Pub Date : 2020-07-01DOI: 10.23919/ACC45564.2020.9147473
Rollen S. D’Souza, Christopher Nielsen
Path planning and following together constitute a critical part of the decision-making hierarchy in autonomous ground vehicles. One of the simplest instances of this architecture is when the path planner generates waypoints that define a sequence of collision free line segments from a start location to goal destination and when the vehicle’s kinematic model is taken to be Dubin’s vehicle. The low level feedback controller can then be design by treating the path following problem as a set stabilization problem; one such approach is called transverse feedback linearization (TFL). However, for a Dubin’s vehicle with only one input, the direction of traversal along the path is completely determined by the vehicle’s initial condition. In this paper we provide easily certifiable sufficient conditions and a systematic design procedure that guarantees the robot satisfies the initial condition requirements at transitions between line segments of the path. Our analysis relies on geometric properties of the path; as a result we construct a formal connection between the feasible motions generated by the planner and the path following controller’s convergence properties.
{"title":"Piecewise-Linear Path Following for a Unicycle using Transverse Feedback Linearization","authors":"Rollen S. D’Souza, Christopher Nielsen","doi":"10.23919/ACC45564.2020.9147473","DOIUrl":"https://doi.org/10.23919/ACC45564.2020.9147473","url":null,"abstract":"Path planning and following together constitute a critical part of the decision-making hierarchy in autonomous ground vehicles. One of the simplest instances of this architecture is when the path planner generates waypoints that define a sequence of collision free line segments from a start location to goal destination and when the vehicle’s kinematic model is taken to be Dubin’s vehicle. The low level feedback controller can then be design by treating the path following problem as a set stabilization problem; one such approach is called transverse feedback linearization (TFL). However, for a Dubin’s vehicle with only one input, the direction of traversal along the path is completely determined by the vehicle’s initial condition. In this paper we provide easily certifiable sufficient conditions and a systematic design procedure that guarantees the robot satisfies the initial condition requirements at transitions between line segments of the path. Our analysis relies on geometric properties of the path; as a result we construct a formal connection between the feasible motions generated by the planner and the path following controller’s convergence properties.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132867839","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 : 2020-07-01DOI: 10.23919/ACC45564.2020.9147908
Mathis Allen, H. Khalil
This paper presents an output feedback model predictive control for a class of nonlinear systems in a multirate scheme, where the control sampling period is larger than the estimation sampling period. With a small sampling period, the observer is designed to be faster than the dynamics of the closed-loop system under state feedback. Stabilization is achieved by a separation approach in which the control is designed first using state feedback and practical stabilization is achieved by output feedback.
{"title":"Nonlinear Model Predictive Control Using Output Feedback","authors":"Mathis Allen, H. Khalil","doi":"10.23919/ACC45564.2020.9147908","DOIUrl":"https://doi.org/10.23919/ACC45564.2020.9147908","url":null,"abstract":"This paper presents an output feedback model predictive control for a class of nonlinear systems in a multirate scheme, where the control sampling period is larger than the estimation sampling period. With a small sampling period, the observer is designed to be faster than the dynamics of the closed-loop system under state feedback. Stabilization is achieved by a separation approach in which the control is designed first using state feedback and practical stabilization is achieved by output feedback.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132043016","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 : 2020-07-01DOI: 10.23919/ACC45564.2020.9147765
Xu Zhang, Yang Lu, Minghui Zhu
This paper considers a class of nonlinear distributed control systems subject to false data injection attacks, Byzantine attacks and switching attacks. The problem of attack detection is formulated as the simultaneous recovery of system states, attack vectors and system mode of a switched nonlinear system. In the proposed attack detection algorithm, the inverse system of each mode aims to estimate system states and attack vectors when the corresponding mode is input-output decoupled. A set-valued mode index map gives all modes which generate a switch-singular pair. A machine learning example is used to validate the performance of the developed algorithm.
