Pub Date : 2024-11-02DOI: 10.1016/j.ifacsc.2024.100290
Timm Faulwasser , Arne-Jens Hempel , Stefan Streif
It is well-known that the training of Deep Neural Networks (DNN) can be formalized in the language of optimal control. In this context, this paper leverages classical turnpike properties of optimal control problems to attempt a quantifiable answer to the question of how many layers should be considered in a DNN. The underlying assumption is that the number of neurons per layer—i.e., the width of the DNN—is kept constant. Pursuing a different route than the classical analysis of approximation properties of sigmoidal functions, we prove explicit bounds on the required depths of DNNs based on asymptotic reachability assumptions and a dissipativity-inducing choice of the regularization terms in the training problem. Numerical results obtained for the two spiral task data set for classification indicate that the proposed constructive estimates can provide non-conservative depth bounds.
{"title":"On the turnpike to design of deep neural networks: Explicit depth bounds","authors":"Timm Faulwasser , Arne-Jens Hempel , Stefan Streif","doi":"10.1016/j.ifacsc.2024.100290","DOIUrl":"10.1016/j.ifacsc.2024.100290","url":null,"abstract":"<div><div>It is well-known that the training of Deep Neural Networks (DNN) can be formalized in the language of optimal control. In this context, this paper leverages classical turnpike properties of optimal control problems to attempt a quantifiable answer to the question of how many layers should be considered in a DNN. The underlying assumption is that the number of neurons per layer—i.e., the width of the DNN—is kept constant. Pursuing a different route than the classical analysis of approximation properties of sigmoidal functions, we prove explicit bounds on the required depths of DNNs based on asymptotic reachability assumptions and a dissipativity-inducing choice of the regularization terms in the training problem. Numerical results obtained for the two spiral task data set for classification indicate that the proposed constructive estimates can provide non-conservative depth bounds.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"30 ","pages":"Article 100290"},"PeriodicalIF":1.8,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142579112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-02DOI: 10.1016/j.ifacsc.2024.100289
Lian Chen , Cui Cai , Xijun Liu , Chen Wang
This paper primarily investigates the event-triggered tracking control problem for quadcopter attitude systems, utilizing finite-time zero compensation technology. Unlike existing research results, a zero compensation technology is proposed to solve non-affine control input problems such as saturation, dead zones, and gaps. The command filtered compensation technology is used to solve ’differential explosion’ and filtering errors. A novel Tanh type filter and a neural network are employed to approximate virtual control signals and account for un-modeled dynamics, respectively. Moreover, the finite-time convergence theory is used to prove that the state, tracking error, and filtered error compensation signals in the entire closed-loop system converge to an arbitrarily small neighborhood of the equilibrium origin. Finally, the advantages of the proposed control algorithm in improving tracking accuracy and reducing communication load were demonstrated through simulation.
{"title":"Finite-time event-triggered tracking control for quadcopter attitude systems with zero compensation technology","authors":"Lian Chen , Cui Cai , Xijun Liu , Chen Wang","doi":"10.1016/j.ifacsc.2024.100289","DOIUrl":"10.1016/j.ifacsc.2024.100289","url":null,"abstract":"<div><div>This paper primarily investigates the event-triggered tracking control problem for quadcopter attitude systems, utilizing finite-time zero compensation technology. Unlike existing research results, a zero compensation technology is proposed to solve non-affine control input problems such as saturation, dead zones, and gaps. The command filtered compensation technology is used to solve ’differential explosion’ and filtering errors. A novel Tanh type filter and a neural network are employed to approximate virtual control signals and account for un-modeled dynamics, respectively. Moreover, the finite-time convergence theory is used to prove that the state, tracking error, and filtered error compensation signals in the entire closed-loop system converge to an arbitrarily small neighborhood of the equilibrium origin. Finally, the advantages of the proposed control algorithm in improving tracking accuracy and reducing communication load were demonstrated through simulation.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"30 ","pages":"Article 100289"},"PeriodicalIF":1.8,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-30DOI: 10.1016/j.ifacsc.2024.100291
Bhim Kumar, Muslim Malik
In this article, we have used the concepts of time scales theory to discuss nonlinear switched impulsive systems with delay. Our main objective is to determine the Hyers–Ulam stability and controllability of nonlinear switched impulsive systems with delay on non-uniform time domains. To obtain the necessary and sufficient conditions for existence, Hyers–Ulam stability, and controllability, we utilize the Banach fixed-point theorem and Krasnoselskii’s fixed-point theorem. In order to demonstrate our conclusions, we have discussed some simulation-based examples along with the three tank liquid control problem and a potential practical situation related to the infectious disease with switching rules. The results of this manuscript provide all the necessary and sufficient conditions for Hyers–Ulam stability and controllability that are true for discrete, continuous as well as unified time domains simultaneously.
