A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous solution and optimization strategy to solve the model's differential equations. The equations are discretized by equidistant collocation, and along with the algebraic model equations are included as constraints in a nonlinear programming (NLP) problem. This algorithm is compared with the algorithm that uses orthogonal collocation on finite elements. The equidistant collocation algorithm results in simpler equations, providing a decrease in computation time for the control moves. Simulation results are presented and show a satisfactory performance of this algorithm
Abstract─While linear model predictive control is popular since the 70s of the past century, only si...
this paper aims at combining powerful nonlinear modeling techniques with existing linear control tec...
Abstract. Sensitivity-based strategies for on-line moving horizon estimation (MHE) and nonlinear mod...
This paper discusses an algorithm for efficiently calculating the control moves for constrained nonl...
Nonlinear Model Predictive Controllers determine appropriate control actions by solving an on-line o...
The nonlinear model predictive control (NMPC) is an on-line application based on nonlinear convoluti...
In this paper an efficient algorithm for Nonlinear Model Predictive Control is presented. The nonli...
This paper provides a review of computationally efficient approaches to nonlinear model predictive c...
Motivated by a specific manufacturing problem in 1990, Exxon Chemical Company embarked on the develo...
Abstract--This article concerns non-linear control of single-input-single-output processes with inpu...
Model Predictive Control (MPC) is an optimal control method. At each instant of time, a per-formance...
Abstract: In less than two decades, Nonlinear Model Predictive Control (NMPC) has evolved from a con...
Nonlinear Model Predictive Controllers determine appropriate control actions by solving an on-line o...
Abstract: The computational burden, which obstacles Nonlinear Model Predictive Control techniques to...
Many processes in the chemical industry have modest nonlinearities; i.e., linear dynamics play a dom...
Abstract─While linear model predictive control is popular since the 70s of the past century, only si...
this paper aims at combining powerful nonlinear modeling techniques with existing linear control tec...
Abstract. Sensitivity-based strategies for on-line moving horizon estimation (MHE) and nonlinear mod...
This paper discusses an algorithm for efficiently calculating the control moves for constrained nonl...
Nonlinear Model Predictive Controllers determine appropriate control actions by solving an on-line o...
The nonlinear model predictive control (NMPC) is an on-line application based on nonlinear convoluti...
In this paper an efficient algorithm for Nonlinear Model Predictive Control is presented. The nonli...
This paper provides a review of computationally efficient approaches to nonlinear model predictive c...
Motivated by a specific manufacturing problem in 1990, Exxon Chemical Company embarked on the develo...
Abstract--This article concerns non-linear control of single-input-single-output processes with inpu...
Model Predictive Control (MPC) is an optimal control method. At each instant of time, a per-formance...
Abstract: In less than two decades, Nonlinear Model Predictive Control (NMPC) has evolved from a con...
Nonlinear Model Predictive Controllers determine appropriate control actions by solving an on-line o...
Abstract: The computational burden, which obstacles Nonlinear Model Predictive Control techniques to...
Many processes in the chemical industry have modest nonlinearities; i.e., linear dynamics play a dom...
Abstract─While linear model predictive control is popular since the 70s of the past century, only si...
this paper aims at combining powerful nonlinear modeling techniques with existing linear control tec...
Abstract. Sensitivity-based strategies for on-line moving horizon estimation (MHE) and nonlinear mod...