Cooperative Manufacturing and Assembling Supported by CRQAOVTM Agent in Open Environment
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摘要: 针对开放式环境下松耦合程度和可靠性不够的协作模式的缺点,以及协同制造装配问题出现的"结构失配"和"工艺革新"的特性,提出CRQAOVTMAgent模型.模型从服务参数(属性)松耦合程度和服务执行结果确定性两个方面区别定义普通(O,Ordinary)接口、转换(V, conVersion)接口、多参数适配器(T, multiparameter adapTor)接口和概念实例调制器(M, concept instance Modulator)接口,并在此基础上提供包括普通协作、转换性协作、适配性协作和调制性协作的混合协作模式,且在处方的基础上引入量化合成,以更加灵活的方式处理"结构失配"和"工艺革新"问题.同时模型引入合同的约束,保证自组织协作是可信的.通过验证并与RPACTI Agent模型比较可知,该模型的协作机制既具有很高的成功率和效率,又具有很高的灵活性,更加适合开放环境下的协同制造装配.
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关键词:
- CRQAOVTM Agent /
- 协同制造装配 /
- 合同约束 /
- 多Agent系统
Abstract: For the shortcomings of the cooperation mode of low loose coupling degree and low reliability in open environment, and for the "mismatched-structured" and "technics-innovation" characteristics of cooperative manufacturing and assembling problem, a CRQAOVTM Agent model is presented. Four cooperative interfaces, called Ordinary, conVersion, adapTor and Modulator interfaces, are defined and distinguished by their different degrees of loose coupling of service parameters (attributes) and determinations of service execution result. Further based on them, a hybrid collaboration mode is presented, including Ordinary, conVersion, adapTor, and weakly-constrained Modulator collaborations. Based on recipes, quantitative service compositions are imported. All these make agents have the ability to cope with the "mismatched-structured" and "technics -innovation" problems in a more flexible manner. Contract constraint is also integrated into the model to ensure the self-organizing collaboration is trusted. Through verification and comparison with RPACTI Agent model we know, it strongly supports multi-agent systems to work well for cooperative manufacturing and assembling in open environment, by the guarantee of high success rate, high efficiency and more flexibility at the same time.1) 本文责任编委 赵千川 -
表 1 任务约束项数为4~7时两类模型的接口成功概率数据
Table 1 Two model interface success rate data under task constraints 4$\, \sim\, $7
接口代理 能力 潜力 兴趣 普通接口 转换接口 适配接口 调制接口 接口代理 Agent1 {1, 3, 1} {2, 3, 75%} {61, 3, 50%} {1, 3, 1} {3, 1, 93%} {2, 3, 86%} {61, 3, 60%} AGENT1 {5, 1, 1} {4, 1, 75%} {83, 1, 50%} {5, 1, 1} {6, 3, 93%} {4, 1, 86%} {83, 1, 60%} {11, 1, 1} {12, 1, 75%} {95, 1, 50%} {11, 1, 1} {7, 2, 93%} {12, 1, 86%} {95, 1, 60%} {15, 1, 1} {16, 1, 75%} {97, 1, 50%} {15, 1, 1} {8, 2, 93%} {16, 1, 86%} {97, 1, 60%} {21, 2, 1} {22, 2, 75%} {75, 2, 50%} {21, 2, 1} {9, 3, 93%} {22, 2, 86%} {75, 2, 60%} {51, 3, 1} {52, 3, 75%} {87, 3, 50%} {51, 3, 1} {10, 2, 93%} {52, 3, 86%} {87, 3, 60%} Agents2 {2, 2, 1} {1, 2, 73%} {61, 2, 55%} {2, 2, 1} {61, 3, 96%} {1, 2, 84%} {61, 2, 64%} AGENT2 {4, 2, 731} {5, 2, 73%} {83, 2, 55%} {4, 2, 1} {83, 1, 96%} {5, 2, 84%} {83, 2, 64%} {12, 3, 1} {11, 3, 73%} {95, 3, 55%} {12, 3, 1} {95, 1, 96%} {11, 