Adaptive disturbance cancellation for a class of MIMO nonlinear Euler-Lagrange systems under input saturation

Area of Science:

• Robotics and Control Systems
• Nonlinear System Dynamics
• Adaptive Control Theory

Background:

• Euler-Lagrange systems are fundamental in robotics and mechanics but are susceptible to unknown time-varying disturbances.
• Input saturation presents a significant challenge in practical control system design, limiting actuator capabilities.
• Existing control methods often struggle to simultaneously address unknown disturbances and input saturation in complex systems.

Purpose of the Study:

• To develop an adaptive disturbance cancellation tracking control strategy for multi-input, multi-output (MIMO) nonlinear Euler-Lagrange systems.
• To address challenges posed by unknown time-varying disturbances and input saturation.
• To achieve asymptotically converging output tracking errors and guaranteed system stability.

Main Methods:

• An observer was constructed to estimate unavailable regressors for disturbance cancellation, converting the problem into an adaptive control task.
• An auxiliary dynamic system (ADS) was employed to mitigate the effects of input saturation.
• A robust adaptive tracking control law was designed using adaptive vectorial backstepping, incorporating a robustifying term.

Main Results:

• The proposed control strategy guarantees asymptotic convergence of output tracking errors for the Euler-Lagrange systems.
• Uniform ultimate boundedness of all signals in the closed-loop control system is theoretically proven.
• Simulations on a two-link rigid manipulator and a scale model ship demonstrate the effectiveness and superiority of the proposed scheme.

Conclusions:

• The developed adaptive disturbance cancellation strategy effectively handles unknown disturbances and input saturation in MIMO nonlinear Euler-Lagrange systems.
• The control scheme ensures precise tracking performance with guaranteed stability, validated through theoretical analysis and simulations.
• This work offers a robust and effective solution for advanced control applications in robotics and other dynamic systems.