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摘要: 针对电力巡检机器人(Power-line inspection robot, PLIR)的平衡调节问题, 设计了广义二型模糊逻辑控制器(General type-2 fuzzy logic controller, GT2FLC); 针对GT2FLC中隶属函数参数难以确定的问题, 通过模糊粒子群(Fuzzy particle swarm optimization, FPSO)算法来优化隶属函数参数. 将GT2FLC的控制性能与区间二型模糊逻辑控制器(Interval type-2 fuzzy logic controller, IT2FLC)和一型模糊逻辑控制器(Type-1 fuzzy logic controller, T1FLC) 的控制性能进行对比. 除此之外, 还考虑了外部干扰对三种控制器控制效果的影响. 仿真结果表明, GT2FLC具有更好的性能和处理不确定性的能力.
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关键词:
- 广义二型模糊逻辑控制器 /
- 隶属函数 /
- 模糊粒子群 /
- 电力巡检机器人
Abstract: A general type-2 fuzzy logic controller (GT2FLC) is designed to control the balance of a power-line inspection robot (PLIR). Because it is difficult to determine parameters of membership function in GT2FLC, the fuzzy particle swarm optimization (FPSO) is applied to optimize the parameters of membership function in GT2FLC. The performance of GT2FLC is compared with the performance of the type-1 fuzzy logic controller (T1FLC) and interval type-2 fuzzy logic controller (IT2FLC). Furthermore, the influence of external disturbances on the control effect of the PLIR is considered. According to simulations, the performance of GT2FLC is better than performance of other controllers, and the GT2FLC has better ability to deal with uncertainties. -
图 6 PLIR平衡控制和优化原理图
Fig. 6 The diagram of balance control and optimization for the PLIR
图 8 优化前
${{\tilde \theta }_1}$ 对应的FOUFig. 8 The FOU for
${{\tilde \theta }_1}$ without optimization
图 9 优化前
${{{\dot{\tilde{\theta }}}}_{2}}$ 对应的FOUFig. 9 FOU for
${{{\dot{\tilde{\theta }}}}_{2}}$ without optimization
图 10 优化后
${{\tilde \theta }_1}$ 对应的FOUFig. 10 The FOU for
${{\tilde \theta }_1}$ with optimization
图 11 优化后
${{{\dot{\tilde{\theta }}}}_{2}}$ 对应的FOUFig. 11 The FOU for
${{{\dot{\tilde{\theta }}}}_{2}}$ with optimization
图 12 无干扰下
$\theta_1$ 和$\dot{\theta}_1$ 的响应Fig. 12 Responses of
$\theta_1$ and$\dot{\theta}_1$ without disturbance
图 13 无干扰下
$\theta_2$ 和$\dot{\theta}_2$ 的响应Fig. 13 Responses of
$\theta_2$ and$\dot{\theta}_2$ without disturbance
图 14 有干扰下
$\theta_1$ 和$\dot{\theta}_1$ 的响应Fig. 14 Responses of
$\theta_1$ and$\dot {\theta}_1$ with disturbances
图 15 有干扰下
$\theta_2$ 和$\dot{\theta}_2$ 的响应Fig. 15 Responses of
$\theta_2$ and$\dot{\theta}_2$ with disturbances表 1 PLIR对应参数值
Table 1 Values of parameters for the PLI robot
参数 参数值 参数 参数值 $m_1\, ({\rm{kg} })$ 63 $m_2\,({\rm{kg} })$ 27 $h_1\,({\rm{m} })$ 0.18 $h_{20}\,({\rm{m} })$ 0.42 $l \,({\rm{m} })$ 0.5 $h\,({\rm{m} })$ 0.5 
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表 2 FPSO惯性权重调整模糊规则表
Table 2 The rulebase of adjustment for inertia weight in FPSO
$\omega$ $Nite$ NB NS ZO PS PB $Nfit$ NB ZO PS PS PB PB NS NS ZO PS PB PB ZO NS NS ZO PS PS PS NB NB NS ZO PS PB NB NB NS NS ZO
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表 3 PLIR平衡调节模糊规则表
Table 3 The rulebase of balance adjustment for the PLIR
u2 ${{{\tilde \theta }_1}}$ NB NS ZO PS PB ${{{\dot{\tilde{\theta }}}}_{1}}$ NB PB PB PS PS ZO NS PB PB PS ZO NS ZO PS PS ZO NS NS PS PS ZO NS NB NB PB ZO NS NS NB NB
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表 4 无干扰下平均评价指标
Table 4 Average evaluation index without disturbance
控制器 ISE IAE ITAE T1FLC-PSO 0.02660 0.14820 0.08061 IT2FLC-PSO 0.02655 0.14238 0.06800 GT2FLC-PSO 0.02655 0.14290 0.06914 T1FLC-FPSO 0.02656 0.14534 0.07417 IT2FLC-FPSO 0.02653 0.14236 0.06732 GT2FLC-FPSO 0.02654 0.14127 0.06536
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表 5 有干扰下平均评价指标
Table 5 Average evaluation index with disturbances
控制器 ISE IAE ITAE T1FLC-PSO 0.07380 0.39140 1.76303 IT2FLC-PSO 0.06907 0.37776 1.69851 GT2FLC-PSO 0.06856 0.37537 1.68996 T1FLC-FPSO 0.07376 0.38991 1.75956 IT2FLC-FPSO 0.06875 0.37773 1.69275 GT2FLC-FPSO 0.06857 0.37414 1.68423
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