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This paper considers the optimal control of a second-order nonlinear system with unknown dynamics. A new reinforcement learning based approach is proposed with the aid of direct adaptive control. By the new approach actor-critic reinforcement learning algorithms are proposed with three neural network approximation. Simulation results are presented to show the effectiveness of the proposed algorithms. 

Shear forces between cells occur during global changes in multicellular organization during morphogenesis and tissue growth, yet how cells sense shear forces and propagate a response across a tissue is unknown. We found that applying exogenous shear at the midline of an epithelium induced a local, short-term deformation near the shear plane, and a long-term collective oscillatory movement across the epithelium that spread from the shear-plane and gradually dampened. Inhibiting actomyosin contraction or E-cadherin trans-cell adhesion blocked oscillations, whereas stabilizing actin filaments prolonged oscillations. Combining these data with a model of epithelium mechanics supports a mechanism involving the generation of a shear-induced mechanical event at the shear plane which is then relayed across the epithelium by actomyosin contraction linked through E-cadherin. This causes an imbalance of forces in the epithelium, which is gradually dissipated through oscillatory cell movements and actin filament turnover to restore the force balance across the epithelium. 

Climate change is increasing the frequency and severity of short-term (~1 y) drought events—the most common duration of drought—globally. Yet the impact of this intensification of drought on ecosystem functioning remains poorly resolved. This is due in part to the widely disparate approaches ecologists have employed to study drought, variation in the severity and duration of drought studied, and differences among ecosystems in vegetation, edaphic and climatic attributes that can mediate drought impacts. To overcome these problems and better identify the factors that modulate drought responses, we used a coordinated distributed experiment to quantify the impact of short-term drought on grassland and shrubland ecosystems. With a standardized approach, we imposed ~a single year of drought at 100 sites on six continents. Here we show that loss of a foundational ecosystem function—aboveground net primary production (ANPP)—was 60% greater at sites that experienced statistically extreme drought (1-in-100-y event) vs. those sites where drought was nominal (historically more common) in magnitude (35% vs. 21%, respectively). This reduction in a key carbon cycle process with a single year of extreme drought greatly exceeds previously reported losses for grasslands and shrublands. Our global experiment also revealed high variability in drought response but that relative reductions in ANPP were greater in drier ecosystems and those with fewer plant species. Overall, our results demonstrate with unprecedented rigor that the global impacts of projected increases in drought severity have been significantly underestimated and that drier and less diverse sites are likely to be most vulnerable to extreme drought.