一种新型稳定平台伺服控制系统

深入研究了三自由度并串联混合机构稳定平台,设计了一个非线性自适应控制器。考虑到实际系统工作中存在摩擦、负载扰动和动力学参数误差,分离出动力学模型中的未建模动力学参数、摩擦力参数和负载扰动,建立了关于待辨识参数的线性动力学模型。运用Lyapunov方法设计了一个非线性自适应控制器。构建了并串联光电稳定平台伺服系统实验平台。分别将所设计的控制器与计算力矩控制器分别在高速和低速扰动情况进行了实验,实验表明所提出非线性自适应控制器在低速0.006(°)/s时,跟踪精度分别为滚转轴0.071°、俯仰轴0.064°、偏转轴0.038°,在20(°)/s高速状态下,跟踪精度分别为滚转轴0.045°、俯仰轴0.042°、偏转轴0.029°,其控制效果明显好于传统控制。     

Computational model investigating the effect of magnetic field on neural-astrocyte microcircuit

Extremely low-frequency magnetic field is widely used as a noninvasive stimulation method in clinical practice and basic research. Electrical field induced from magnetic pulse can decrease or increase neuronal electrical activity. However, the cellular mechanism underlying the effects of magnetic field is not clear from experimental data. Recent studies have demonstrated that "non-neuronal" cells, especially astrocytes, may be the potential effector for transcranial magnetic stimulation (TMS). In the present study, we implemented a neural-astrocyte microcircuit computational model based on hippocampal architecture to investigate the biological effects of different magnetic field frequencies on cells. The purpose of the present study is to elucidate the main influencing factors of MS to allow a better understanding of its mechanisms. Our model reproduced the basic characteristics of the neuron and astrocyte response to different magnetic stimulation. The results predict that interneurons with lower firing thresholds were more active in magnetic fields by contrast to pyramidal neurons. And the synaptic coupling strength between the connected neurons may be one of the critical factor to affect the effect of magnetic field on cells. In addition, the simulations show that astrocytes can decrease or increase slow inward currents (SICs) to finely tune neuronal excitation, which suggests their key role in excitatory-inhibitory balance. The interaction between neurons and astrocytes may represent a novel target for effective therapeutic strategies involving magnetic stimulation.