Dynamic optimization and optimal control problems form the backbone of numerous applications in engineering, economics and the natural sciences. These methodologies involve determining a time-varying ...

Differential equations and systems analysis. Undergraduate controls and/or signal processing course would satisfy this requirement. A graduate-level systems course is also helpful, but not necessary.

Wuhan Zhonghe Shili Automation Technology Co., Ltd. applied for a patent titled "An AI-Optimized Control Method and System for Water-Based Glue Coating" in August 2025, with publication number ...

Applying model-predictive methods and a continuous process-control framework to a continuous tablet-manufacturing process. Currently, there is a high level of interest in the pharmaceutical industry ...

Stochastic control problems that arise in reliability and maintenance optimization typically assume that information used for decision-making is obtained according to a predetermined sampling schedule ...

Khan, Akhtar A. and Dumitru Motreanu. "Existence Theorems for Elliptic and Evolutionary." J Optim Theory Appl 167. (2015): 1136—1161. Print. * Jadamba, B., et al. "Identification of Flexural Rigidity ...

Not feeling yourself, even with “normal” labs? Apollo Health Optimization goes beyond baseline to help you feel truly optimal ...

Like octopuses squeezing through a tiny sea cave, metatruss robots can adapt to demanding environments by changing their shape. These mighty morphing robots are made of trusses composed of hundreds of ...

Model Predictive Control (MPC) is a modern feedback law that generates the control signal by solving an optimal control problem at each sampling time. This approach is capable of maximizing a certain ...