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Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
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Actor-Critic-Based Prescribed Performance Optimal Control for Flexible-Joint Robots With Input Delay.

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    This study introduces a new control method for flexible-joint robots facing input delays. The approach ensures faster, more accurate performance and stability using neural networks and reinforcement learning.

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    Area of Science:

    • Robotics
    • Control Systems
    • Artificial Intelligence

    Background:

    • Flexible-joint (FJ) robots present control challenges due to inherent flexibility and input delays.
    • Existing control methods struggle to guarantee stability and performance under these conditions.

    Purpose of the Study:

    • To develop a novel optimal control strategy for FJ robots with input delay.
    • To enhance tracking accuracy and convergence speed while ensuring system stability.
    • To address the optimal tracking problem using a simplified reinforcement learning approach.

    Main Methods:

    • Utilized auxiliary system and dynamic surface control for coordinate transformations to mitigate input delay effects.
    • Proposed a prescribed-time prescribed performance method to improve tracking accuracy and predetermine error convergence time.
    • Designed update laws for identifier, actor, and critic neural networks (NNs) using revised terms and prediction error.

    Main Results:

    • Successfully mitigated adverse effects of input delay on system stability.
    • Significantly enhanced transient and steady-state performance, improving tracking accuracy.
    • Demonstrated the effectiveness of the simplified reinforcement learning algorithm for optimal tracking in FJ robots.

    Conclusions:

    • The proposed prescribed performance optimal control method effectively addresses challenges in FJ robots with input delay.
    • The method achieves superior control performance with predetermined convergence times.
    • Simulation results validate the efficacy and robustness of the developed control scheme.