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Application of Terminal Region Enlargement Approach for Discrete Time Quasi Infinite Horizon NMPC [article]

Chinmay Rajhans, Sowmya Gupta
2021 arXiv   pre-print
Approaches available in the literature provide limited degrees of freedom for the characterization of the terminal region for the discrete time Quasi Infinite Horizon NMPC (QIH-NMPC) formulation.  ...  Current work presents alternate approaches namely arbitrary controller based approach and LQR based approach, which provide large degrees of freedom for enlarging the terminal region.  ...  The term Quasi Infinite is because of the fact that the NMPC formulation depicts the stability properties of the infinite horizon formulation, however, the actual implementation contains finite horizon  ... 
arXiv:2107.09267v1 fatcat:xzrylcgd5ngofmghiai4fedshm

Nonlinear Controller Design with Prediction Horizon Time Reduction Applied to Unstable CSTR System [article]

Chinmay Rajhans, Sowmya Gupta
2021 arXiv   pre-print
Current work presents alternate approaches namely arbitrary controller based approach and linear quadratic regulator based approach, which provide larger degrees of freedom for enlarging the terminal region  ...  As a result, there is significant reduction in the prediction and control horizon time.  ...  Although the approaches developed for the discrete time QIH-NMPC formulations provide large degrees of freedom for enlarging the terminal region, however, their application to continuous time QIH-NMPC  ... 
arXiv:2108.00689v1 fatcat:5xjpsejumjhbpmdug77v2xovum

A Framework for Quasi Time-Optimal Nonlinear Model Predictive Control with Soft Constraints [article]

Jawad Ismail, Steven Liu
2020 arXiv   pre-print
This paper tackles the time-optimal control problem and proposes a novel approach, which explicitly addresses the vibrational behavior in the context of the receding horizon technique.  ...  Such technique is a key feature, especially for systems with a time-varying vibrational behavior.  ...  Zhao et al. (2004) introduced a quasi time-optimal NMPC, which is formulated in standard regulator NMPC form, with time-dependency on the terminal cost and fixed horizon length.  ... 
arXiv:2005.02994v2 fatcat:kvng2r22q5egjnr2rkpp3hzl74

Explicit nonlinear model predictive control of the air path of a turbocharged spark-ignited engine

Jamil El Hadef, Sorin Olaru, Pedro Rodriguez-Ayerbe, Guillaume Colin, Yann Chamaillard, Vincent Talon
2013 2013 IEEE International Conference on Control Applications (CCA)  
In order to reduce time-to-market and development costs, recent research has investigated the idea of a quasi-systematic engine control development approach.  ...  In this paper, we present the synthesis of a physics-based nonlinear model predictive control law especially designed for powertrain control.  ...  The NMPC formulation (5-10) avoids the use of a terminal penalty term and terminal constraints [19] .  ... 
doi:10.1109/cca.2013.6662746 dblp:conf/IEEEcca/HadefORCCT13 fatcat:nr3ih7ib4fb3lhm533sdxen4jq

Considerations on nonlinear model predictive control techniques

Flavio Manenti
2011 Computers and Chemical Engineering  
The nonlinear model predictive control (NMPC) is an on-line application based on nonlinear convolution models.  ...  Beyond a short review of the state-of-the-art, the paper is aimed at highlighting the possibility to exploit at best the intrinsic features of the specific system one is going to control using the NMPC  ...  Real-time dynamic optimization The real-time dynamic optimization is based on the same moving horizon methodology of the NMPC and the time scale involved is not so far from NMPC scale.  ... 
doi:10.1016/j.compchemeng.2011.04.009 fatcat:ykwlnnhymndh7hj7muqposvbae

Model Predictive Control for Block-oriented Nonlinear Systems with Input Constraints [chapter]

Hai-Tao Zhang
2011 Advanced Model Predictive Control  
Meanwhile, these approaches can effectively enlarge the closed-loop stable area so as to extend the feasible working region and improve the reliability of the control systems in real process industrial  ...  In sum, this chapter developed some new NMPC methods for block-oriented nonlinearities with input constraints.  ...  In order to enlarge the asymptotically stable region for constrained nonlinear systems, Chen and Allgöwer (14) developed a quasi-infinite horizon Nonlinear Model Predictive Control (NMPC) algorithms based  ... 
doi:10.5772/17752 fatcat:a75yfpis6bhbxc2nnv6iwdfzwy

Multirate sliding mode disturbance compensation for model predictive control

D. M. Raimondo, M. Rubagotti, C. N. Jones, L. Magni, A. Ferrara, M. Morari
2014 International Journal of Robust and Nonlinear Control  
In this paper, a novel hierarchical multirate control scheme for nonlinear discrete-time systems is presented, consisting of a robust Nonlinear Model Predictive Controller (NMPC) and a Multirate Sliding  ...  computational burden) to those of NMPC (optimality, constraints handling).  ...  Indeed, as expected for any discrete-time sliding mode approach, the system state is kept on a boundary layer of the sliding manifold, which means that a quasi-sliding mode [26] is enforced.  ... 
doi:10.1002/rnc.3244 fatcat:mzqnxdgahvfb7aw23tksynjzbe

