Modeling and Control of Multi-Agent Systems

Biology has brought much enlightenment to the development of human technology, for example, the collective behaviors inspired engineering applications (such as, the unmanned vehicle formation, the satellite alignment etc.), and even the study of network theory. This discipline has made a significant contribution to technology development. As a prospective solution to the current issues, multi-agent control has become a popular research topic in recent decades. The traditional control methods based on the classical models are suffering from high sensitivity to model accuracy, computational complexity, low fault tolerance, and weakness in real-time performance. Therefore, the advantages of multi-agent control are obvious: 1) easy maintenance and expansion of the system by repairing, replacing or adding agents; 2) high fault tolerance and robustness, ability to function properly even when some agents fail; 3) low requirement of distributed controllers, which brings low cost and large flexibility. In this thesis, I investigate problems on modeling and control of multi-agent systems. In particular, I propose a three-dimensional model to simulate collective behavior under high-speed conditions. I design an improved adaptive-velocity strategy and weighted strategy to enhance the performance of the multi-agent system. Moreover, I analyze the performance from the aspects of energy and parameter space. I show how the model works and its advantages compared to existing models. Then, I study the design of distributed controllers for multi-agent systems. Output regulation with input saturation and nonlinear flocking problems are studied with the assumption of a heterogeneous switching topology. The output regulation problem is solved via low gain state feedback and its validity verified by theoretical study. Then, the flocking problem with heterogeneous nonlinear dynamics is solved. A connectivity-preserving algorithm and potential function are designed to ensure the controllability of the multi-agent system through the dynamic process. Overall, this thesis provides examples of how to analyze and manipulate multi-agent systems. It offers promising solutions to solve physical multi-agent modeling and control problems and provides ideas for bio-inspired engineering and artificial intelligent control for multi-agent systems

The Burnside ai-semiring variety defined by xn≈xx^n\approx x

Let ${\bf Sr}(n, 1)$ denote the ai-semiring variety defined by the identity $x^n\approx x$, where $n>1$. We characterize all subdirectly irreducible members of a semisimple subvariety of ${\bf Sr}(n, 1)$. Based on this result, we prove that ${\bf Sr}(n, 1)$ is hereditarily finitely based (resp., hereditarily finitely generated) if and only if $n<4$ and that the lattice of subvarieties of ${\bf Sr}(n, 1)$ is countable if and only if $n<4$. Also, we show that the class of all locally finite members of ${\bf Sr}(n, 1)$ forms a variety and so affirmatively answer the restricted Burnside problem for ${\bf Sr}(n, 1)$. In addition, we provide a simplified proof of the main result obtained by Gajdo\v{s} and Ku\v{r}il (Semigroup Forum 80: 92--104, 2010)

Research on Risk Prediction and Early Warning of Human Resource Management Based on Machine Learning and Ontology Reasoning

Talent is the first resource, the development of the enterprise to retain key talent is essential, the main research is based on machine learning and ontological reasoning, human resources analysis and management risk prediction and early warning methods, first of all, according to the specific situation and the target case, through the calculation of the similarity of the concept name and attribute of the similarity assessment of the source case in the case library, the matching of knowledge-based employees of the company\u27s case for the similarity prediction and human resources management risk prediction research. Then, according to the evaluation results, we can find out the most suitable job matches in specific risk problems and situations. This is a solution to the target cases and criteria for companies to evaluate candidates. Second, we have successfully developed and implemented a prediction model that applies machine learning to the early warning study of risk prediction for HR management. The model is optimized with a cross-validation function, and the convergence of the model training is accelerated by the regularization of Newton\u27s iterative method. Finally, our prediction model achieved 82% yield. Ontological reasoning and machine learning are promising in human resource management risk prediction and warning, which is proved by the high accuracy rate verified by examples. Finally, we analyze the proposed results of HRM risk prediction and early warning to contribute to the improvement of risk control and suggest measures for possible risks

Characteristics Analysis of Non-linear Torsional Vibration in Engine and Generator Shafting system

To solve the non-linear torsional vibration problem of engine and generator shafting causing body structural vibration and noise in motorized wheel vehicle, where the engine and the generator connected directly. First of all, analysis the characteristics of the shafting system, besides the external shock excitation of engine and generator. Then, through lumped parameter model method, mathematical model of the non-linear torsional vibration was established, which could reflect the dynamic characteristics of the system. Analysis the effect of mechanical parameters and electromagnetic parameters on the shafting. And get the non-linear differential equations of the system torsional vibration, which expresses the relation between structural parameters, electromagnetic parameters and the system dynamic characteristics. And multiple scales method was used to solve the equations. Non-contact measurement method was used in the torsional vibration test. Finally, consistency of the results, indicate that the research method used is reliability and accuracy, and get the critical speed of the shafting torsional vibration

THE VARIETY GENERATED BY AN AI-SEMIRING OF ORDER THREE

Up to isomorphism, there are 61 ai-semirings of order three. The finite basis problem for these semirings is investigated. This problem for 45 semirings of them is answered by some results in the literature. The remaining semirings are studied using equational logic. It is shown that with the possible exception of the semiring $S_7$, all ai-semirings of order three are finitely based

Chronic disease knowledge and its determinants among chronically ill adults in rural areas of Shanxi Province in China: a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Chronic disease knowledge is an important prerequisite for an individual to implement behavioural changes towards the prevention and control of chronic diseases (CDs). Limited information is available about the relationship between different levels of health services and CD knowledge among rural residents with CDs. This research explores the distribution characteristics of CD knowledge and its determinants among chronically ill adults in rural China according to the aspects of patients and health service providers.</p> <p>Methods</p> <p>A cross-sectional study was undertaken to estimate distribution characteristics of CD knowledge and collect data of socio-demographic characteristics, healthcare institutions attendances, duration of illness, and family history of CDs. Participants were 1060 rural adults with hypertension or type II diabetes. Correct responses to 12 questions were summed into a total knowledge score, and participants were divided into an adequate health knowledge group (score ≥ 6) or an inadequate health knowledge group (score < 5). Logistic regression was used determine the predictors of adequate CD health knowledge.</p> <p>Results</p> <p>The mean age of participants was 61.34 years (SD = 10 years). Out of a possible 12, the median score on the CD knowledge questionnaire was 3.0. About 25% of participants were classified as having adequate CD knowledge. Those who had a family history and/or long duration of CDs were more likely to have adequate health knowledge. Participants who received CD health information and self-care instructions from their physicians had 2.67 and 13.34 times greater odds of possessing adequate health knowledge than those who received no information, respectively. Adequate CD knowledge was strongly associated with regular check-ups, especially for those who attended township hospitals (OR = 40.17).</p> <p>Conclusions</p> <p>Having regular check-ups at a fixed healthcare institution and receiving health information from physicians are important measures for increasing CD knowledge among rural adults with CDs. Township hospitals are the most effective settings for health education. It is important to develop an effective community-based prevention and control mechanism for CDs. This requires township hospitals to take a leading role in improving CD knowledge among chronically ill patients, and enhancing implementation of health education in rural China.</p