3, 84%} {95, 3, 64%} {16, 4, 1} {15, 4, 73%} {97, 4, 55%} {16, 4, 1} {97, 1, 96%} {15, 4, 84%} {97, 4, 64%} {22, 1, 1} {21, 1, 73%} {75, 1, 55%} {22, 1, 1} {75, 2, 96%} {21, 1, 84%} {75, 1, 64%} {52, 1, 1} {51, 1, 73%} {87, 1, 55%} {52, 1, 1} {87, 3, 96%} {51, 1, 84%} {87, 1, 64%} Agents3 {61, 1, 1} {2, 1, 76%} {1, 1, 52%} {61, 1, 1} {13, 2, 95%} {2, 1, 84%} {1, 1, 62%} AGENT3 {83, 3, 1} {4, 3, 76%} {5, 3, 52%} {83, 3, 1} {14, 2, 95%} {4, 3, 84%} {5, 3, 62%} {95, 2, 1} {12, 2, 76%} {11, 2, 52%} {95, 2, 1} {17, 3, 95%} {12, 2, 84%} {11, 2, 62%} {97, 2, 1} {16, 2, 76%} {15, 2, 52%} {97, 2, 1} {18, 4, 95%} {16, 2, 84%} {15, 2, 62%} {75, 3, 1} {22, 3, 76%} {21, 3, 52%} {75, 3, 1} {19, 1, 95%} {22, 3, 84%} {21, 3, 62%} {87, 2, 1} {52, 2, 76%} {日1,2, 52%} {87, 2, 1} {20, 1, 95%} {52, 2, 84%} {51, 2, 62%} Agent4 {1, 4, 1} {2, 4, 78%} {61, 4, 51%} {1, 4, 1} {23, 4, 94%} {2, 4, 85%} {61, 4, 63%} AGENT4 {5, 4, 1} {4, 4, 78%} {83, 4, 51%} {5, 4, 1} {24, 4, 94%} {4, 4, 85%} {83, 4, 63%} {11, 5, 1} {12, 5, 78%} {95, 5, 51%} {11, 5, 1} {25, 5, 94%} {12, 5, 85%} {95, 5, 63%} {15, 3, 1} {16, 3, 78%} {97, 3, 51%} {15, 3, 1} {26, 3, 94%} {16, 3, 85%} {97, 3, 63%} {21, 4, 1} {22, 4, 78%} {75, 4, 51%} {21, 4, 1} {27, 4, 94%} {22, 4, 85%} {75, 4, 63%} {51, 4, 1} {52, 4, 78%} {87, 4, 51%} {51, 4, 1} {28, 4, 94%} {52, 4, 85%} {87, 4, 63%} $\vdots $ $\vdots $ $\vdots $ $\vdots $ $\vdots $ $\vdots $ $\vdots $ $\vdots $ $\vdots $ 表 2 任务约束项数为4$ \sim $7时方案
Table 2 Schemes under task constraints 4$ \sim $7
任务 约束项数 RPA$_{CTI}$ Agent方案 CRQA$_{OVTM}$ Agent方案 说明 任务1 $4\in 4 \sim 7$ {Agent$_3$.$I$ (52 %), Agent$_2.P$ (73$ \%$),
Agent$_1.C$, Agent$_4.C$}{AGENT$_3$.$M$ (62$ \%$), AGENT$_2$.$T$ (84$ \%$),
AGENT$_1$.$O$, AGENT$_4$.$O$}RPA$_{CTI}$Agent方案连续出现两个", "说明第2项约束(子任务)无接口可以匹配 任务2 $4\in 4 \sim 7$ {Agent$_3$.$P$ (76$ \%$), Agent$_2$.$C$,
Agent$_1$.$P$ (75$ \%$), Agent$_4$.$P$ (78$ \%$)}{AGENT$_3$.$T$ (84$ \%$), AGENT$_5$.$O$, AGENT$_6$.$T$
(86$ \%$), AGENT$_7$.$T$ (85$ \%$)}任务3 $4\in 4 \sim 7$ {Agent$_5.P$ (76 $\%$),
Agent$_7$.$P$ (75$ \%$), Agent$_9$.$P$ (78$ \%$)}{AGENT$_1$.$V$ (93$ \%$), AGENT$_3$.$T$ (84$ \%$), AGENT2.$O$,
AGENT$_4$.$T$ (85$ \%$)}任务4 $4\in 4 \sim 7$ {Agent$_1$.$P$ (75$ \%$), Agent$_2$.$C$,
Agent$_3$.$P$ (76$ \%$), Agent$_4$.$P$ (78$ \%$)}{AGENT$_1$.$T$ (86$ \%$), AGENT$_2$.$O$, AGENT$_3$.$T$
(84$ \%$), AGENT$_4$.$T$ (85$ \%$)}任务5 $4\in 4 \sim 7$ {Agent$_1$.$C$, Agent$_2$.$P$ (73$ \%$),
$\quad$
Agent$_3$.$I$ (52$ \%$), Agent$_4$.$C$}{AGENT$_1$.$O$, AGENT$_2$.$T$ (84$ \%$),
AGENT$_3$.$M$ (62$ \%$), AGENT$_4$.$O$}$\vdots $ $\vdots $ $\vdots $ $\vdots $ $\vdots $ 表 3 两类系统实验数据
Table 3 Experiment data of the two kinds of systems
$4 \sim 7$ $10 \sim 12$ $22 \sim 25$ 30$ \sim $32 ${\rm RPA}_{CTI}$ Agent系统 91.4$ \%$ 72.8$ \%$ 62.3$ \%$ 40.6$ \%$ ${\rm CRQA}_{OVTM}$ Agent系统 97.8$ \%$ 90.2$ \%$ 77.7$ \%$ 68.5$ \%$ -
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