To address the perturbation of formation multiple unmanned aerial vehicles (UAVs) subject to external disturbances, an algorithm distributed Kalman model predictive control is proposed in this paper improve accuracy maintaining a flight. A UAV two-order discrete-time system was built before devising prediction based on standard model. The desired configuration and neighbor optimal state estimat...

Typical production objectives in distillation process require the delivery of products whose compositions meet certain specifications. The distillation control system, therefore, must hold product compositions as near the set points as possible in faces of upset. In this project, inferential model predictive control, that utilizes an artificial neural network estimator and model predictive cont...

Reinforcement learning (RL) methods have demonstrated their efficiency in simulation. However, many of the applications for which RL offers great potential, such as autonomous driving, are also safety critical and require a certified closed-loop behavior order to meet specifications presence physical constraints. This article introduces concept called probabilistic model predictive certificatio...