Sensors Allocation and Observer Design for Discrete Bilateral Teleoperation Systems with Multi-Rate Sampling

Area of Science:

• Robotics
• Control Systems Engineering
• Signal Processing

Background:

• Existing research on teleoperation systems primarily focuses on continuous-time models.
• Practical challenges like data-swapping and varying sampling/refresh rates are often overlooked.
• Discrete-time teleoperation systems require specific stability analysis considering these practical factors.

Purpose of the Study:

• To develop a sensor allocation strategy for discrete-time teleoperation systems.
• To analyze and guarantee exponential stability under multi-rate sampling conditions.
• To address hardware limitations in isolated master and slave robotic systems.

Main Methods:

• Implementation of a multi-rate sampling approach for data acquisition.
• Assignment of position and velocity signals to sensors with diverse sampling rates.
• Utilization of Krasovskii-based conditions and linear matrix inequalities (LMIs) for stability analysis.
• Design of observers to ensure exponential convergence of estimation errors.

Main Results:

• Sufficient conditions derived to ensure exponential stability of the multi-rate sampled-data teleoperation system.
• The sensor allocation problem is formulated as a mixed-integer program.
• Observers designed for multi-rate systems demonstrate exponential error convergence.
• Numerical simulations validate the proposed methodology.

Conclusions:

• The proposed multi-rate sampling strategy effectively guarantees exponential stability in discrete-time teleoperation systems.
• The method provides a framework for designing sensor networks in teleoperation, considering practical hardware constraints.
• The study offers a robust approach to observer design for enhanced system performance and reliability.