{"title":"Analysis of Hyers–Ulam stability and controllability of non-linear switched impulsive systems with delays on time scales","authors":"Bhim Kumar, Muslim Malik","doi":"10.1016/j.ifacsc.2024.100291","DOIUrl":"10.1016/j.ifacsc.2024.100291","url":null,"abstract":"<div><div>In this article, we have used the concepts of time scales theory to discuss nonlinear switched impulsive systems with delay. Our main objective is to determine the Hyers–Ulam stability and controllability of nonlinear switched impulsive systems with delay on non-uniform time domains. To obtain the necessary and sufficient conditions for existence, Hyers–Ulam stability, and controllability, we utilize the Banach fixed-point theorem and Krasnoselskii’s fixed-point theorem. In order to demonstrate our conclusions, we have discussed some simulation-based examples along with the three tank liquid control problem and a potential practical situation related to the infectious disease with switching rules. The results of this manuscript provide all the necessary and sufficient conditions for Hyers–Ulam stability and controllability that are true for discrete, continuous as well as unified time domains simultaneously.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"30 ","pages":"Article 100291"},"PeriodicalIF":1.8,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142664061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-30DOI: 10.1016/j.ifacsc.2024.100288
Savin Treanţă , Ramona-Manuela Calianu
In this study, we investigate a class of multi-objective variational control problems governed by nonconvex simple integral functionals. Concretely, we establish and prove (necessary and sufficient) efficiency criteria and dual techniques for some nonconvex multiple cost minimization models. To this aim, we extend and use the concept of -invexity to the case of multi-objective variational control problems. Thereafter, by assuming -invexity, (strictly) -pseudoinvexity and/or -quasiinvexity of the involved functionals, we state the sufficient efficiency criteria and associate a dual problem for the considered model.
{"title":"Efficiency criteria and dual techniques for some nonconvex multiple cost minimization models","authors":"Savin Treanţă , Ramona-Manuela Calianu","doi":"10.1016/j.ifacsc.2024.100288","DOIUrl":"10.1016/j.ifacsc.2024.100288","url":null,"abstract":"<div><div>In this study, we investigate a class of multi-objective variational control problems governed by nonconvex simple integral functionals. Concretely, we establish and prove (necessary and sufficient) efficiency criteria and dual techniques for some nonconvex multiple cost minimization models. To this aim, we extend and use the concept of <span><math><mrow><mo>(</mo><mi>Ψ</mi><mo>,</mo><mi>ω</mi><mo>)</mo></mrow></math></span>-invexity to the case of multi-objective variational control problems. Thereafter, by assuming <span><math><mrow><mo>(</mo><mi>Ψ</mi><mo>,</mo><mi>ω</mi><mo>)</mo></mrow></math></span>-invexity, (strictly) <span><math><mrow><mo>(</mo><mi>Ψ</mi><mo>,</mo><mi>ω</mi><mo>)</mo></mrow></math></span>-pseudoinvexity and/or <span><math><mrow><mo>(</mo><mi>Ψ</mi><mo>,</mo><mi>ω</mi><mo>)</mo></mrow></math></span>-quasiinvexity of the involved functionals, we state the sufficient efficiency criteria and associate a dual problem for the considered model.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"30 ","pages":"Article 100288"},"PeriodicalIF":1.8,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142573448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes the design of a robust fixed-time sliding mode controller for a second-order nonlinear system with matched and unmatched uncertainties. First, a fixed-time stable scalar dynamics with a variable exponent is introduced. We establish the global fixed-time stability results for the proposed dynamics using Lyapunov analysis. The maximum convergence time has been derived in terms of the design parameters, which is independent of the initial conditions. These results are then extended to solve the robust fixed-time stabilization for uncertain nonlinear second-order system. Specifically, we proceed with the sliding mode control design, where the sliding surface and the control law are motivated by the proposed scalar dynamics. Moreover, the proposed design is free from singularity and guarantees fixed-time robust stabilization. Simulation results with comparative analysis has been included. Further, experimental validation on a single link manipulator is provided to demonstrate the performance of the proposed approach.
