An adaptive controller is presented in this paper to control an n-link flexible-joint manipulator with time-varying uncertainties. The function approximation technique (FAT) is utilized to represent time-varying uncertainties in some finite combinations of orthogonal basis. The tedious computation of the regressor matrix needed in traditional adaptive control is avoided in the new design, and t...

Clustering algorithms have been applied in several disciplines successfully. One of those applications is the initialization of Radial Basis Function (RBF) centers composing a Neural Network, designed to solve functional approximation problems. The Clustering for Function Approximation (CFA) algorithm was presented as a new clustering technique that provides better results than other clustering...

Using Taylor's series we propose a modified secant relation to get a more accurate approximation of the second curvature of the objective function. Then, based on this modified secant relation we present a new BFGS method for solving unconstrained optimization problems. The proposed method make use of both gradient and function values while the usual secant relation uses only gradient values. U...

abstract it is the purpose of this article to introduce a linear approximation technique for solving a fractional chance constrained programming (cc) problem. for this purpose, a fuzzy goal programming model of the equivalent deterministic form of the fractional chance constrained programming is provided and then the process of defuzzification and linearization of the problem is started. a samp...

We provide an RKHS based inverse problem formulation[15] for analytically deriving the optimal function approximation when probabilistic information about the underlying regression is available in terms of the associated correlation functions as used in [9, 8]. On the lines of Poggio and Girosi[9], we show that this solution can be sparsified using principles of SVM and provide an implementatio...

Multivariate quasi-projection operators Qj(f,φ,φ˜), associated with a function φ and distribution/function φ˜, are considered. The is supposed to satisfy the Strang-Fix conditions compatibility condition φ˜. Using technique based on Fourier multipliers, we study approximation properties of such for functions f from anisotropic Besov spaces Lp 1≤p≤∞. In particular, upper lower estimates Lp-error...

Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning tasks, TD methods require a function approximator to represent the value function. However, using function approximators requires manually making crucial representational decisions. This paper investigates evolutionary...