The paper presents an algorithm which combining a neural network observer, it give more flexible and accurate control on the engine operation. In recent year, several researchers ...
Gaussian Process prior models, as used in Bayesian non-parametric statistical models methodology are applied to implement a nonlinear adaptive control law. The expected value of a...
We consider a class of systems influenced by perturbations that are nonlinearly parameterized by unknown constant parameters, and develop a method for estimating the unknown param...
— In this paper, an optimization-based adaptive Kalman filtering method is proposed. The method produces an estimate of the process noise covariance matrix Q by solving an optim...
— In this paper, adaptive control is presented for a class of parametric output feedback nonlinear systems with output constraint. Adaptive observer backstepping is adopted to ac...
Beibei Ren, Shuzhi Sam Ge, Keng Peng Tee, Tong Hen...