The quantum-classical correspondence for dynamics of the nonlinear classically chaotic systems is analysed. The problem of quantum chaos consists of two parts: the quasiclassical quantisation of the chaotic systems and attempts to understand the classical chaos in terms of quantum mechanics. The first question has been partially solved by the Gutzwiller semiclassical trace formula for the eigen...

In this paper, we propose an approach for modeling fault coverage in nonlinear dynamical systems. Fault coverage gives a measure of the likelihood that a system will be able to recover after a fault occurrence. In our setup, the system dynamics are described by a standard state-space model. The system input (disturbance) is considered to be unknown but bounded at all times. Before any fault occ...

Model Order Reduction of Nonlinear Dynamical Systems by Chenjie Gu Doctor of Philosophy in Electrical Engineering and Computer Science University of California, Berkeley Professor Jaijeet Roychowdhury, Chair Higher-level representations (macromodels, reduced-order models) abstract away unnecessary implementation details and model only important system properties such as functionality. This meth...

In the paper stochastic dynamical control systems described by nonlinear stationary ordinary differential state equations are considered. Using a generalized open mapping theorem, sufficient conditions for constrained local stochastic controllability in a given time interval are formulated and proved. It is generally assumed, that the values of admissible controls are in a convex and closed con...

This paper discusses the interplay of symmetries and stability in the analysis and control of nonlinear dynamical systems and networks. Specifically, it combines standard results on symmetries and equivariance with recent convergence analysis tools based on nonlinear contraction theory and virtual dynamical systems. This synergy between structural properties (symmetries) and convergence propert...

Fuzzy Counter Propagation Neural Network (FCPN) controller design is developed, for a class of nonlinear dynamical systems. In this process, the weight connecting between the instar and outstar, that is, input-hidden and hidden-output layer, respectively, is adjusted by using Fuzzy Competitive Learning (FCL). FCL paradigm adopts the principle of learning, which is used to calculate Best Matched...

& Ersue, 1992) published a few years back on the subject of neurocontrol. The subject of neural networks for modeling and control of dynamical systems represents an important area of applications of artiÿcial neural networks that reemerged in 1980s. On the other hand, to control engineers , neurocontrol, or neural networks for controls, brings about some new and fresh ideas to the modeling and ...

The paper proposes derivative-free nonlinear Kalman Filtering for MIMO nonlinear dynamical systems. The considered nonlinear filtering scheme which is based on differential flatness theory extends the class of systems to which Kalman Filtering can be applied without the need for calculation of Jacobian matrices. To deduce if a dynamical system is differentially flat, the following should be exa...

In this paper, we consider local and uniform invariance preserving steplength thresholds on a set when a discretization method is applied to a linear or nonlinear dynamical system. For the forward or backward Euler method, the existence of local and uniform invariance preserving steplength thresholds is proved when the invariant sets are polyhedra, ellipsoids, or Lorenz cones. Further, we also ...

This paper focuses on the sensitivity analysis of coupled nonlinear dynamical systems, which under certain conditions exhibit the chaotic behavior. Sensitivity functions calculated via conventional methods of sensitivity analysis are inherently uninformative and inconclusive. The use of the pseudo-orbit shadowing property in dynamical systems allows calculating sensitivity functions correctly a...