Pub Date : 2018-06-14DOI: 10.23919/ECC.2018.8550396
Jonathan Hermann, Sebastian Bernhard, U. Konigorski, J. Adamy
In this paper the synchronization of homogeneous linear multi-agent systems is considered. In this process, all agents are required to converge to a common trajectory called synchronization trajectory. Without synchronization every sin- gle agent would have followed its own autonomous trajectory determined by its initial state. Hence, we interpret the initial states of the agents as their respective preferences. We define a cost function that penalizes the compromise each agent has to make when the synchronization trajectory differs from the agent's preferred trajectory. Using classical synchronization controllers, the synchronization trajectory essentially depends on the communication topology and the initial states of the agents. Therefore, we pose optimization problems concerned with finding the communication topology yielding minimal cost, i.e. the synchronization trajectory that constitutes an optimal compromise forall agents. In this respect, we minimize the cost for a given initial state, for the worst-case as well as for the average over all admissible initial states of the agents. The introduced minimization problems are reformulated as semidefinite programs so that they can be efficiently solved. A numerical example illustrates the results.
{"title":"Designing Communication Topologies for Optimal Synchronization Trajectories of HomogeneousLinear Multi-Agent Systems","authors":"Jonathan Hermann, Sebastian Bernhard, U. Konigorski, J. Adamy","doi":"10.23919/ECC.2018.8550396","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550396","url":null,"abstract":"In this paper the synchronization of homogeneous linear multi-agent systems is considered. In this process, all agents are required to converge to a common trajectory called synchronization trajectory. Without synchronization every sin- gle agent would have followed its own autonomous trajectory determined by its initial state. Hence, we interpret the initial states of the agents as their respective preferences. We define a cost function that penalizes the compromise each agent has to make when the synchronization trajectory differs from the agent's preferred trajectory. Using classical synchronization controllers, the synchronization trajectory essentially depends on the communication topology and the initial states of the agents. Therefore, we pose optimization problems concerned with finding the communication topology yielding minimal cost, i.e. the synchronization trajectory that constitutes an optimal compromise forall agents. In this respect, we minimize the cost for a given initial state, for the worst-case as well as for the average over all admissible initial states of the agents. The introduced minimization problems are reformulated as semidefinite programs so that they can be efficiently solved. A numerical example illustrates the results.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130246610","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 : 2018-06-12DOI: 10.23919/ECC.2018.8550309
G. Rousseau, C. Stoica, S. Tebbani, M. Babel, Nicolas Martin
This paper proposes a receding waypoint horizon strategy generating a piecewise polynomial trajectory with minimum jerk and predictive tracking of camera references for quadrotors, in the context of autonomous aerial single- sequence shots in a static environment. In order to deal with the limited on-board computation resources, the camera control is performed with an undersampled model predictive controller generating a set-point trajectory and a feedforward control signal, both used by a larger frequency controller. The performance of the overall strategy is illustrated with a real flight, on a Parrot Bebop 2 drone.
{"title":"Quadcopter-performed cinematographic flight plans using minimum jerk trajectories and predictive camera control","authors":"G. Rousseau, C. Stoica, S. Tebbani, M. Babel, Nicolas Martin","doi":"10.23919/ECC.2018.8550309","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550309","url":null,"abstract":"This paper proposes a receding waypoint horizon strategy generating a piecewise polynomial trajectory with minimum jerk and predictive tracking of camera references for quadrotors, in the context of autonomous aerial single- sequence shots in a static environment. In order to deal with the limited on-board computation resources, the camera control is performed with an undersampled model predictive controller generating a set-point trajectory and a feedforward control signal, both used by a larger frequency controller. The performance of the overall strategy is illustrated with a real flight, on a Parrot Bebop 2 drone.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126811711","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 : 2018-06-12DOI: 10.23919/ECC.2018.8550596
Michael Ringkowski, Stefan Gering, M. Manderla, E. Arnold, O. Sawodny
In model predictive direct switching control (MPDSC) approaches, the finite set of inverter switch positions for the control of electrical drives is taken as control variables within the MPC underlying optimization problem. The cost function can be designed to track a torque or current reference while also considering additional control goals like minimizing switching and conduction losses, as well as physical constraints. The challenge is to solve the resulting integer quadratically constrained quadratic program (IQCQP) with high sampling frequencies online in order to obtain the optimal switch positions at each fixed time step. This paper presents two new MPDSC algorithms, namely relaxed barrier functions iteration scheme (RBF) and alternating direction method of multipliers heuristic (ADMM) and compares them with two state-of-the-art algorithms, namely full enumeration (FE) and multistep with sphere decoding (MSD) for the example of a multi-phase permanent-magnet synchronous motor (PMSM) in simulations.
