SBIR PHASE I: Advanced Adaptive Critic Designs for Optimization and Control of Complex Nonlinear Dynamic Systems

这个小型企业创新研究(SBIR)第一阶段项目将设计一种基于自适应批评者的控制器，用于复杂的大范围、多目标系统的优化控制，这些系统表现出非线性动态。目前实现的自适应批评控制器通常在小规模问题上工作得很好，但在复杂的大规模问题上收敛速度很慢。此外，优化性能和相互竞争的目标的需要使得自适应批评控制器的学习和收敛变得困难。第一阶段将在一个典型但具有挑战性的问题上演示这种自适应批评控制器：在标准行驶周期内优化汽车驾驶特性。该控制器将优化油门控制、加速、减速和制动，以最大限度地减少整个赛程的能量消耗，同时在最小的时间跨度内穿越自行车。这类似于长途卡车司机寻找最优的油门踏板和刹车控制序列，以在最短的时间内从纽约到洛杉矶，并消耗最少的燃料(并在其间穿行于丘陵和山脉之间)。这种自适应批评控制器的商业应用有望在半导体制造和飞行控制以及汽车控制问题中得到应用。

This Small Business Innovation Research (SBIR) Phase I project will design an adaptive critic based controller for use in optimizing control of complex large-scale, multi-goal systems which exhibit nonlinear dynamics. Currently implemented Adaptive Critic controllers often work well on small-scale problems, but convergence is slow on complex large-scale problems. In addition, the need to optimize performance with competing goals makes learning and convergence of adaptive critic controllers difficult. Phase I will demonstrate this adaptive critic controller on a typical but challenging problem: optimization of auto driving characteristics over a standard driving cycle. The controller will optimize throttle control, acceleration, deceleration, and braking so as to minimize energy expenditure over the course while also traversing the cycle in a minimum time span. This is similar to a long-haul truck driver searching for an optimal sequence of gas pedal and brake controls to go from New York to Los Angeles in minimum time and burning minimum fuel (and traveling through hills and mountains in between). Commercial applications of adaptive critic controllers of this kind are expected semiconductor manufacturing and flight control as well as in the automotive control problem.