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The conversion of state-space representation to a transfer function is a fundamental process in system analysis. It provides a method for transitioning from a time-domain description to a frequency-domain representation, which is crucial for simplifying the analysis and design of control systems.
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Related Experiment Video

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Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators

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Zonotope-Based State Estimation for Boost Converter System with Markov Jump Process.

Chaoxu Guan¹, You Li¹, Zhenyu Wang²

¹College of Mechanical Engineering, Jiaxing University, Jiaxing 314001, China.

|October 29, 2025

Summary

This summary is machine-generated.

This study presents zonotope-based state estimation for Markov jump boost converters. The adaptive event-triggered approach enhances robustness and conserves communication resources for power electronics systems.

Keywords:

Markov jump process adaptive event-triggered mechanism boost converter state estimation zonotopes

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Area of Science:

Power Electronics and Control Systems
Nonlinear System Analysis
Stochastic Systems

Background:

DC-DC boost converters are crucial for power electronics applications like renewable energy and electric vehicles.
Nonlinear dynamics and uncertainties in boost converters necessitate robust state estimation techniques.
Markov jump systems model stochastic behavior and switching in dynamic systems.

Purpose of the Study:

To develop a zonotope-based state estimation method for boost converter systems with Markov jump processes.
To integrate time delays, disturbances, and noises into a generalized discrete-time model.
To implement an adaptive event-triggered mechanism for efficient data transmission.

Main Methods:

Modeling the boost converter as a Markov jump system with uncertainties and delays.
Designing an H∞-performance observer for the augmented system.
Developing a zonotopic set-membership estimation algorithm to bound system states.
Utilizing an adaptive event-triggered mechanism to optimize data transmission.

Main Results:

The proposed zonotopic estimation effectively encloses all system states under Markov jump dynamics.
The adaptive event-triggered mechanism significantly reduces communication load while maintaining estimation accuracy.
The H∞ performance criterion ensures robustness against disturbances and noise.
Numerical simulations validate the effectiveness of the developed state estimation approach.

Conclusions:

The zonotope-based state estimation provides a robust solution for boost converters operating under stochastic conditions.
The adaptive event-triggered strategy enhances communication efficiency in networked control systems.
This method contributes to the reliable operation and control of modern power electronic systems.