切削加工尺寸精度模糊智能控制的研究

针对金属切削加工中影响工件尺寸精度非线性因素众多 ,精确数学模型难以建立的特点 ,提出尺寸加工精度控制的模糊智能化方法 ,设计了自寻优模糊控制器 ,实现了工件尺寸精度在线智能监控。仿真试验结果表明 ,这种控制器具有很好的鲁棒性 ,获得了满意的控制效果。     

Self-optimized and renewable Ni–Co alloy@Co–Co2C catalyst for higher alcohols synthesis from syngas

Higher alcohols synthesis (HAS) from syngas (CO/H₂) has attracted widespread attention, while the low selectivity and poor stability of the catalysts mainly stumbled its industrial application. In the work, Ni–Co alloy nanoparticles (NPs) derived from Co_1-xNi_xAl₂O₄ loaded on the SiO₂ with large specific surface area were prepared; and during reaction, the highly dispersed Ni–Co alloys were self-optimized to Ni–Co alloy@Co–Co₂C. Importantly, Ni–Co alloy@Co–Co₂C can be regenerated through oxidation - reduction - self-optimization process. Characteristic results indicated that the structural liberalization during the reaction process inhibited the loss of Ni, regulated and balanced the dual active sites of the catalyst and the Ni–Co alloys were regenerated after the re-oxidation and re-reduction process. The optimized catalyst exhibited excellent catalytic performance, including a high total selectivity to alcohols of 39.3% and an excellent catalytic stability at 250 °C, 3.5 MPa (H₂/CO = 2) and a space velocity of 6000 mL (g_cat h)^?1. In addition, the Ni–Co alloy@Co–Co₂C catalyst after stability test could recover its original catalytic performance after re-oxidation and re-reduction. The renewable characteristics and superior catalytic performance of Ni–Co alloy@Co–Co₂C made the catalyst to be one of the potential industrial catalysts for HAS.     

A new approach for online multiobjective optimization of mechatronic systems

We present a new concept for online multiobjective optimization and its application to the optimization of the operating point assignment for a doubly-fed linear motor. This problem leads to a time-dependent multiobjective optimization problem. In contrast to classical optimization where the aim is to find the (global) minimum of a single function, we want to simultaneously minimize k objective functions. The solution to this problem is given by the set of optimal compromises, the so-called Pareto set. In the case of the linear motor, there are two conflicting aims which both have to be maximized: the degree of efficiency and the inverter utilization factor. The objective functions depend on velocity, force and power, which can be modeled as time-dependent parameters. For a fixed point of time, the entire corresponding Pareto set can be computed by means of a recently developed set-oriented numerical method. An online computation of the time-dependent Pareto sets is not possible, because the computation itself is too complex. Therefore, we combine the computation of the Pareto set with numerical path following techniques. Under certain smoothness assumptions the set of Pareto points can be characterized as the set of zeros of a certain function. Here, path following allows to track the evolution of a given solution point through time.     

Multi-stage optimization method for air-intake system of hovercraft based on autonomous optimization

Abstract

In this study, an optimal structural design program was designed and developed for Computational Fluid Dynamics based on self-optimization, effectively reducing the time required for structural optimization. Through experimental design using this program, the effects of various design variables on the optimization objectives were evaluated, and an adaptive simulated annealing algorithm was used for global optimization. Furthermore, response surface methodology and a nonlinear quadratic programming algorithm were utilized to obtain a global optimum solution after repeated iterations. Moreover, using a hovercraft air-intake system as the optimized object, the total pressure loss of the system was completely optimized by using a porous medium model and Matlab analysis program, and the accuracy of the structural design optimization program was validated. After the global optimization, the total pressure loss of the air-intake system was reduced by 20.5% compared to the original model. An average nonuniformity of 4.36% of engine inlet speed and 5% local nonuniformity of 11.19% satisfy the design requirements of the hovercraft engine. This method can be directly applied to engineering optimization problems as well as multiobjective optimization tasks after improving the relevant methodologies.     

Tool support for the design of self-optimizing mechatronic multi-agent systems

Complex technical systems, such as mechatronic systems, can exploit networking as well as the computational power available today to achieve an automatic improvement of the technical system performance at run-time through self-optimization. To realize this vision, appropriate means for the design of such self-optimizing mechatronic systems are required. Well-established techniques and tools for the modeling of cognitive behavior, reflective behavior, and control behavior exist. However, to really enable self-optimization and its full potential, these different aspects have to be safely integrated in a manner that remains comprehensible to the designer. In this article, we present how this required integration has been realized at the semantic level by extending the unified modeling language (UML), and at the tool level by integrating the CAE tool CAMeL and the CASE tool Fujaba real-time tool suite. The presented Mechatronic UML approach supports the design of verifiable, complex, reconfigurable mechatronic systems using the multi-agent system metaphor. This work was developed in the course of the Special Research Initiative 614—self-optimizing concepts and structures in mechanical engineering—University of Paderborn, and was published on its behalf and funded by the Deutsche Forschungsgemeinschaft. Sven Burmester, Oliver Oberschelp, Florian Klein and Peter Scheideler are members of the respective research group which left after the paper was submitted.     

AMUN: an autonomic middleware for the Smart Doorplate Project

We envision future office buildings that partly or fully implement a flexible office organization where office rooms are dynamically assigned to currently present employees. Such organizational principles save required office space, therefore decrease costs, but require a sophisticated software system that is highly dynamic, scalable, context-aware, self-configuring, self-optimizing and self-healing. We propose an autonomic/organic middleware approach for such ubiquitous indoor environments with an extensive monitoring at different system levels and demonstrate the software by using our Smart Doorplate Project that is designed to support a flexible office organization.