{"title":"Design of fixed-time sliding mode control using variable exponents","authors":"Krishanu Nath, Neetish Patel, Indra Narayan Kar, Janardhanan Sivaramakrishnan","doi":"10.1016/j.ifacsc.2024.100287","DOIUrl":"10.1016/j.ifacsc.2024.100287","url":null,"abstract":"<div><div>This paper proposes the design of a robust fixed-time sliding mode controller for a second-order nonlinear system with matched and unmatched uncertainties. First, a fixed-time stable scalar dynamics with a variable exponent is introduced. We establish the global fixed-time stability results for the proposed dynamics using Lyapunov analysis. The maximum convergence time has been derived in terms of the design parameters, which is independent of the initial conditions. These results are then extended to solve the robust fixed-time stabilization for uncertain nonlinear second-order system. Specifically, we proceed with the sliding mode control design, where the sliding surface and the control law are motivated by the proposed scalar dynamics. Moreover, the proposed design is free from singularity and guarantees fixed-time robust stabilization. Simulation results with comparative analysis has been included. Further, experimental validation on a single link manipulator is provided to demonstrate the performance of the proposed approach.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"30 ","pages":"Article 100287"},"PeriodicalIF":1.8,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142536179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-09DOI: 10.1016/j.ifacsc.2024.100286
Thomas Claudet , Davide Martire , Damiana Losa , Francesco Sanfedino , Daniel Alazard
Optimizing high-level mission planning constraints is traditionally solved in exponential time and requires to split the problem into several ones, making the connections between them a convoluted task. This paper aims at generalizing recent works on the convexification of Signal Temporal Logic (STL) constraints converting them into linear approximations. Graphs are employed to build general linguistic semantics based on key words (such as Not, And, Or, Eventually, Always), and super-operators (e.g., Until, Imply, If and Only If) based on already defined ones. Numerical validations demonstrate the performance of the proposed approach on two practical use-cases of satellite optimal guidance using a modified Successive Convexification scheme. Finally, a potential hybridization with generative pre-trained language models is showcased.
{"title":"A novel graph-based theory for convexification of mission-planning constraints and generative pre-trained trajectory optimization","authors":"Thomas Claudet , Davide Martire , Damiana Losa , Francesco Sanfedino , Daniel Alazard","doi":"10.1016/j.ifacsc.2024.100286","DOIUrl":"10.1016/j.ifacsc.2024.100286","url":null,"abstract":"<div><div>Optimizing high-level mission planning constraints is traditionally solved in exponential time and requires to split the problem into several ones, making the connections between them a convoluted task. This paper aims at generalizing recent works on the convexification of Signal Temporal Logic (STL) constraints converting them into linear approximations. Graphs are employed to build general linguistic semantics based on key words (such as <em>Not</em>, <em>And</em>, <em>Or</em>, <em>Eventually</em>, <em>Always</em>), and <em>super-operators</em> (e.g., <em>Until</em>, <em>Imply</em>, <em>If and Only If</em>) based on already defined ones. Numerical validations demonstrate the performance of the proposed approach on two practical use-cases of satellite optimal guidance using a modified Successive Convexification scheme. Finally, a potential hybridization with generative pre-trained language models is showcased.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"30 ","pages":"Article 100286"},"PeriodicalIF":1.8,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-26DOI: 10.1016/j.ifacsc.2024.100284
Bálint Szabó , Ákos Szlávecz , Béla Paláncz , Omer S. Alkhafaf , Ameer B. Alsultani , Katalin Kovács , J. Geoffrey Chase , Balázs István Benyó
Insulin dosing of hyperglycemic patients in the intensive care unit (ICU) is a complex and nonlinear clinical control problem. Recent model-based glycemic control protocols predict a patient-specific and time-specific future insulin sensitivity distribution, which defines the future patient state in response to insulin and nutrition inputs. The prediction methods provide a 90% confidence interval for a future insulin sensitivity distribution for a given time horizon, making the prediction problem more specific compared to common prediction problems where the aim is to predict the expected value of the given stochastic parameter. This study proposes three alternative artificial intelligence-based insulin sensitivity prediction methods to improve the prediction accuracy and make prediction parameters better fit the clinical requirements. The proposed prediction methods use different neural network models: a classification deep neural network model, a Mixture Density Network model, and a Quantile Regression-based model. A large patient data set was used to create the neural network models, including 2357 patients and 92646 blood glucose measurements from three clinical sites (Christchurch, New Zealand, Gyula, Hungary, and Liege, Belgium). Prediction accuracy was assessed by statistical metrics expressing clinical requirements, as well as via validated in-silico virtual patient simulations comparing the clinical performance of a proven glycaemic control protocol using the alternative prediction methods to assess impact on glycemic control performance and thus the need for these alternative models.
