Novel Models and Algorithms of Load Balancing for Variable-structured Collaborative Simulation under HLA/RTI

High level architecture(HLA) is the open standard in the collaborative simulation field. Scholars have been paying close attention to theoretical research on and engineering applications of collaborative simulation based on HLA/RTI, which extends HLA in various aspects like functionality and efficiency. However, related study on the load balancing problem of HLA collaborative simulation is insufficient. Without load balancing, collaborative simulation under HLA/RTI may encounter performance reduction or even fatal errors. In this paper, load balancing is further divided into static problems and dynamic problems. A multi-objective model is established and the randomness of model parameters is taken into consideration for static load balancing, which makes the model more credible. The Monte Carlo based optimization algorithm(MCOA) is excogitated to gain static load balance. For dynamic load balancing, a new type of dynamic load balancing problem is put forward with regards to the variable-structured collaborative simulation under HLA/RTI. In order to minimize the influence against the running collaborative simulation, the ordinal optimization based algorithm(OOA) is devised to shorten the optimization time. Furthermore, the two algorithms are adopted in simulation experiments of different scenarios, which demonstrate their effectiveness and efficiency. An engineering experiment about collaborative simulation under HLA/RTI of high speed electricity multiple units(EMU) is also conducted to indentify credibility of the proposed models and supportive utility of MCOA and OOA to practical engineering systems. The proposed research ensures compatibility of traditional HLA, enhances the ability for assigning simulation loads onto computing units both statically and dynamically, improves the performance of collaborative simulation system and makes full use of the hardware resources.

An Approach to Integrated and Concurrent Product Development

A concurrent product development example is used in this paper to introduce a roadmap for integrated and concurrent product development. The roadmap covers the following steps: (1)enterprise problem specifying; (2)information integration modeling; (3)integrated products development team modeling; (4)product development process modeling; and (5) integrated information-process-organization modeling. They have been successfully applied in the major pilot project of "Concurrent Engineering" of the 863 Programme of China.

Data Driven Uncertainty Evaluation for Complex Engineered System Design

Complex engineered systems are often difficult to analyze and design due to the tangled interdependencies among their subsystems and components. Conventional design methods often need exact modeling or accurate structure decomposition, which limits their practical application. The rapid expansion of data makes utilizing data to guide and improve system design indispensable in practical engineering. In this paper, a data driven uncertainty evaluation approach is proposed to support the design of complex engineered systems. The core of the approach is a data-mining based uncertainty evaluation method that predicts the uncertainty level of a specific system design by means of analyzing association relations along different system attributes and synthesizing the information entropy of the covered attribute areas, and a quantitative measure of system uncertainty can be obtained accordingly. Monte Carlo simulation is introduced to get the uncertainty extrema, and the possible data distributions under different situations is discussed in detail The uncertainty values can be normalized using the simulation results and the values can be used to evaluate different system designs. A prototype system is established, and two case studies have been carded out. The case of an inverted pendulum system validates the effectiveness of the proposed method, and the case of an oil sump design shows the practicability when two or more design plans need to be compared. This research can be used to evaluate the uncertainty of complex engineered systems completely relying on data, and is ideally suited for plan selection and performance analysis in system design.

Synergic Motion Trajectory Planning for Airplane Docking Based on6PURU Parallel Mechanism

Motion planning issues encountered in assembling airplanes by employing the 6PURU parallel mechanism are analyzed in this paper. A sine curve of the change rate of acceleration, which is called as jerk in the following text, is proposed for uniaxial flexible acceleration and deceleration planning based on the optimal time and velocity and acceleration constraints. Compared with other curves, the proposed curve can realize a continuous n-order derivative and the smooth change of the speed and acceleration. The method is computational^y simple and suitable for programming. In addition, a multiaxial coordinated movement scheme is proposed. The motion trajectory is no longer simply split into many single-direction trajectories nor are all single-direction planning trajectories combined directly. The multiaxial coordinated movement scheme aims to achieve synergic movement in multiple directions to ensure smoothness of the movement in the event of a kinematic error when maintaining a stable value. If the movement fails to achieve this goal, driving force mutations will deteriorate the effect of synergic movement. A physical model of the parallel mechanism is developed in simMechanics, and a holistic system model is completed in SIMULINK. The feasibility of the new planning algorithm is simulated and tested, and then, the multiaxial synergic movement planning method is proposed and verified.

Data fusion and simulation-based planning and control in cyber physical system for digital assembly of aeroplane

This paper introduces a CPS application for intelligent aeroplane assembly.At first,the CPS structure is presented,which acquires the characteristics of general CPS and enables“simulation-based planning and control”to achieve high level intelligent assembly.Then the paper puts forward data fusion estimation algorithm under synchronous and asynchronous sampling,respectively.The experiment shows that global optimal distributed fusion estimation under synchronized sampling proves to be closer to the actual value compared with ordinary weighted estimation,and multi-scale distributed fusion estimation algorithm of wavelet under asynchronous sampling does not need time registration,it can also directly link to data,and the error is smaller.This paper presents hybrid control strategy under the circumstance of joint action of the inner and outer loop to address the problems caused by the less controllable feature of the parallel mechanism when undertaking online process simulation and control.A robust adaptive sliding mode controller is designed based on disturbance observer to restrain inner interference and maintain robustness.At the same time,an outer collaborative trajectory planning is also designed.All the experiment results show the feasibility of above proposed methods.

Approach of hybrid GA for multi-objective job-shop scheduling

In recent years,scholars have made many research results on job-shop scheduling(JSP)problem,especially in single objective such as the maximum completion time.But most of the actual system scheduling problems are more than one object.Therefore,the research of multi-objective scheduling problem is very important and meaningful.In this paper,we proposed a multi-objective scheduling model which adopts weighted sum method to optimize two important indexes(makespan and total flow time).Genetic algorithm(GA)has diversified global search ability,while simulated annealing(SA)combined with tabu search(TS)have intensified capabilities in local neighborhood search.To overcome the drawback of the GA,we proposed a new hybrid GA(NewHGA)which produces initial solutions by GA firstly,and then take SA operator incorporate TS operator to search in the local space.By adding the novel local search strategy,the diversity of solutions will be improved greatly so that it can ensure the algorithm jump out of the local optimal value.We test this algorithm using the benchmark instances of different sizes taken from the OR-Library,and the results show that the algorithm is efficient than another hybrid algorithm.