State variable

About: State variable is a research topic. Over the lifetime, 14354 publications have been published within this topic receiving 254707 citations.

Efficient Global Reliability Analysis for Nonlinear Implicit Performance Functions

Abstract: Many engineering applications are characterized by implicit response functions that are expensive to evaluate and sometimes nonlinear in their behavior, making reliability analysis difficult. This paper develops an efficient reliability analysis method that accurately characterizes the limit state throughout the random variable space. The method begins with a Gaussian process model built from a very small number of samples, and then adaptively chooses where to generate subsequent samples to ensure that the model is accurate in the vicinity of the limit state. The resulting Gaussian process model is then sampled using multimodal adaptive importance sampling to calculate the probability of exceeding (or failing to exceed) the response level of interest. By locating multiple points on or near the limit state, more complex and nonlinear limit states can be modeled, leading to more accurate probability integration. By concentrating the samples in the area where accuracy is important (i.e., in the vicinity of the limit state), only a small number of true function evaluations are required to build a quality surrogate model. The resulting method is both accurate for any arbitrarily shaped limit state and computationally efficient even for expensive response functions. This new method is applied to a collection of example problems including one that analyzes the reliability of a microelectromechanical system device that current available methods have difficulty solving either accurately or efficiently.

Decoupling in the design and synthesis of multivariable control systems

Abstract: Necessary and sufficient conditions for the "decoupling" of an m -input, m -output time-invariant linear system using state variable feedback are determined. Given a system which satisfies these conditions, i.e., which can be decoupled by state variable feedback, the class φ of all feedback matrices which decouple the system is characterized. The characterization of φ is used to determine the number of closed-loop poles which can be specified for the decoupled system and to develop a synthesis technique for the realization of desired closed-loop pole configurations. Transfer matrix consequences of decoupling are examined and practice implications discussed through numerical examples.

Constrained state estimation for nonlinear discrete-time systems: stability and moving horizon approximations

Abstract: State estimator design for a nonlinear discrete-time system is a challenging problem, further complicated when additional physical insight is available in the form of inequality constraints on the state variables and disturbances. One strategy for constrained state estimation is to employ online optimization using a moving horizon approximation. We propose a general theory for constrained moving horizon estimation. Sufficient conditions for asymptotic and bounded stability are established. We apply these results to develop a practical algorithm for constrained linear and nonlinear state estimation. Examples are used to illustrate the benefits of constrained state estimation. Our framework is deterministic.

Stress state variables for unsaturated soils

Abstract: An unsaturated soil is visualized as a four-phase system, the fourth phase being the air-water interface commonly referred to as the contractile skin. Suitable stress state variables for an unsaturated soil are proposed on the basis of writing force equilibrium equations for each phase, within the context of multiphase continuum mechanics. The analysis indicates that any two of three possible normal stress variables can be used to define the stress state. Experimental null-type tests verified the proposed stress state variables for the soil structure and contractile skin of an unsaturated soil.