{"title":"Comparison of three artificial intelligence methods for predicting 90% quantile interval of future insulin sensitivity of intensive care patients","authors":"Bálint Szabó , Ákos Szlávecz , Béla Paláncz , Omer S. Alkhafaf , Ameer B. Alsultani , Katalin Kovács , J. Geoffrey Chase , Balázs István Benyó","doi":"10.1016/j.ifacsc.2024.100284","DOIUrl":"10.1016/j.ifacsc.2024.100284","url":null,"abstract":"<div><div>Insulin dosing of hyperglycemic patients in the intensive care unit (ICU) is a complex and nonlinear clinical control problem. Recent model-based glycemic control protocols predict a patient-specific and time-specific future insulin sensitivity distribution, which defines the future patient state in response to insulin and nutrition inputs. The prediction methods provide a 90% confidence interval for a future insulin sensitivity distribution for a given time horizon, making the prediction problem more specific compared to common prediction problems where the aim is to predict the expected value of the given stochastic parameter. This study proposes three alternative artificial intelligence-based insulin sensitivity prediction methods to improve the prediction accuracy and make prediction parameters better fit the clinical requirements. The proposed prediction methods use different neural network models: a classification deep neural network model, a Mixture Density Network model, and a Quantile Regression-based model. A large patient data set was used to create the neural network models, including 2357 patients and 92646 blood glucose measurements from three clinical sites (Christchurch, New Zealand, Gyula, Hungary, and Liege, Belgium). Prediction accuracy was assessed by statistical metrics expressing clinical requirements, as well as via validated in-silico virtual patient simulations comparing the clinical performance of a proven glycaemic control protocol using the alternative prediction methods to assess impact on glycemic control performance and thus the need for these alternative models.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"30 ","pages":"Article 100284"},"PeriodicalIF":1.8,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142358107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-23DOI: 10.1016/j.ifacsc.2024.100285
Younes Solgi
This study introduces a Non-monotonic Lyapunov (NML) framework aimed at stability evaluation and controller design for continuous-time systems, particularly under conditions of uncertainty. Conventional Lyapunov techniques often exhibit a conservative nature, particularly in the context of uncertain systems, which necessitates the development of less conservative alternatives like NML. The NML methodology distinguishes itself by not imposing strict monotonicity requirements for demonstrating the decrease of a Lyapunov functional. Consequently, this paper derives new stability and stabilization criteria framed as matrix inequalities applicable to a specific class of uncertain systems. The practical applicability of the introduced approach is illustrated through controller design for uncertain systems, exemplified by a nonlinear bilateral teleoperation model. Assorted demonstrative examples and simulation outcomes support the findings, underscoring the NML approach’s efficaciousness.
{"title":"Robust non-monotonic Lyapunov based stability and stabilization methods for continuous-time systems: Applied on bilateral teleoperation system","authors":"Younes Solgi","doi":"10.1016/j.ifacsc.2024.100285","DOIUrl":"10.1016/j.ifacsc.2024.100285","url":null,"abstract":"<div><div>This study introduces a Non-monotonic Lyapunov (NML) framework aimed at stability evaluation and controller design for continuous-time systems, particularly under conditions of uncertainty. Conventional Lyapunov techniques often exhibit a conservative nature, particularly in the context of uncertain systems, which necessitates the development of less conservative alternatives like NML. The NML methodology distinguishes itself by not imposing strict monotonicity requirements for demonstrating the decrease of a Lyapunov functional. Consequently, this paper derives new stability and stabilization criteria framed as matrix inequalities applicable to a specific class of uncertain systems. The practical applicability of the introduced approach is illustrated through controller design for uncertain systems, exemplified by a nonlinear bilateral teleoperation model. Assorted demonstrative examples and simulation outcomes support the findings, underscoring the NML approach’s efficaciousness.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"30 ","pages":"Article 100285"},"PeriodicalIF":1.8,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-16DOI: 10.1016/j.ifacsc.2024.100283
Peter Zentgraf , Abhishek Shivarkar
This paper presents a transparent technique that simulates processes using input and output measurement data without the use of any complex optimization or iterative algorithms. The method is very simple and easy to understand as it comprises only of linear ordinary differential equations, Laplace transformations and least squares technique. The solution can be expressed only in two linear matrix equations. The main aim is to provide bachelor students of engineering with a tool to formulate transfer functions.
The method is validated with artificially generated erroneous measurement data as well as using measurements obtained from a practical application at the university. Inclusion of dead times and estimation of initial conditions make it ideal to be used for various range of applications such as stable and unstable systems with and without damping, open and closed loop systems. Over-integration, normalizing and/or zeroing of different coefficients add more degrees of freedom to improve the model quality.
