Recently, model predictive control (MPC) is increasingly applied to path tracking of mobile
devices, such as mobile robots. The characteristics of these MPC-based controllers are not …

The learning-based model predictive control (LB-MPC) is an effective and critical method to
solve the path tracking problem in mobile platforms under uncertain disturbances. It is well …

Physics-informed neural networks (PINNs) incorporate established physical principles into
the training of deep neural networks, ensuring that they adhere to the underlying physics of …

Non-holonomic wheeled mobile robots (WMRs) are highly uncertain, multi-input multi-output
(MIMO), non-linear dynamic systems that are expected to perform under varying …

Robot trajectory tracking control based on differential-algebraic equation (DAE) models is
still a thorny issue, because the DAEs of such systems are inherently complex and unstable …

Compared to omnidirectional wheel robots and Mecanum wheel robots, four-wheel
independent steering (4WIS) robots are more efficient. In recent years, 4WIS robot become …

This article proposes an adaptive trajectory tracking control scheme for low-speed car-like
vehicles with less efforts in tuning of the control gains. An interesting way of integrating …

Mobile medical robots have been widely used in various structured scenarios, such as
hospital drug delivery, public area disinfection, and medical examinations. Considering the …

Nonlinear model predictive control (NMPC) of industrial processes is changeling in part
because the model of the plant may not be completely known but also for being …