{"title":"Attack detection of nonlinear distributed control systems","authors":"Xu Zhang, Yang Lu, Minghui Zhu","doi":"10.23919/ACC45564.2020.9147765","DOIUrl":"https://doi.org/10.23919/ACC45564.2020.9147765","url":null,"abstract":"This paper considers a class of nonlinear distributed control systems subject to false data injection attacks, Byzantine attacks and switching attacks. The problem of attack detection is formulated as the simultaneous recovery of system states, attack vectors and system mode of a switched nonlinear system. In the proposed attack detection algorithm, the inverse system of each mode aims to estimate system states and attack vectors when the corresponding mode is input-output decoupled. A set-valued mode index map gives all modes which generate a switch-singular pair. A machine learning example is used to validate the performance of the developed algorithm.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130938936","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 : 2020-07-01DOI: 10.23919/ACC45564.2020.9147839
J. Siefert, Perry Y. Li
Most off-highway construction and agriculture equipment use hydraulics, which has unmatched power density, for power transmission and throttling as a means for control. Trends towards better efficiency and electrification motivated a novel Hybrid Hydraulic-Electric Architecture (HHEA) which could significantly reduce energy consumption even in high power machines that would be too costly to electrify directly. This is achieved by using a set of common pressure rails to transmit the majority of power hydraulically and modulating the power with small electric motor-drives to achieve precise control. This paper proposes a computationally efficient, Lagrange multiplier method for computing the optimal sequence of pressure rail selections to minimize energy use. This is needed to evaluate HHEA’s energy saving potential and for iterative architecture design and sizing. An interesting complication is that the cost function is not fully defined until the candidate control sequence is fully specified. This issue is dealt with by decomposing the original problem into a set of subproblems with inequality constraints that can be solved efficiently. A case study of an off-road construction machine demonstrates that the HHEA reduces energy consumption by 2/3 compared to the baseline load sensing architecture.
{"title":"Optimal Operation of a Hybrid Hydraulic Electric Architecture (HHEA) for Off-Road Vehicles Over Discrete Operating Decisions","authors":"J. Siefert, Perry Y. Li","doi":"10.23919/ACC45564.2020.9147839","DOIUrl":"https://doi.org/10.23919/ACC45564.2020.9147839","url":null,"abstract":"Most off-highway construction and agriculture equipment use hydraulics, which has unmatched power density, for power transmission and throttling as a means for control. Trends towards better efficiency and electrification motivated a novel Hybrid Hydraulic-Electric Architecture (HHEA) which could significantly reduce energy consumption even in high power machines that would be too costly to electrify directly. This is achieved by using a set of common pressure rails to transmit the majority of power hydraulically and modulating the power with small electric motor-drives to achieve precise control. This paper proposes a computationally efficient, Lagrange multiplier method for computing the optimal sequence of pressure rail selections to minimize energy use. This is needed to evaluate HHEA’s energy saving potential and for iterative architecture design and sizing. An interesting complication is that the cost function is not fully defined until the candidate control sequence is fully specified. This issue is dealt with by decomposing the original problem into a set of subproblems with inequality constraints that can be solved efficiently. A case study of an off-road construction machine demonstrates that the HHEA reduces energy consumption by 2/3 compared to the baseline load sensing architecture.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131724502","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 : 2020-07-01DOI: 10.23919/ACC45564.2020.9147845
A. Armstrong, A. Alleyne
For learning control algorithms to date, the convergence rate in the iteration domain depends on the level of plant knowledge. This work presents a Fast Cross-coupled Iterative Learning Control (F-CCILC) scheme to overcome the current limitations in learning control algorithms. F-CCILC achieves fast convergence for multi-input multi-output (MIMO) systems with high model uncertainty. The approach uses involves using a novel error term in the ILC learning law based on techniques from Sliding Mode Control (SMC). The input signal is guaranteed to remain bounded in the time and iteration domains, and the approach does not require end-user tuning of arbitrary gains. In this paper, the design for the F-CCILC system is presented, and the performance of this system is compared to the performance of existing ILC control schemes via simulations and experimental testing. Compared to the current control methods, the simulation results demonstrate increased robustness and learning speeds for multi-axis systems with significant model uncertainty.
