Abstract: We consider the problem of optimizing the economic performance of nonlinear constrained systems subject to uncertain time-varying parameters and bounded disturbances. In particular, we ...

Abstract: To address the locomotion control challenges of asymmetric wheel-legged quadrupedal robots under unknown loads, this paper proposes a Robust Adaptive Model Predictive Control (RA-MPC) ...

More engineers are turning to reinforcement learning to incorporate adaptive and self-tuning control into industrial systems. It aims to strike a balance between traditional ...

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 ...

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 ...

A new technique able to forecast how changes to parameters will impact biomanufacturing processes could revolutionize drug production, save manufacturers time and money, and help increase access to ...

Today’s ac servo systems are much different than those built even 10 years ago. Faster processors and higher resolution encoders are enabling manufacturers to implement amazing advances in tuning ...