In model-based fault diagnosis for dynamic systems with uncertain parameters, an envelope of all fault-free behaviors can be determined from the model and used as a reference for detecting faults. We demonstrate here a method for generating an envelope that is rigorously guaranteed to be complete, but without significant overestimation. The method is based on an interval approach, but uses Tayl...

Linear Programming (LP) remains the workhorse of applied optimization, having openloop process applications such as production planning, inventory scheduling and closedloop applications such as Real-time optimization and the steady-state determination at each execution of a Model Predictive Controller (MPC). This paper presents new methods for monitoring performance (estimating the degradation ...

Usually when determining parameters with an inverse method, it is assumed that parameters or properties, other than those being sought, are known exactly. When such known parameters are uncertain, the inverse solution can be very sensitive to the degree of uncertainty. The stochastic regularization method can be modi ed to reduce this sensitivity. This paper presents such a modi cation. In addi...

Algorithms for full 3D robotic visual tracking of moving targets whose motion is 3D and consists of translational and rotational components are presented. The objective of the system is to track selected features on moving objects and to place their projections on the image plane at desired positions by appropriate camera motion. The most important characteristics of the proposed algorithms are...

Although we usually would like to work with exact systems, most of the real world systems are nonlinear with uncertain parameters. In this paper, we propose AVK (A.V. Kamyad) approach to solve nonlinear problems with uncertain parameters (NPUP). This approach substitutes the original nonlinear system with an equivalent nonlinear programming (NLP) problem. Using this approach, we found an optima...

This paper deals with uncertain parabolic fluid flow problem where the uncertainty occurs due to the initial conditions and parameters involved in the system. Uncertain values are considered as fuzzy and these are handled through a recently developed method. Here the concepts of fuzzy numbers are combined with Finite Difference Method (FDM) and then Fuzzy Finite Difference Method (FFDM) has bee...

Sequential decision problems can often be modeled as Markov decision processes. Classical solution approaches assume that the parameters of the model are known. However, model parameters are usually estimated and uncertain in practice. As a result, managers are often interested in how estimation errors affect the optimal solution. In this paper we illustrate how sensitivity analysis can be perf...

It is commonly the case in biochemical modelling that we have knowledge of the qualitative 'structure' of a model and some measurements of the time series of the variables of interest (concentrations and fluxes), but little or no knowledge of the model's parameters. This is, then, a system identification problem, that is commonly addressed by running a model with estimated parameters and assess...

Abstract This article deals with anti-synchronization between different hyperchaotic systems such as Lu system and Newton-Leipnik system; and Newton-Leipnik system and Rossler system using adaptive control method. Based on Lyapunov stability theory, the anti synchronization between a pair of hyperchaotic systems with fully unknown parameters are derived. An adaptive control law and a parameter ...

Active Systems with Uncertain Parameters: an Information-Theoretic Perspective by Gireeja Vishnu Ranade Doctor of Philosophy in Electrical Engineering and Computer Sciences University of California, Berkeley Professor Anant Sahai, Chair The sister fields of control and communication share many common goals. While communication aims to reduce uncertainty by communicating information about the st...