{"title":"An Improved Iterative Learning Control for Uncertain Multi-Axis Systems","authors":"A. Armstrong, A. Alleyne","doi":"10.23919/ACC45564.2020.9147845","DOIUrl":"https://doi.org/10.23919/ACC45564.2020.9147845","url":null,"abstract":"For learning control algorithms to date, the convergence rate in the iteration domain depends on the level of plant knowledge. This work presents a Fast Cross-coupled Iterative Learning Control (F-CCILC) scheme to overcome the current limitations in learning control algorithms. F-CCILC achieves fast convergence for multi-input multi-output (MIMO) systems with high model uncertainty. The approach uses involves using a novel error term in the ILC learning law based on techniques from Sliding Mode Control (SMC). The input signal is guaranteed to remain bounded in the time and iteration domains, and the approach does not require end-user tuning of arbitrary gains. In this paper, the design for the F-CCILC system is presented, and the performance of this system is compared to the performance of existing ILC control schemes via simulations and experimental testing. Compared to the current control methods, the simulation results demonstrate increased robustness and learning speeds for multi-axis systems with significant model uncertainty.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129245804","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 : 2020-07-01DOI: 10.23919/acc45564.2020.9147649
Liangting Wu, L. Bridgeman
The Conic Sector Theorem can be employed for controller synthesis to ensure input-output stability. This work develops a method to synthesize conic, observer-based controllers by minimizing an upper-bound on the closed-loop ${mathcal{H}_2}$-norm. The proposed method can be seen as the dual of an existing optimal synthesis method, but with an alternative initialization to expand the set of plants for which it is feasible. This results in better performance in some examples and therefore provides a useful alternative tool for robust and optimal control.
{"title":"Dual, Iterative H2-Conic Controller Synthesis","authors":"Liangting Wu, L. Bridgeman","doi":"10.23919/acc45564.2020.9147649","DOIUrl":"https://doi.org/10.23919/acc45564.2020.9147649","url":null,"abstract":"The Conic Sector Theorem can be employed for controller synthesis to ensure input-output stability. This work develops a method to synthesize conic, observer-based controllers by minimizing an upper-bound on the closed-loop ${mathcal{H}_2}$-norm. The proposed method can be seen as the dual of an existing optimal synthesis method, but with an alternative initialization to expand the set of plants for which it is feasible. This results in better performance in some examples and therefore provides a useful alternative tool for robust and optimal control.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"277 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123367818","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 : 2020-07-01DOI: 10.23919/ACC45564.2020.9147379
Shantanu Prasad Burnwal, M. Vidyasagar
In this paper, we study the matrix completion problem: Suppose $X in {mathbb{R}^{{n_r} times {n_c}}}$ is unknown except for an upper bound r on its rank. By measuring a small number m ≪ nrnc of elements of X, is it possible to recover X exactly, or at least, to construct a reasonable approximation of X? At present, there are two approaches to choosing the sample set, namely probabilistic and deterministic. Probabilistic methods can guarantee exact recovery of the unknown matrix, but only with high probability. In this approach, samples are taken uniformly at random. Therefore we need to start sampling for every new matrix afresh. In the deterministic approach, sampling points can be kept fixed. At present, there are very few deterministic methods, and they mostly apply only to square matrices. In this paper, we present a deterministic method for selecting the sample set that can guarantee the exact recovery of the unknown matrix. This approach works for the recovery of rectangular as well as square matrices. We achieve this by choosing the elements to be sampled as the edge set of a Ramanujan bigraph. If samples are the edge set of a Ramanujan bigraph, then we can recover the unknown matrix from that sample set using nuclear norm minimization. A companion paper discusses the explicit construction of Ramanujan bigraphs. We provide a sufficient condition, that is if the samples taken are of the order of r3 then we can recover the unknown entries exactly if the unknown matrix satisfies some coherence condition. We believe this the first sufficient condition available using deterministic sampling technique and nuclear norm minimization.
