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Application of Terminal Region Enlargement Approach for Discrete Time Quasi Infinite Horizon NMPC
[article]
2021
arXiv
pre-print
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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]
2021
arXiv
pre-print
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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]
2020
arXiv
pre-print
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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
2013
2013 IEEE International Conference on Control Applications (CCA)
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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
2011
Computers and Chemical Engineering
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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]
2011
Advanced Model Predictive Control
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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
2014
International Journal of Robust and Nonlinear Control
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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
2017
2017 IEEE 56th Annual Conference on Decision and Control (CDC)
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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]
2017
arXiv
pre-print
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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
2018
at - Automatisierungstechnik
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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
2008
International Journal of Control
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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]
2021
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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]
2021
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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
2012
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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
2021
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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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