We consider a class of minimum-phase non-linear systems with large parametric uncertainties. The non-linear dynamics is assumed to be linearly parameterized in terms of the unknown parameters. A novel scheme which utilizes multiple models in a model reference adaptive control (MRAC) framework is proposed to improve the transient performance of the adaptive scheme. The proposed approach makes us...

This paper shows how controlled-invariant manifolds in hybrid dynamical systems can be used to reduce the offline computational burden associated with locally exponentially stabilizing periodic orbits. We recently introduced a method to systematically select stabilizing feedback controllers for hybrid periodic orbits from a family of parameterized control laws by solving offline optimization pr...

In this paper stabilization of nonlinear systems with quadratic multi-input is considered. With the help of control Lyapunov function (CLF), a constructive parameterization of controls that globally asymptotically stabilize the system is proposed. Two different cases are considered. Firstly, under certain regularity assumptions, the feasible control set is parameterized, and continuous feedback...

We study the probabilistic generative models parameterized by feedforward neural networks. An attractor dynamics for probabilistic inference in these models is derived from a mean field approximation for large, layered sigmoidal networks. Fixed points of the dynamics correspond to solutions of the mean field equations, which relate the statistics of each unit to those of its Markov blanket. We ...

For nonlinear systems that satisfy certain regularity conditions it is shown that upper and lower bounds on the performance (cost function) can be computed using linear or quadratic programming. The performance conditions derived from Hamilton-Jacobi inequalities are formulated as linear inequalities de ned pointwise by discretizing the state-space when assuming a linearly parameterized class o...

In this paper, robust state feedback and observer-based fuzzy controllers are developed for uncertain T-S fuzzy systems with input delay. By using a generalized Lyapunov function and introducing a parameterized model transformation with free weighting matrices, the less conservative robust stabilization conditions are given for both state measured and state unmeasured cases, which are formulate...

In this paper, we are going to estimate the domain of attraction of tumor-free equilibrium points in a perturbed cancer tumor model describing the tumor-immune system competition dynamics. The proposed method is based on an optimization problem solution for a chosen Lyapunov function that can be casted in terms of Linear Matrix Inequalities constraint and Taylor expansion of nonlinear terms. We...