Xi Yugeng

Neural network design based on evolutionary programming

Abstract In this paper, a new design method for neural networks is presented based on evolutionary programming. By using an evolutionary algorithm the structure and weights of static neural networks can be simultaneously acquired. This method is further extended to design recurrent neural networks through introducing ‘delayed links’ into networks. Simulation results are also given to illustrate the efficiency of the proposed method.In this paper, a new design method for neural networks is presented based on evolutionary programming. By using an evolutionary algorithm the structure and weights of static neural networks can be simultaneously acquired. This method is further extended to design recurrent neural networks through introducing ‘delayed links’ into networks. Simulation results are also given to illustrate the efficiency of the proposed method.

Chaos communication based on synchronization of discrete-time chaotic systems

A novel chaos communication method is proposed based on synchronization of discrete-time chaotic systems. This method uses a full-order state observer to achieve synchronization and secure communication between the transmitter and the receiver. Further, we present a multiple-access chaotic digital communication method by combining the observer with the on-line least square method. Simulation results are also given for illustration.

Stabilization and trajectory tracking of autonomous airship's planar motion

Abstract The stabilization and trajectory tracking problems of autonomous airships planar motion are studied. By defining novel configuration error and velocity error, the dynamics of error systems are derived. By applying Lyapunov stability method, the state feedback control laws are designed and the close-loop error systems are proved to be uniformly asymptotically stable by Matrosov theorem. In particular, the controller does not need knowledge on system parameters in the case of set-point stabilization, which makes the controller robust with respect to parameter uncertainty. Numerical simulations illustrate the effectiveness of the controller designed.

Adaptive fuzzy sliding mode control for a class of uncertain dynamic systems

When a fuzzy controller is to be used, what is used is often a fuzzy sliding mode controller, because fuzzy logic systems (FLS) can be utilized to approximate complex uncertain dynamic nonlinear systems. In this paper an adaptive fuzzy sliding mode control (SMC) scheme in which FLS is used to approximate the unknown systems is proposed. In order to reduce the approximation errors between the true nonlinear function and FLS, an adaptive law is presented. The stability of the proposed control schemes are proved using Lyapunov stability theory. These proposed control schemes are applied to an inverted pendulum system to shown the effectiveness.

Robot path planning in globally unknown environments based on rolling windows

In this paper, robot path planning in globally unknown environments is studied. Using the rolling optimization concept in predictive control for reference, a new strategy of path planning for a mobile robot, based on rolling windows, is proposed. The method makes full use of the real-time local environmental information detected by the robot and the on-line path planning is carried on in a rolling style. Optimization and feedback are combined in a reasonable way. The convergence of the planning algorithm is also discussed.

Dynamic modeling for airship equipped with ballonets and ballast

Total dynamics of an airship is modeled. The body of an airship is taken as a submerged rigid body with neutral buoyancy,i. e., buoyancy with value equal to that of gravity, and the coupled dynamics between the body with ballonets and ballast is considered. The total dynamics of the airship is firstly derived by Newton-Euler laws and Kirchkoffs equations. Furthermore, by using Hamiltonian and Lagrangian semidirect product reduction theories, the dynamics is formulated as a Lie-Poisson system, or also an Euler-Poincaré system. These two formulations can be exploited for the control design using energy-based methods for Hamiltonian or Lagrangian system.

Modified bottleneck-based heuristic for large-scale job-shop scheduling problems with a single bottleneck*

Abstract A modified bottleneck-based (MB) heuristic for large-scale job-shop scheduling problems with a welldefined bottleneck is suggested, which is simpler but more tailored than the shifting bottleneck (SB) procedure. In this algorithm, the bottleneck is first scheduled optimally while the non-bottleneck machines are subordinated around the solutions of the bottleneck schedule by some effective dispatching rules. Computational results indicate that the MB heuristic can achieve a better tradeoff between solution quality and computational time compared to SB procedure for medium-size problems. Furthermore, it can obtain a good solution in a short time for large-scale jobshop scheduling problems.

Study on the closed-loop properties of GPC"

Based on the coefficient mapping of eigenpolynomial from plant to GPC closed-loop system in the IMC structure, the solvability of the optimal control law of GPC and some properties of GPC in relationship with tuning parameters are discussed. Theorems on GPC resulting in deadbeat control are given by properly choosing the design parameters. Furthermore, new result about reducing GPC closed-loop system is derived, which extends the former conclusions. It also provides a new way to study the properties of GPC system based on coefficient mapping.

Flocking of multi-agent dynamic systems with guaranteed group connectivity

This paper investigates distributed flocking problem where the information exchange among agents is modeled by the communication topology changing with time. Previous research on this problem establishes group stabilization by assuming that the dynamic topology is connected all the time, which however can not be guaranteed by most proposed distributed control laws. In this paper, a distributed algorithm to distill a necessary subgraph of the initial communication topology is presented. We prove that the communication topology is always connected as long as this subgraph is connected. A distributed control law is then designed to achieve the flocking motion while preserving all the edges in this subgraph. In this way, flocking problem can be solved only provided the initial communication topology of multi-agent system is connected.

Sub-optimality analysis of mobile robot rolling path planning

Rolling planning is an efficient method for path planning in uncertain environment. In this paper, the general principle and algorithm of mobile robot path planning based on rolling windows are studied. The sub-optimality of rolling path planning is analyzed in details and explained with a concrete example.