A simple and efficient algorithm for nonlinear model predictive control

Lorenzo Stella, Andreas Themelis, Pantelis Sopasakis, Panagiotis Patrinos
2017 2017 IEEE 56th Annual Conference on Decision and Control (CDC)  
The lowmemory requirements and simple implementation make our method particularly suited for embedded NMPC applications.  ...  We present PANOC, a new algorithm for solving optimal control problems arising in nonlinear model predictive control (NMPC).  ...  The first two authors are also affiliated with the IMT School for Advanced Studies Lucca, Piazza S. Francesco 17, 55100 Lucca, Italy.  ... 
doi:10.1109/cdc.2017.8263933 dblp:conf/cdc/StellaTSP17 fatcat:e4dsequkn5gvbg47jwrqqk7saq

A Simple and Efficient Algorithm for Nonlinear Model Predictive Control [article]

Lorenzo Stella, Andreas Themelis, Pantelis Sopasakis, Panagiotis Patrinos
2017 arXiv   pre-print
The low-memory requirements and simple implementation make our method particularly suited for embedded NMPC applications.  ...  We present PANOC, a new algorithm for solving optimal control problems arising in nonlinear model predictive control (NMPC).  ...  Typically this NLP represents a discrete-time approximation of the continuous-time, and thus infinite-dimensional, constrained nonlinear optimal control problem, within a direct optimal control framework  ... 
arXiv:1709.06487v1 fatcat:vztsqfngofbqji653j522cg2om

Optimal power flow: an introduction to predictive, distributed and stochastic control challenges

Timm Faulwasser, Alexander Engelmann, Tillmann Mühlpfordt, Veit Hagenmeyer
2018 at - Automatisierungstechnik  
Moreover, we sketch open questions that might be of interest for the systems and control community.  ...  Based on a concise problem statement, we introduce a common description of optimal power flow variants including multi-stage problems and predictive control, stochastic uncertainties, and issues of distributed  ...  Thus, in real-world applications (multi-stage quasi-stationary) opf problems are subject to hidden constraints that can be expressed as discrete-time dynamics.  ... 
doi:10.1515/auto-2018-0040 fatcat:sa3jdyjcm5hivhpiqxxyp62lie

Dual-mode predictive control algorithm for constrained Hammerstein systems

Hai-Tao Zhang, Han-Xiong Li, Guanrong Chen
2008 International Journal of Control  
In detail, over a finite horizon, an optimal input profile found by solving a open-loop optimal control problem drives the non-linear system state into the terminal invariant set; afterwards a linear output-feedback  ...  With this TS-SCIA as the inner model, a dual-mode non-linear model predictive control (NMPC) algorithm is developed.  ...  In order to enlarge the asymptotically stable region for constrained non-linear systems, Chen and Allgo¨wer (1998b) developed a quasi-infinite horizon non-linear model predictive control (NMPC) algorithms  ... 
doi:10.1080/00207170701885453 fatcat:pdxnyfhdmzcefjjswhtswftssq

Real-time moving horizon planning and control of aerial systems under uncertainties [article]

Mohamed Sayed Ibrahim Korany, Universitäts- Und Landesbibliothek Sachsen-Anhalt, Martin-Luther Universität, Rolf Findeisen, Eric Bullinger
2021
This work proposes model predictive control as a suitable method to tackle combined planning and control challenges for aircraft applications.  ...  Using model predictive control for load alleviation allows enlarging the flight envelops and improving fatigue life and aircraft performance, such as passenger comfort.  ...  To avoid this problem, the terminal region constraint and/or the terminal penalty have been proposed which determines an upper bound of the infinite-horizon cost.  ... 
doi:10.25673/36359 fatcat:3hk56k2g5fhylnqcxrvydu2n34

Model predictive energy management for induction motor drives and all-wheel-drive battery electric vehicles : a flatness based approach [article]

Bernhard Rolle, Universität Stuttgart
2021
Due to a wide spectrum of involved time constants in the range of seconds to a few milliseconds, efficiency analyses of electric vehicles rarely follow model-based approaches and instead rely on characteristic  ...  The modeling approach focuses on loss processes associated with the energy conversion of the voltage source inverters and induction motors.  ...  penalty is imposed on the terminal state variable via the distance function ϑ f . No terminal constraint is used, since the terminal state may not be reached within the consider time horizon.  ... 
doi:10.18419/opus-11446 fatcat:6wmtcwzopvchnerd6kay5igxje

Defect minimizing control of low pressure die casting

XinMei Shi
2012
The resulting MIMO state-space model facilitated the design of a controller for this process.  ...  Current strategies for eliminating macro-porosity focus on the execution of pre-set casting cycles, die structure design or the combination of both.  ...  A good example of a linear discrete-time control model application in die casting is that of Maijer et al.  ... 
doi:10.14288/1.0072882 fatcat:ejh6jobot5g7zhb4petcihjc2a

Numerical optimal control with applications in aerospace

Yuanbo Nie, Eric Kerrigan, Rafael Palacios Nieto
2021
A general approach for direct implementation of rate constraints on the discretization mesh is proposed.  ...  The last part of this work focuses on the use of DOPs in aerospace applications, with a number of topics studied.  ...  different when considering a single solve of the DOP on a given discretization mesh, especially considering on-line NMPC applications.  ... 
doi:10.25560/87136 fatcat:hmj7xae3nnb7xiwbkdw22kdjqi
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