{"title":"A transparent experimental modelling method for linear multiple-input multiple-output systems","authors":"Peter Zentgraf , Abhishek Shivarkar","doi":"10.1016/j.ifacsc.2024.100283","DOIUrl":"10.1016/j.ifacsc.2024.100283","url":null,"abstract":"<div><div>This paper presents a transparent technique that simulates processes using input and output measurement data without the use of any complex optimization or iterative algorithms. The method is very simple and easy to understand as it comprises only of linear ordinary differential equations, Laplace transformations and least squares technique. The solution can be expressed only in two linear matrix equations. The main aim is to provide bachelor students of engineering with a tool to formulate transfer functions.</div><div>The method is validated with artificially generated erroneous measurement data as well as using measurements obtained from a practical application at the university. Inclusion of dead times and estimation of initial conditions make it ideal to be used for various range of applications such as stable and unstable systems with and without damping, open and closed loop systems. Over-integration, normalizing and/or zeroing of different coefficients add more degrees of freedom to improve the model quality.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"30 ","pages":"Article 100283"},"PeriodicalIF":1.8,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-13DOI: 10.1016/j.ifacsc.2024.100282
Michele Pagone , Giordana Bucchioni , Francesco Alfino , Carlo Novara
This paper explores the application of Nonlinear Model Predictive Control (NMPC) techniques, based on the Pontryagin Minimum Principle, for a minimum-propellant autonomous rendezvous maneuver in non-Keplerian Lunar orbits. The relative motion between the chaser and the target is described by the nonlinear dynamics of the circular restricted three body-problem, posing unique challenges due to the complex and unstable dynamics of near-rectilinear halo orbits. Key aspects of the proposed NMPC include trajectory optimization, maneuver planning, and real-time control, leveraging on its ability to satisfy complex mission requirements while ensuring safe and efficient spacecraft operations and in the presence of input and nonlinear/non-convex state constraints. The proposed formulation allows the design of a minimum-propellant controller, whose optimal control signal results to be bang–bang in time. A case study based on the Artemis III mission – where the docking of the Orion spacecraft to the Gateway station is planned – is illustrated in order to demonstrate the efficiency of the proposed approach, showcasing its potential for enhancing target tracking accuracy, while reducing propellant consumption.
本文探讨了基于庞特里亚金最小原理的非线性模型预测控制（NMPC）技术在非开普勒月球轨道最小推进剂自主交会机动中的应用。追逐者和目标之间的相对运动由圆形受限三体问题的非线性动力学描述，由于近直角光环轨道的动力学复杂且不稳定，因此带来了独特的挑战。拟议的 NMPC 的主要方面包括轨迹优化、机动规划和实时控制，利用其满足复杂任务要求的能力，同时确保航天器在输入和非线性/非凸状态约束下安全高效地运行。所提出的公式允许设计一个最小推进力控制器，其最优控制信号结果在时间上是 "砰砰 "的。为了证明所提方法的效率，展示其在提高目标跟踪精度、减少推进剂消耗方面的潜力，以 Artemis III 任务为基础进行了案例研究--该任务计划将猎户座飞船与网关站对接。
{"title":"Autonomous Lunar rendezvous trajectory planning and control using nonlinear MPC and Pontryagin’s principle","authors":"Michele Pagone , Giordana Bucchioni , Francesco Alfino , Carlo Novara","doi":"10.1016/j.ifacsc.2024.100282","DOIUrl":"10.1016/j.ifacsc.2024.100282","url":null,"abstract":"<div><p>This paper explores the application of Nonlinear Model Predictive Control (NMPC) techniques, based on the Pontryagin Minimum Principle, for a minimum-propellant autonomous rendezvous maneuver in non-Keplerian Lunar orbits. The relative motion between the chaser and the target is described by the nonlinear dynamics of the circular restricted three body-problem, posing unique challenges due to the complex and unstable dynamics of near-rectilinear halo orbits. Key aspects of the proposed NMPC include trajectory optimization, maneuver planning, and real-time control, leveraging on its ability to satisfy complex mission requirements while ensuring safe and efficient spacecraft operations and in the presence of input and nonlinear/non-convex state constraints. The proposed formulation allows the design of a minimum-propellant controller, whose optimal control signal results to be bang–bang in time. A case study based on the Artemis III mission – where the docking of the Orion spacecraft to the Gateway station is planned – is illustrated in order to demonstrate the efficiency of the proposed approach, showcasing its potential for enhancing target tracking accuracy, while reducing propellant consumption.</p></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"30 ","pages":"Article 100282"},"PeriodicalIF":1.8,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142274558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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