{"title":"Model Predictive Direct Switching Control for Multi-Phase Permanent-Magnet Synchronous Motors","authors":"Michael Ringkowski, Stefan Gering, M. Manderla, E. Arnold, O. Sawodny","doi":"10.23919/ECC.2018.8550596","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550596","url":null,"abstract":"In model predictive direct switching control (MPDSC) approaches, the finite set of inverter switch positions for the control of electrical drives is taken as control variables within the MPC underlying optimization problem. The cost function can be designed to track a torque or current reference while also considering additional control goals like minimizing switching and conduction losses, as well as physical constraints. The challenge is to solve the resulting integer quadratically constrained quadratic program (IQCQP) with high sampling frequencies online in order to obtain the optimal switch positions at each fixed time step. This paper presents two new MPDSC algorithms, namely relaxed barrier functions iteration scheme (RBF) and alternating direction method of multipliers heuristic (ADMM) and compares them with two state-of-the-art algorithms, namely full enumeration (FE) and multistep with sphere decoding (MSD) for the example of a multi-phase permanent-magnet synchronous motor (PMSM) in simulations.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126903935","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 : 2018-06-12DOI: 10.23919/ECC.2018.8550423
Uros Kalabic, S. D. Cairano
This paper presents a novel reference-governor-based approach to enforcing constraints in open-loop systems, where the constraint enforcement scheme modifies a control signal from a feedback controller. The reference governor is not typically applicable to these systems, since reference governors modify reference signals, which are inputs to a feedback controller.The design is based on duplicating the feedback controller of the closed-loop system and implementing a reference governor to modify the reference input to the duplicate controller. Effectively, this bypasses the nominal controller, whose internal dynamics may not be asymptotically stable. We present a method to ensure stability of the closed-loop system by ceding some control authority to the nominal controller.A numerical example is considered in which the nominal controller is a human operator of a steer-by-wire system. The operator is modeled as a PID controller with unknown parameters. Results show that the inner-loop governor design is able to satisfactorily enforce constraints in such an application.
{"title":"Inner-Loop Reference Governor Design with an Application to Human-in-the-Loop Control","authors":"Uros Kalabic, S. D. Cairano","doi":"10.23919/ECC.2018.8550423","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550423","url":null,"abstract":"This paper presents a novel reference-governor-based approach to enforcing constraints in open-loop systems, where the constraint enforcement scheme modifies a control signal from a feedback controller. The reference governor is not typically applicable to these systems, since reference governors modify reference signals, which are inputs to a feedback controller.The design is based on duplicating the feedback controller of the closed-loop system and implementing a reference governor to modify the reference input to the duplicate controller. Effectively, this bypasses the nominal controller, whose internal dynamics may not be asymptotically stable. We present a method to ensure stability of the closed-loop system by ceding some control authority to the nominal controller.A numerical example is considered in which the nominal controller is a human operator of a steer-by-wire system. The operator is modeled as a PID controller with unknown parameters. Results show that the inner-loop governor design is able to satisfactorily enforce constraints in such an application.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117117045","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 : 2018-06-01DOI: 10.23919/ECC.2018.8550497
A. Casavola, E. Garone, Francesco Saverio Tedesco
this paper the link between Graph colorability theory and the design of a distributed Command Governor (CG) strategy is investigated. The first link between distributed supervision of systems with constraints and colorability properties was highlighted in a previous work where the idea of Turnbased CG was introduced for dynamically decoupled systems subject to coupling constraints. In this paper we will extend such a scheme to the case of dynamically coupled systems and we will show that the problem of determining the the minimal number of turns along with maximization of the agents appearance in turns is equivalent to a particular graph coloring problem. Such a problem is presented in a formal way and its complexity properties deeply discussed. A final example is presented to illustrate the effectiveness of the proposed strategy.
