The plain Newton-min algorithm to solve the linear complementarity problem (LCP for short) 0 6 x ⊥ (Mx + q) > 0 can be viewed as a semismooth Newton algorithm without globalization technique to solve the system of piecewise linear equations min(x,Mx + q) = 0, which is equivalent to the LCP. When M is an M-matrix of order n, the algorithm is known to converge in at most n iterations. We show in ...

Fuzzy control of robot manipulators with a decentralized structure is facing a serious challenge. The state-space model of a robotic system including the robot manipulator and motors is in non-companion form, multivariable, highly nonlinear, and heavily coupled with a variable input gain matrix. Considering the problem, causes and solutions, we use voltage control strategy and convergence analy...

Concerning with the topics of fuzzy decision processes, a brief survey on ordering of fuzzy numbers on R is presented and an extension to that of fuzzy sets(numbers) on Rn are considered. This extension is a pseudo order 4 K de ned by a non-empty closed convex cone K and characterized by the projection into its dual cone K. Especially a structure of the lattice is presented on the class of rect...

The plain Newton-min algorithm to solve the linear complementarity problem (LCP for short) 0 6 x ⊥ (Mx + q) > 0 can be viewed as a semismooth Newton algorithm without globalization technique to solve the system of piecewise linear equations min(x,Mx + q) = 0, which is equivalent to the LCP. When M is an M-matrix of order n, the algorithm is known to converge in at most n iterations. We show in ...

In the convergence theory of Padé approximation, one needs to estimate the size of a set on which a suitably normalized polynomial q is small. For example, one needs to estimate the size of the set of r 2 [0; 1] for which max jtj=1 jq (t)j =min jtj=r jq (t)j is not “too large”. We discuss some old and new problems of this type, and the methods used to solve them. 1. Introduction Let f be a func...

In this paper, we introduce and study a generalized Yosida approximation operator associated to H(·, ·)-co-accretive operator and discuss some of its properties. Using the concept of graph convergence and resolvent operator, we establish the convergence for generalized Yosida approximation operator. Also, we show an equivalence between graph convergence for H(·, ·)-co-accretive operator and gen...

We study the q–deformed fuzzy sphere, which is related to D-branes on SU(2) WZW models, for both real q and q a root of unity. We construct for both cases a differential calculus which is compatible with the star structure, study the integral, and find a canonical frame of one–forms. We then consider actions for scalar field theory, as well as for Yang–Mills and Chern–Simons–type gauge theories...

Reinforcement learning is one of the most important learning methods for intelligent robots working in unknown/uncertain environments. Multi-dimensional fuzzy Q-learning, an extension of the Q-learning method, has been proposed in this study. The proposed method has been applied for an intelligent robot working in a dynamic environment. The rewards from the evaluation functions and the fuzzy Q-...