach

“…The forward kinematics of AUTAREP manipulator is derived in [11] while the inverse kinematics model is presented in [10].…”

Trajectory Tracking Control Design of a Mass-Damping-Spring System with Uncertainty using the Bond Graph Approach

“…Physical systems vary from linear [15] to non-linear [16] and may or may not vary in time with several control techniques to regulate or track trajectory, leading to several control laws which may be linear such as the LQR control [17], LQR control based on bond graph model [18], PID and Intelligent PID control [19], and nonlinear control in several techniques based on graphical model (bond graph) [20][21], mathematical model (CTC, VSC, backstepping, H ∞ , MPC, etc.) [22][23][24], or intelligent and meta-heuristic model optimization [19,[25][26], etc. [27][28].…”

Enhancement in pneumatic positioning system using nonlinear gain constrained model predictive controller: experimental validation

“…MPC can considers the constraints, deals with multivariable control issue, and also suitable for single-input and single-output (SISO) system and multi-input and multi-output (MIMO) system [10]- [12], which explain why it is highly favourable in the process industries. MPC is also reported used to control robots [13], [14]. Figure 1 shows the basic structure of MPC.…”