{"title":"On the Link Between Multi-Coloring Problems for Graphs and Distributed Supervision of Interconnected Systems","authors":"A. Casavola, E. Garone, Francesco Saverio Tedesco","doi":"10.23919/ECC.2018.8550497","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550497","url":null,"abstract":"this paper the link between Graph colorability theory and the design of a distributed Command Governor (CG) strategy is investigated. The first link between distributed supervision of systems with constraints and colorability properties was highlighted in a previous work where the idea of Turnbased CG was introduced for dynamically decoupled systems subject to coupling constraints. In this paper we will extend such a scheme to the case of dynamically coupled systems and we will show that the problem of determining the the minimal number of turns along with maximization of the agents appearance in turns is equivalent to a particular graph coloring problem. Such a problem is presented in a formal way and its complexity properties deeply discussed. A final example is presented to illustrate the effectiveness of the proposed strategy.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123062433","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 : 2018-06-01DOI: 10.23919/ECC.2018.8550201
Anas W. Alhashimi, S. D. Favero, Damiano Varagnolo, T. Gustafsson, G. Pillonetto
This paper investigates the problem of calibrating sensors affected by (i) heteroskedastic measurement noise and (ii) a polynomial bias, describing a systematic distortion of the measured quantity. First, a set of increasingly complex statistical models for the measurement process was proposed. Then, for each model the authors design a Bayesian parameters estimation method handling heteroskedasticity and capable to exploit prior information about the model parameters. The Bayesian problem is solved using MCMC methods and reconstructing the unknown parameters posterior in sampled form. The authors then test the proposed techniques on a practically relevant case study, the calibration of Light Detection and Ranging (Lidar) sensor, and evaluate the different proposed procedures using both artificial and field data.
{"title":"Bayesian strategies for calibrating heteroskedastic static sensors with unknown model structures","authors":"Anas W. Alhashimi, S. D. Favero, Damiano Varagnolo, T. Gustafsson, G. Pillonetto","doi":"10.23919/ECC.2018.8550201","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550201","url":null,"abstract":"This paper investigates the problem of calibrating sensors affected by (i) heteroskedastic measurement noise and (ii) a polynomial bias, describing a systematic distortion of the measured quantity. First, a set of increasingly complex statistical models for the measurement process was proposed. Then, for each model the authors design a Bayesian parameters estimation method handling heteroskedasticity and capable to exploit prior information about the model parameters. The Bayesian problem is solved using MCMC methods and reconstructing the unknown parameters posterior in sampled form. The authors then test the proposed techniques on a practically relevant case study, the calibration of Light Detection and Ranging (Lidar) sensor, and evaluate the different proposed procedures using both artificial and field data.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116653777","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 : 2018-06-01DOI: 10.23919/ECC.2018.8550244
Veli-Pekka Pyrhonen, H. Koivisto, M. Vilkko
We present in this paper gain-scheduling composite nonlinear feedback (CNF) control for a set of second-order linear parameter-varying (LPV) systems that capture commonly used plant models in automatic control. The selected three parameter-varying plant models are double integrator with a gain, a series connection of an integrator and a first order system, and a second-order system without integration. We assume that the parameters of the plant models depend on an exogenous scheduling signal, which is unknown a priori, but it is measurable online and available for feedback control. The resulting model-based parameter-varying CNF controller assigns certain predefined properties for the closed-loop control system, which can be explained using linear time invariant (LTI) control theory. We demonstrate the proposed control structure with a simulation-based design example, in which a plant model is updated through a slowly varying scheduling signal, and, at the same time, the closed-loop system is commanded towards desired reference values. Our simulation results indicate that the closed-loop control system yields satisfactory tracking performance under parameter-varying conditions.
