In this paper, we propose a recognition system of wrist operation by focusing on ElectroMyoGram (EMG) that is the living body signal generated with movement of a subject. In previous research, we only performed pattern recognition by Neural Network (NN) and Fast Fourier Transform (FFT). In contrast, in proposal research, we try to improve recognition accuracy and reduce learning-time of system by combining Multi Discriminant Analysis (MDA) and gradual Principal Component Analysis (PCA) based on the PCA result of EMG data. From results of computer simulation, it is shown that our approach is effective for improvement in recognition accuracy and speed.
This paper is concerned with a Lyapunov stability analysis of a two-dimensional (2-D) discrete-time system described by a high-order partial difference equation in the behavioral setting. We first formulate the autonomy and asymptotic stability of 2-D discrete-time behavior in terms of the characteristic set over Z2. A sufficient condition for asymptotic stability is derived in terms of quadratic difference forms. This condition can be numerically checked by solving a certain four-variable polynomial matrix equation. It also turns out that the present result generalizes some existing stability conditions for the Fornasini-Marchesini state-space model to the behavioral setting.
This paper is concerned with point-to-point feedback control of a trident snake robot. The robot is proposed in our recent work as a new example of nonholonomic systems with two generators. In this paper, a new feedforward type periodic algorithm is proposed to achieve smooth and quantitative locomotion of the robot. Then, a periodic feedback control method is also given which drives the state of the robot to a desired one. The proposed methods are examined by numerical simulations and experiments.
Turbine load allocation is a difficult optimization problem due to its non-smooth characteristic of efficiency. We formulate the problem as a non-smooth, non-convex optimization problem. We propose a practical and efficient global optimization algorithm, which is based on Lipshitz optimization method. The effectiveness of the algorithm is examined through computaional experiments with a real world problem.