This paper discusses an algorithm for efficiently calculating the control moves for constrained nonlinear model predictive control. The approach focuses on real-time optimization strategies that maintain feasibility with respect to the model and constraints at each iteration, yielding a stable technique suitable for suboptimal model predictive control of nonlinear process. We present a simulation to illustrate the performance of our method
Model predictive control is an optimization based form of control that is commonly used in the chemi...
Abstract: This paper investigates application of SQP optimization algorithms to nonlinear model pred...
A computationally inexpensive model predictive control strategy for constrained linear systems is pr...
A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous sol...
Controlling a system and state constraints is one of the most important problems in control theory, ...
Model Predictive Control (MPC) is an optimal control method. At each instant of time, a per-formance...
Nonlinear Model Predictive Controllers determine appropriate control actions by solving an on-line o...
Motivated by a specific manufacturing problem in 1990, Exxon Chemical Company embarked on the develo...
A significant number of Model Predictive Control algorithms solve on-line an appropriate optimizatio...
Nonlinear Model Predictive Controllers determine appropriate control actions by solving an on-line o...
This paper provides a review of computationally efficient approaches to nonlinear model predictive c...
In this paper, nonlinear model predictive control is applied to an inverted pendulum apparatus. The ...
Abstract─While linear model predictive control is popular since the 70s of the past century, only si...
An analytical solution to the nonlinear model predictive control (NMPC) optimization problem is deri...
Model Predictive control (MPC) is shown to be particularly effective for the self-tuning control of ...
Model predictive control is an optimization based form of control that is commonly used in the chemi...
Abstract: This paper investigates application of SQP optimization algorithms to nonlinear model pred...
A computationally inexpensive model predictive control strategy for constrained linear systems is pr...
A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous sol...
Controlling a system and state constraints is one of the most important problems in control theory, ...
Model Predictive Control (MPC) is an optimal control method. At each instant of time, a per-formance...
Nonlinear Model Predictive Controllers determine appropriate control actions by solving an on-line o...
Motivated by a specific manufacturing problem in 1990, Exxon Chemical Company embarked on the develo...
A significant number of Model Predictive Control algorithms solve on-line an appropriate optimizatio...
Nonlinear Model Predictive Controllers determine appropriate control actions by solving an on-line o...
This paper provides a review of computationally efficient approaches to nonlinear model predictive c...
In this paper, nonlinear model predictive control is applied to an inverted pendulum apparatus. The ...
Abstract─While linear model predictive control is popular since the 70s of the past century, only si...
An analytical solution to the nonlinear model predictive control (NMPC) optimization problem is deri...
Model Predictive control (MPC) is shown to be particularly effective for the self-tuning control of ...
Model predictive control is an optimization based form of control that is commonly used in the chemi...
Abstract: This paper investigates application of SQP optimization algorithms to nonlinear model pred...
A computationally inexpensive model predictive control strategy for constrained linear systems is pr...