The combined use of the closed-loop paradigm, an augmented autonomous state space formulation, partial invariance, local affine difference inclusion, and polytopic invariance are deployed in this paper to propose an NMPC algorithm which, unlike earlier algorithms that have to tackle online a nonlinear non-convex optimization problem, requires the solution of a simple QP. The proposed algorithm is shown to outperform earlier algorithms in respect of size of region of attraction and online computational load. Conversely, for comparable computational loads, the proposed algorithm outperforms earlier algorithms in terms of optimality of dynamic performance. Copyright © 2005 John Wiley and Sons, Ltd
Nonlinear model predictive control (NMPC) and real-time dynamic optimization (RTDO) both based on a ...
This paper presents an approach to efficiently implement Nonlinear Model Predictive Control (NMPC) f...
Abstract. Sensitivity-based strategies for on-line moving horizon estimation (MHE) and nonlinear mod...
This paper provides a review of computationally efficient approaches to nonlinear model predictive c...
The nonlinear model predictive control (NMPC) is an on-line application based on nonlinear convoluti...
© 2017 IEEE. We present PANOC, a new algorithm for solving optimal control problems arising in nonli...
A novel decomposition scheme to solve parametric non-convex programs as they arise in Nonlinear Mode...
This article focuses on the synthesis of computationally friendly sub-optimal nonlinear model predic...
For large numbers of degrees of freedom and/or high dimensional systems, nonlinear model predictive ...
Widespread application of dynamic optimization with fast optimization solvers leads to in-creased co...
Nonlinear Model Predictive Control (NMPC) is a control strategy based on repeatedly solving an optim...
An analytical solution to the nonlinear model predictive control (NMPC) optimization problem is deri...
In nonlinear model predictive control (NMPC), a control task is approached by repeatedly solving an ...
We present and investigate a Newton type method for online optimization in nonlinear model predictiv...
Nonlinear model predictive control (NMPC) suffers from problems of closed loop instability and huge ...
Nonlinear model predictive control (NMPC) and real-time dynamic optimization (RTDO) both based on a ...
This paper presents an approach to efficiently implement Nonlinear Model Predictive Control (NMPC) f...
Abstract. Sensitivity-based strategies for on-line moving horizon estimation (MHE) and nonlinear mod...
This paper provides a review of computationally efficient approaches to nonlinear model predictive c...
The nonlinear model predictive control (NMPC) is an on-line application based on nonlinear convoluti...
© 2017 IEEE. We present PANOC, a new algorithm for solving optimal control problems arising in nonli...
A novel decomposition scheme to solve parametric non-convex programs as they arise in Nonlinear Mode...
This article focuses on the synthesis of computationally friendly sub-optimal nonlinear model predic...
For large numbers of degrees of freedom and/or high dimensional systems, nonlinear model predictive ...
Widespread application of dynamic optimization with fast optimization solvers leads to in-creased co...
Nonlinear Model Predictive Control (NMPC) is a control strategy based on repeatedly solving an optim...
An analytical solution to the nonlinear model predictive control (NMPC) optimization problem is deri...
In nonlinear model predictive control (NMPC), a control task is approached by repeatedly solving an ...
We present and investigate a Newton type method for online optimization in nonlinear model predictiv...
Nonlinear model predictive control (NMPC) suffers from problems of closed loop instability and huge ...
Nonlinear model predictive control (NMPC) and real-time dynamic optimization (RTDO) both based on a ...
This paper presents an approach to efficiently implement Nonlinear Model Predictive Control (NMPC) f...
Abstract. Sensitivity-based strategies for on-line moving horizon estimation (MHE) and nonlinear mod...