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Periodic Event-Triggered Suboptimal Control With Sampling Period and Performance Analysis.

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    This study introduces periodic event-triggered suboptimal control (PETSOC) for linear systems, reducing computational load by checking triggers periodically. The method ensures system stability and performance, validated on a batch reactor.

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    Area of Science:

    • Control Systems Engineering
    • Systems Theory
    • Applied Mathematics

    Background:

    • Continuous monitoring of control system triggers demands significant computational resources.
    • Existing event-triggered control strategies require constant evaluation of triggering conditions.
    • Optimizing resource usage in control systems is crucial for practical implementation.

    Purpose of the Study:

    • To develop a novel periodic event-triggered suboptimal control (PETSOC) method for continuous-time linear systems.
    • To reduce computational overhead compared to traditional event-triggered control by periodic verification.
    • To ensure system stability and performance bounds under the proposed PETSOC strategy.

    Main Methods:

    • Design of the PETSOC control gain using the algebraic Riccati equation.
    • Proposal and periodic verification of the event-triggering condition at sampling instants.
    • Analysis and determination of the sampling period based on the continuous triggering condition form.
    • Stability and performance upper bound proofs for the closed-loop system.

    Main Results:

    • The PETSOC method effectively reduces computational resource demands.
    • Stability and performance guarantees are mathematically proven for the closed-loop system.
    • Simulations on an unstable batch reactor demonstrate the PETSOC method's effectiveness.

    Conclusions:

    • The developed PETSOC method offers a computationally efficient approach to control linear systems.
    • Periodic triggering significantly reduces resource requirements without compromising stability or performance.
    • The PETSOC strategy is validated as effective for practical control applications, including unstable systems.