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首页> 外文期刊>International journal of reasoning-based intelligent systems >Complex electromechanical system condition monitoring based on improved particle swarm optimisation RBF for audio visual fusion
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Complex electromechanical system condition monitoring based on improved particle swarm optimisation RBF for audio visual fusion

机译:基于改进粒子群优化RBF的视听融合复杂机电系统状态监测

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摘要

To improve transient stability of multi-generator power system, continuous high-order sliding mode excitation control strategy is put forward. Power angle deviation of each generator is the variable of sliding mode. Nonlinear and uncertain high-order sliding mode control of multi-generator power system is transferred into limited time stability problem of uncertain integral chain system. Limited time convergence of system condition is realised and overcoming uncertainty, such as unmodeled dynamics of system, measuring error and external disturbance, etc., through combination of controller and geometric homogeneous continuous control law and second-order sliding mode super-twisting algorithm. Power angle differential with precise robust differentiator is observed. Limited time stability of closed-loop system theoretically is analysed and verified. High-order sliding mode excitation controller designed can keep voltage stability at generator terminal and improves transient stability of power system effectively. Simulation result aimed at three-generator system verifies effectiveness of control method mentioned.
机译:为了提高多发电机电力系统的暂态稳定性,提出了连续的高阶滑模励磁控制策略。每个发电机的功率角偏差是滑模的变量。将多发电机电力系统的非线性不确定高阶滑模控制转化为不确定整体链系统的有限时间稳定性问题。通过控制器和几何均匀连续控制律以及二阶滑模超扭曲算法的结合,实现了系统状态的有限时间收敛,克服了系统动力学建模,测量误差和外部干扰等不确定性。观察到具有精确鲁棒微分器的功率角微分。从理论上分析和验证了闭环系统的时限稳定性。设计的高阶滑模励磁控制器可以保持发电机端电压稳定,有效提高电力系统的暂态稳定性。针对三发电机系统的仿真结果验证了所提控制方法的有效性。

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