本文研究了矩阵补全问题:假设$X In {mathbb{R}^{{n_r} 乘以{n_c}} $除了秩上有上界R外是未知的。通过测量少量的X元素的m < nrnc，是否有可能精确地得到X，或者至少构造出X的合理近似值?目前，有两种选择样本集的方法，即概率方法和确定性方法。概率方法可以保证未知矩阵的精确恢复，但只有在高概率的情况下。在这种方法中，样本是均匀随机抽取的。因此，我们需要对每个新矩阵重新开始采样。在确定性方法中，采样点可以保持固定。目前，确定性方法很少，而且大多只适用于方阵。本文提出了一种确定的样本集选择方法，保证了未知矩阵的精确恢复。这种方法既适用于矩形矩阵的恢复，也适用于方阵的恢复。我们通过选择要采样的元素作为拉马努金图的边集来实现这一点。如果样本是拉马努金图的边集，那么我们可以使用核范数最小化从该样本集恢复未知矩阵。另一篇论文讨论了拉马努金图的显式构造。我们提供了一个充分条件，如果所取的样本是r3阶的，那么如果未知矩阵满足相干性条件，我们可以准确地恢复未知项。我们认为这是采用确定性抽样技术和核范数最小化方法得到的第一个充分条件。
{"title":"Exact Completion of Rectangular Matrices Using Ramanujan Bigraphs","authors":"Shantanu Prasad Burnwal, M. Vidyasagar","doi":"10.23919/ACC45564.2020.9147379","DOIUrl":"https://doi.org/10.23919/ACC45564.2020.9147379","url":null,"abstract":"In this paper, we study the matrix completion problem: Suppose $X in {mathbb{R}^{{n_r} times {n_c}}}$ is unknown except for an upper bound r on its rank. By measuring a small number m ≪ nrnc of elements of X, is it possible to recover X exactly, or at least, to construct a reasonable approximation of X? At present, there are two approaches to choosing the sample set, namely probabilistic and deterministic. Probabilistic methods can guarantee exact recovery of the unknown matrix, but only with high probability. In this approach, samples are taken uniformly at random. Therefore we need to start sampling for every new matrix afresh. In the deterministic approach, sampling points can be kept fixed. At present, there are very few deterministic methods, and they mostly apply only to square matrices. In this paper, we present a deterministic method for selecting the sample set that can guarantee the exact recovery of the unknown matrix. This approach works for the recovery of rectangular as well as square matrices. We achieve this by choosing the elements to be sampled as the edge set of a Ramanujan bigraph. If samples are the edge set of a Ramanujan bigraph, then we can recover the unknown matrix from that sample set using nuclear norm minimization. A companion paper discusses the explicit construction of Ramanujan bigraphs. We provide a sufficient condition, that is if the samples taken are of the order of r3 then we can recover the unknown entries exactly if the unknown matrix satisfies some coherence condition. We believe this the first sufficient condition available using deterministic sampling technique and nuclear norm minimization.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126454023","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 : 2020-07-01DOI: 10.23919/acc45564.2020.9147260
Z. Gima, Dylan Kato, Reinhardt Klein, S. Moura
This paper focuses on the problem of online parameter estimation in an electrochemical Li-ion battery model. Online parameter estimation is necessary to account for model mismatch, environmental disturbances, and cycle-induced aging in Li-ion battery models. Sensitivity analysis can improve parameter estimation by identifying which data the parameters are most sensitive to. However, computing parameter sensitivity in full-order electrochemical models is typically intractable for online applications. Using a reduced-order model can lower the computational burden and, as we demonstrate, approximates well the sensitivity of the higher-order model. To provide further insight into the parameter estimation challenge, we analyze the effect that identifying parameters according to voltage RMSE data has on internal state errors. We perform a simulation study which demonstrates that parameter estimation approaches based on this paradigm are not sufficient for safe battery operation or other control objectives that require accurate estimates of these states.
