Research on self-adaptive height adjustment control of shearer based on deep deterministic policy gradient. [PDF]
Wang Y +8 more
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Differential Transdiagnostic Relevance of Early Maladaptive Schemas Across Personality Traits and Psychopathological Symptoms. [PDF]
Major J, Matuz A, Gács B, Birkás B.
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Designing a cascaded exponential PID controller via starfish optimizer for DC motor and liquid level systems. [PDF]
Izci D +6 more
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Adaptive virtual impedance control strategy based on IWOA-fuzzy PID and its application to reactive power sharing in islanded microgrids. [PDF]
Hou Y.
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Adaptive core-enhanced latent factor model for highly accurate QoS prediction. [PDF]
Ai S, Li P, Fang H, Xia Y.
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An adaptive model predictive control approach for robust load frequency control under renewable energy disturbances. [PDF]
Ayman M, Attia MA, Asim AM.
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PID control system analysis, design, and technology [PDF]
Designing and tuning a proportional-integral-derivative (PID) controller appears to be conceptually intuitive, but can be hard in practice, if multiple (and often conflicting) objectives such as short transient and high stability are to be achieved ...
Yun Li
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In this paper, an index for measuring fragility of proportional integral derivative (PID) controllers is proposed. This index relates the losses of robustness of the control loop when controller parameters change, to the nominal robustness of the control loop. Furthermore, it defines when a PID controller is fragile, nonfragile or resilient.
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Spiking Neural PID Controllers
2011A PID controller is a simple and general-purpose way of providing responsive control of dynamic systems with reduced overshoot and oscillation. Spiking neural networks offer some advantages for dynamic systems control, including an ability to adapt, but it is not obvious how to alter such a control network's parameters to shape its response curve.
Webb, Andrew +2 more
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