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New results on delay-range-dependent stability analysis for interval time-varying delay systems with non-linear
1Department of Automation Engineering Institute of Mechatronoptic System, Chienkuo Technology University, Changhua 500, Taiwan, ROC.
This study presents a new method for analyzing the stability of time-varying delay systems with nonlinear perturbations. The approach ensures system stability within specific delay ranges, reducing conservatism in stability analysis.
Area of Science:
- Control Systems Engineering
- Nonlinear Dynamics
- Systems Theory
Background:
- Interval time-varying delay systems are crucial in many applications but challenging to analyze due to time delays and nonlinearities.
- Existing stability criteria often exhibit conservatism, limiting their practical applicability.
- Lyapunov-Krasovskii functionals (LKF) are standard tools for stability analysis, but their effectiveness can be enhanced.
Purpose of the Study:
- To develop a novel, less conservative stability criterion for interval time-varying delay systems with nonlinear perturbations.
- To improve the accuracy and efficiency of stability analysis for such complex systems.
- To provide a delay-range-dependent stability condition.
Main Methods:
- Utilizing Lyapunov-Krasovskii functionals (LKF) for stability analysis.
- Employing linear matrix inequality (LMI) techniques.
- Applying integral inequality approach (IIA) and delayed decomposition approach (DDA).
- Segmenting the delay range into two equal parts for analysis.
Main Results:
- A sufficient delay-range-dependent criterion for asymptotic stability was derived.
- The proposed method demonstrated reduced conservatism compared to existing approaches.
- Theoretical and numerical comparisons confirmed the method's effectiveness and efficiency.
- Validation through two well-known examples.
Conclusions:
- The developed method provides an effective and less conservative approach for stability analysis of interval time-varying delay systems.
- The combination of LKF, LMI, IIA, and DDA offers significant improvements in stability analysis.
- The findings contribute to the robust design and control of systems with time delays and nonlinearities.
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