{"title":"Analysis of Online Parameter Estimation for Electrochemical Li-ion Battery Models via Reduced Sensitivity Equations","authors":"Z. Gima, Dylan Kato, Reinhardt Klein, S. Moura","doi":"10.23919/acc45564.2020.9147260","DOIUrl":"https://doi.org/10.23919/acc45564.2020.9147260","url":null,"abstract":"This paper focuses on the problem of online parameter estimation in an electrochemical Li-ion battery model. Online parameter estimation is necessary to account for model mismatch, environmental disturbances, and cycle-induced aging in Li-ion battery models. Sensitivity analysis can improve parameter estimation by identifying which data the parameters are most sensitive to. However, computing parameter sensitivity in full-order electrochemical models is typically intractable for online applications. Using a reduced-order model can lower the computational burden and, as we demonstrate, approximates well the sensitivity of the higher-order model. To provide further insight into the parameter estimation challenge, we analyze the effect that identifying parameters according to voltage RMSE data has on internal state errors. We perform a simulation study which demonstrates that parameter estimation approaches based on this paradigm are not sufficient for safe battery operation or other control objectives that require accurate estimates of these states.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121609641","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 : 2020-07-01DOI: 10.23919/ACC45564.2020.9147928
Christian A. Cousin
Hybrid exoskeletons combine two increasingly common rehabilitative therapies, functional electrical stimulation (FES) and robotic therapy, for use on individuals with neuromuscular disorders. As hybrid exoskeletons increase in popularity and complexity, it remains an ever-important issue to not only assist people in performing rehabilitation, but also to guarantee their safety while coupled to the exoskeleton. In this paper, a novel adaptive controller for hybrid exoskeletons is developed to regulate an admittance error system using the exoskeleton’s motors while simultaneously regulating a position error system using the operator’s muscles, stimulated through FES. The stability of the controller is rigorously analyzed using a combined Lyapunov-passivity approach and while the hybrid exoskeleton is proven to be energetically passive, the admittance error system is proven to demonstrate global exponential convergence to a uniform ultimate bound. Simulations were performed on a two degree-of-freedom lower-limb hybrid exoskeleton to demonstrate the efficacy of the controller. Results show the controller achieves an average admittance tracking error of 0.00±0.08 rad and 0.00±0.08 rad/s for joint one (the knee joint), and 0.01±0.11 rad and 0.01±0.12 rad/s for joint two (the ankle joint), while simultaneously applying FES to the operator’s muscles for rehabilitation.
{"title":"Adaptive Admittance Control of Hybrid Exoskeletons","authors":"Christian A. Cousin","doi":"10.23919/ACC45564.2020.9147928","DOIUrl":"https://doi.org/10.23919/ACC45564.2020.9147928","url":null,"abstract":"Hybrid exoskeletons combine two increasingly common rehabilitative therapies, functional electrical stimulation (FES) and robotic therapy, for use on individuals with neuromuscular disorders. As hybrid exoskeletons increase in popularity and complexity, it remains an ever-important issue to not only assist people in performing rehabilitation, but also to guarantee their safety while coupled to the exoskeleton. In this paper, a novel adaptive controller for hybrid exoskeletons is developed to regulate an admittance error system using the exoskeleton’s motors while simultaneously regulating a position error system using the operator’s muscles, stimulated through FES. The stability of the controller is rigorously analyzed using a combined Lyapunov-passivity approach and while the hybrid exoskeleton is proven to be energetically passive, the admittance error system is proven to demonstrate global exponential convergence to a uniform ultimate bound. Simulations were performed on a two degree-of-freedom lower-limb hybrid exoskeleton to demonstrate the efficacy of the controller. Results show the controller achieves an average admittance tracking error of 0.00±0.08 rad and 0.00±0.08 rad/s for joint one (the knee joint), and 0.01±0.11 rad and 0.01±0.12 rad/s for joint two (the ankle joint), while simultaneously applying FES to the operator’s muscles for rehabilitation.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121115487","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 : 2020-07-01DOI: 10.23919/ACC45564.2020.9147993
Minh Vu, Shen Zeng
This paper presents computational solutions for nonlinear optimal control problems with general state-space constraints that may not be representable in terms of analytical expressions. The presented approaches hinge on the iterative nature of an underlying computational nonlinear optimal control methodology by which the non-analytical constraint description can be incorporated as quadratic constraints within each iteration. The functionality and efficiency of the proposed methods are discussed from a computational point of view and illustrated on a standard parallel parking problem.
{"title":"Iterative Optimal Control Syntheses for Nonlinear Systems in Constrained Environments","authors":"Minh Vu, Shen Zeng","doi":"10.23919/ACC45564.2020.9147993","DOIUrl":"https://doi.org/10.23919/ACC45564.2020.9147993","url":null,"abstract":"This paper presents computational solutions for nonlinear optimal control problems with general state-space constraints that may not be representable in terms of analytical expressions. The presented approaches hinge on the iterative nature of an underlying computational nonlinear optimal control methodology by which the non-analytical constraint description can be incorporated as quadratic constraints within each iteration. The functionality and efficiency of the proposed methods are discussed from a computational point of view and illustrated on a standard parallel parking problem.","PeriodicalId":288450,"journal":{"name":"2020 American Control Conference (ACC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121213603","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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