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针对阳离子聚合反应器的温度分布建模与控制问题,提出了一种基于B样条神经网络的广义PI控制方法.首先采用B样条复合网络建立分布函数的动态和静态模型,并基于该模型,将分布函数的跟踪问题等效为动态权值向量的时间域跟踪问题.最后给出一种新型的广义PI控制方法,实现对给定温度分布的跟踪控制.同时,为了更好地抑制未知干扰、参数摄动以及模型不匹配等问题,模型权值状态、模型输出与实测温度分布所对应的权值误差都被引入到反馈控制回路,因此能够大大增强系统的鲁棒性与抗干扰能力.仿真结果表明该方法的可行性.  相似文献
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In this article, we attempt a reapproachment between sliding mode control of linear systems and classical control through the possibilities of evading state measurements and circumventing the use of asymptotic state observers in the sliding surface synthesis. This is shown to be possible thanks to the use of integral state reconstructors combined with iterated integral output error compensation. The proposed scheme is also robust with respect to unmatched perturbation inputs. A connection between sliding modes and classical analog Δ‐modulators, and their natural generalization, is also brought to attention as a tool for the realization of integral reconstructor based sliding mode control schemes.  相似文献
3.
In this note we propose a control strategy which combines sliding modes and generalized PI (GPI) control for the swinging up, and stabilization around its unstable vertical position of the inertia wheel pendulum. Both tasks are achieved using a single controller. The pendulum angular position is assumed to be the only measured output variable. We show that this control scheme is robust with respect to constant torque disturbances. The proposed controller is used in an actual experimental setup.  相似文献
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