Multivariable Feedback Control: Analysis and Design
Multivariable Feedback Control: Analysis and Design
Simulation and the Monte Carlo Method
Simulation and the Monte Carlo Method
Feedback Control of Dynamic Systems
Feedback Control of Dynamic Systems
Feedback Control Theory
Robust H∞ filtering for nonlinear stochastic systems
IEEE Transactions on Signal Processing
Brief Robust control of nonlinear systems with parametric uncertainty
Automatica (Journal of IFAC)
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In this work, a method for determining the reliability of dynamic systems is discussed. Using statistical information on system parameters, the goal is to determine the probability of a dynamic system achieving or not achieving frequency domain performance specifications such as low frequency tracking error, and bandwidth. An example system is considered with closed loop control. A performance specification is given and converted into a performance weight transfer function. The example system is found to have a 20% chance of not achieving the given performance specification. An example of a realistic higher order system model of an electro hydraulic valve with spring feedback and position measurement feedback is also considered. The spring rate and viscous friction are considered random variables with normal distributions. It was found that nearly 6% of valve systems would not achieve the given frequency domain performance requirement.