Distortion Compensation for Block Transmission System with Cyclic Prefix (original) (raw)

Design of a Compensator for Proportional Navigation with .MU.-Synthesis

JOURNAL OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES

This paper proposes a design method of a missile guidance system with robust control. The design method provides a compensator for the proportional navigation guidance law, explicitly considering the uncertainties by employing the µ-synthesis, a design method of robust control systems. The proposed method has two features: One is that the plant is modeled so that the feedback signal becomes the same as that of the proportional navigation, i.e., the relative velocity multiplied by the line-of-sight angular rate. The other is that the controlled output is chosen to be the component of the relative velocity perpendicular to the line of sight, instead of the line-of-sight angular rate, which is usually chosen in guidance law design based on modern control. Computer simulation is performed using a two-dimensional engagement model to show the effectiveness of the guidance law.

C30 Robust Control of Master-Slave Robotic System Considering Environmental Uncertainty and Communication Delay

The Proceedings of the Symposium on the Motion and Vibration Control, 2005

This paper deals with robust control of a master − slave robotic system , We construct a master −slave system by using two 2− DOF robot manipulators and design a robust centrel system via impedance shaping and μ 一 Synthesis considering various uncertaint 孟 es ;e , g , , environment and operator dynamics , perturbation of impedance model and time de 且 ay in telecommunications . The proposed control methodology can guarantee the robust stability and the robust perfbr皿 ance ft) r all these uncertainties of the master −s監ave system . Experiment al results show the effectiveness of our proposed apProach for various environmental uncertainties ・ Key Wbrds : Master − Slave System , Robet Manipulatorl Impedance Shaping , Robust Control , μ 一 Synthesis, Environmental Uncertainty , CQ 皿 munication Delay

Applying Soft Arc Consistency to Distributed Constraint Optimization Problems

Transactions of the Japanese Society for Artificial Intelligence, 2010

The Distributed Constraint Optimization Problem (DCOP) is a fundamental framework of multi-agent systems. With DCOPs a multi-agent system is represented as a set of variables and a set of constraints/cost functions. Distributed task scheduling and distributed resource allocation can be formalized as DCOPs. In this paper, we propose an efficient method that applies directed soft arc consistency to a DCOP. In particular, we focus on DCOP solvers that employ pseudo-trees. A pseudo-tree is a graph structure for a constraint network that represents a partial ordering of variables. Some pseudo-tree-based search algorithms perform optimistic searches using explicit/implicit backtracking in parallel. However, for cost functions taking a wide range of cost values, such exact algorithms require many search iterations. Therefore additional improvements are necessary to reduce the number of search iterations. A previous study used a dynamic programming-based preprocessing technique that estimates the lower bound values of costs. However, there are opportunities for further improvements of efficiency. In addition, modifications of the search algorithm are necessary to use the estimated lower bounds. The proposed method applies soft arc consistency (soft AC) enforcement to DCOP. In the proposed method, directed soft AC is performed based on a pseudo-tree in a bottom up manner. Using the directed soft AC, the global lower bound value of cost functions is passed up to the root node of the pseudo-tree. It also totally reduces values of binary cost functions. As a result, the original problem is converted to an equivalent problem. The equivalent problem is efficiently solved using common search algorithms. Therefore, no major modifications are necessary in search algorithms. The performance of the proposed method is evaluated by experimentation. The results show that it is more efficient than previous methods.

A Note on the Branch-and-Cut Approach to Decoding Linear Block Codes

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2010

Maximum likelihood (ML) decoding of linear block codes can be considered as an integer linear programming (ILP). Since it is an NP-hard problem in general, there are many researches about the algorithms to approximately solve the problem. One of the most popular algorithms is linear programming (LP) decoding. Advanced algorithms for solving ILP (approximately or exactly) include cuttingplane method and branch-and-bound method. As applications of these methods, adaptive LP decoding and branchand-bound decoding have been proposed. Another method for solving ILP is the branch-and-cut method, which is a hybrid of cutting-plane and branch-andbound methods. In this paper, we describe the branch-andcut based ML decoding algorithm. We construct a generalized framework for the branch-and-cut based ML decoding and compare some algorithms with numerical simulations.

Stability analysis of the delayed feedback ccontrol method with commutative gain matrices

2010

The purpose of our investigation is to guarantee the delayed feedback control method in chaos control proposed by Pyragas analytically. Recently, we gave the conditions for deciding whether the control method is successful under some assumption(we will say “Commutative Assumption”) by using the Floquet theory to a delay differential equation. In this article, we summarize the above results and the fundamental matter of the Floquet theory to a delay differential equation. As an application, we will also show numerically that some unstable periodic orbits of the Rössler system can be stabilized by the method using a different control gain matrix from that which Pyragas used. Especially, the numerical result that the 3 times periodic orbit can be stabilized is newly obtained result.