Robust Control Based on Suboptimal Estimator for Highly Nonlinear Robotic Arms Influenced Model Uncertainties and Environmental Disturbance

Document Type : Dynamics, Vibrations, and Control

Authors

1 Corresponding author: Assistant Professor, Department of Science and Technology Studies, AJA Command and Staff University, Tehran, Iran

2 Ph.D. Candidate, Faculty of Mechanical Engineering, Iran University of Science and Technology, Tehran, Iran.

3 Assistant Professor, Department of Science and Technology Studies, AJA Command and Staff University, Tehran, Iran

Abstract

One of the main challenges of using robotic arms in various industrial applications such as: production and assembly line, medical and surgical centers, space industries and military instruments is the lack of accurate modeling and control of the systems. In this paper, the problem of robust control based on the suboptimal estimator for highly nonlinear dynamic systems affected by systemic and environmental uncertainties is addressed. Considering the coupled electrical-driven and mechanical subsystems in modeling leads to a completer and more realistic model known as the electrical flexible joint robots (EFJR). The state-dependent Riccati equation estimator is used to determine unknown state variables that cannot be measured by sensors. By applying the proposed approach in simulating a two degree-of-freedom (DOF) arm with electrically flexible joints as a practical case study, both robustness and optimality are obtained for the system. Then, the proposed method is compared to the sliding mode control and the Kalman filter estimator. The obtained results indicate that the proposed method has improved the system robustness against uncertainty and disturbance. The norm of final error of the robot End-effector has been obtained as 4.13 mm and 37.02 mm in the proposed algorithm and Kalman filter method, respectively. Also, the norm of control input (energy consumption) has been obtained as 7.5 and 16.8 by the two methods, respectively. Therefore, the proposed method provides the possibility of achieving to the goal with a higher accuracy and less control effort.

Highlights

  • Applying robust controller based on suboptimal estimator
  • Ensuring the stability of the proposed controller along with the convergence analysis of the estimation error
  • Flexible design of the control system, by parametrized matrices depending on the non-unique state and adjustable weight matrices

Keywords

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References

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Aerospace Mechanics
Volume 19, Issue 4 - Serial Number 74
December 2023
Pages 85-101

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History

  • Receive Date: 29 March 2023
  • Revise Date: 25 April 2023
  • Accept Date: 17 May 2023
  • Publish Date: 23 August 2023

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