New model reference adaptive control with input constraints

A new scheme of adaptive control is proposed for a class of linear time-invariant（ LTI） dynamical systems,especially in aerospace,with matched parametric uncertainties and input constraints. Based on a typical and conventional direct model reference adaptive control scheme,various modifications have been employed to achieve the goal. ＂C omposite model reference adaptive control＂of higher performance is seam-lessly combined with ＂positive μ-mod＂,which consequently results in a smooth tracking trajectory despite of the input constraints. In addition,bounded-gain forgetting is utilized to facilitate faster convergence of parameter estimates. The stability of the closed-loop systemcan be guaranteed by using Lyapunov theory.The merits and effectiveness of the proposed method are illustrated by a numerical example of the longitudinal dynamical systems of a fixed-wing airplane.

Parallel Cloth Simulation Using OpenGL Shading Language

The primary goal of cloth simulation is to express object behavior in a realistic manner and achieve real-time performance by following the fundamental concept of physic.In general,the mass–spring system is applied to real-time cloth simulation with three types of springs.However,hard spring cloth simulation using the mass–spring system requires a small integration time-step in order to use a large stiffness coefficient.Furthermore,to obtain stable behavior,constraint enforcement is used instead of maintenance of the force of each spring.Constraint force computation involves a large sparse linear solving operation.Due to the large computation,we implement a cloth simulation using adaptive constraint activation and deactivation techniques that involve the mass-spring system and constraint enforcement method to prevent excessive elongation of cloth.At the same time,when the length of the spring is stretched or compressed over a defined threshold,adaptive constraint activation and deactivation method deactivates the spring and generate the implicit constraint.Traditional method that uses a serial process of the Central Processing Unit(CPU)to solve the system in every frame cannot handle the complex structure of cloth model in real-time.Our simulation utilizes the Graphic Processing Unit(GPU)parallel processing with compute shader in OpenGL Shading Language(GLSL)to solve the system effectively.In this paper,we design and implement parallel method for cloth simulation,and experiment on the performance and behavior comparison of the mass-spring system,constraint enforcement,and adaptive constraint activation and deactivation techniques the using GPU-based parallel method.

Trust Type Based Trust Bootstrapping Model of Computer Network Collaborative Defense

In the system of Computer Network Collaborative Defense(CNCD),it is difficult to evaluate the trustworthiness of defense agents which are newly added to the system,since they lack historical interaction for trust evaluation.This will lead that the newly added agents could not get reasonable initial trustworthiness,and affect the whole process of trust evaluation.To solve this problem in CNCD,a trust type based trust bootstrapping model was introduced in this research.First,the division of trust type,trust utility and defense cost were discussed.Then the constraints of defense tasks were analyzed based on game theory.According to the constraints obtained,the trust type of defense agents was identified and the initial trustworthiness was assigned to defense agents.The simulated experiment shows that the methods proposed have lower failure rate of defense tasks and better adaptability in the respect of defense task execution.