Review on model predictive control: An engineering perspective
Abstract Model-based predictive control (MPC) describes a set of advanced control
methods, which make use of a process model to predict the future behavior of the controlled …
methods, which make use of a process model to predict the future behavior of the controlled …
Objectives, challenges, and prospects of batch processes: Arising from injection molding applications
Injection molding, a polymer processing technique that converts thermoplastics into a variety
of plastic products, is a complicated nonlinear dynamic process that interacts with a different …
of plastic products, is a complicated nonlinear dynamic process that interacts with a different …
Two-dimensional reinforcement learning model-free fault-tolerant control for batch processes against multi-faults
Aiming at the characteristics of batch process changing along with time and batch directions,
the existence of unmodeled dynamics, and the partial failure of actuators or/and sensors, we …
the existence of unmodeled dynamics, and the partial failure of actuators or/and sensors, we …
Model-free adaptive iterative learning control method for the Czochralski silicon monocrystalline batch process
JC Ren, D Liu, Y Wan - IEEE Transactions on Semiconductor …, 2021 - ieeexplore.ieee.org
Model-based control methods do not produce satisfactory control results with the batch
process control of Czochralski (CZ) silicon monocrystalline with complex nonlinearity, large …
process control of Czochralski (CZ) silicon monocrystalline with complex nonlinearity, large …
Iterative learning model predictive control based on iterative data-driven modeling
L Ma, X Liu, X Kong, KY Lee - IEEE transactions on neural …, 2020 - ieeexplore.ieee.org
Iterative learning model predictive control (ILMPC) has been recognized as an effective
approach to realize high-precision tracking for batch processes with repetitive nature …
approach to realize high-precision tracking for batch processes with repetitive nature …
Neural network-based iterative learning control for trajectory tracking of unknown SISO nonlinear systems
This paper proposes a neural network-based (NN-based) data-driven iterative learning
control (ILC) algorithm for the tracking problem of nonlinear single-input single-output (SISO) …
control (ILC) algorithm for the tracking problem of nonlinear single-input single-output (SISO) …
Terminal constrained robust hybrid iterative learning model predictive control for complex time-delayed batch processes
This work mainly addresses terminal constrained robust hybrid iterative learning model
predictive control against time delay and uncertainties in a class of complex batch processes …
predictive control against time delay and uncertainties in a class of complex batch processes …
Iterative learning control with data-driven-based compensation
S He, W Chen, D Li, Y **_Method/links/65119011c05e6d1b1c3134e3/Eye-in-Hand-Visual-Servoing-Control-of-Robot-Manipulators-Based-on-an-Input-Map**-Method.pdf" data-clk="hl=fr&sa=T&oi=gga&ct=gga&cd=9&d=15722476407912073689&ei=k-KtZ5r-OoC96rQP29mI6AY" data-clk-atid="2QkP4_10MdoJ" target="_blank">[PDF] researchgate.net
Eye-in-hand visual servoing control of robot manipulators based on an input map** method
In image-based visual servoing (IBVS), parametric uncertainties tend to cause the model
inaccuracy and limit the control performance. Considering these uncertainties can be …
inaccuracy and limit the control performance. Considering these uncertainties can be …