{"title":"Gain-Scheduling Composite Nonlinear Feedback Control for a Set of 2nd Order Linear Parameter-Varying Systems","authors":"Veli-Pekka Pyrhonen, H. Koivisto, M. Vilkko","doi":"10.23919/ECC.2018.8550244","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550244","url":null,"abstract":"We present in this paper gain-scheduling composite nonlinear feedback (CNF) control for a set of second-order linear parameter-varying (LPV) systems that capture commonly used plant models in automatic control. The selected three parameter-varying plant models are double integrator with a gain, a series connection of an integrator and a first order system, and a second-order system without integration. We assume that the parameters of the plant models depend on an exogenous scheduling signal, which is unknown a priori, but it is measurable online and available for feedback control. The resulting model-based parameter-varying CNF controller assigns certain predefined properties for the closed-loop control system, which can be explained using linear time invariant (LTI) control theory. We demonstrate the proposed control structure with a simulation-based design example, in which a plant model is updated through a slowly varying scheduling signal, and, at the same time, the closed-loop system is commanded towards desired reference values. Our simulation results indicate that the closed-loop control system yields satisfactory tracking performance under parameter-varying conditions.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116946645","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 : 2018-06-01DOI: 10.23919/ECC.2018.8550111
Quoc Van Tran, M. Trinh, H. Ahn
In this paper, the novel surrounding formation protocol around a beacon is proposed using bearing-only formation. In the surrounding formation problem, all agents surround the beacon such that all the relative angles between some pairs of agents and the beacon satisfy predefined relative angles. Moreover, each agent senses and controls only its direction to the beacon in its local coordinate frame without knowledge of common global coordinate system. We propose an orientation estimator by adding an auxiliary variable which is assumed to be communicated by agents. A bearing-only based control law is proposed using the auxiliary variables. We show that the desired surrounding formation is almost globally asymptotically stable based on input-to-state stability theory. Further, under the proposed control law, the surrounding formation is collision-free under an assumption of initial positions. Numerical simulations are provided to support the proposed control method.
{"title":"Surrounding formation of star frameworks using bearing-only measurements","authors":"Quoc Van Tran, M. Trinh, H. Ahn","doi":"10.23919/ECC.2018.8550111","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550111","url":null,"abstract":"In this paper, the novel surrounding formation protocol around a beacon is proposed using bearing-only formation. In the surrounding formation problem, all agents surround the beacon such that all the relative angles between some pairs of agents and the beacon satisfy predefined relative angles. Moreover, each agent senses and controls only its direction to the beacon in its local coordinate frame without knowledge of common global coordinate system. We propose an orientation estimator by adding an auxiliary variable which is assumed to be communicated by agents. A bearing-only based control law is proposed using the auxiliary variables. We show that the desired surrounding formation is almost globally asymptotically stable based on input-to-state stability theory. Further, under the proposed control law, the surrounding formation is collision-free under an assumption of initial positions. Numerical simulations are provided to support the proposed control method.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121092886","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 : 2018-06-01DOI: 10.23919/ECC.2018.8550413
R. Mitze, David Dillkötter, S. Gros, A. Schild, M. Mönnigmann
Advanced control applications require accurate system models. Obviously, these models must be evaluated sufficiently fast in order for a model-based controller to be real-time feasible. This holds for methods that are based on online optimizations, such as model predictive control (MPC), in particular. It is common to describe nonlinear static parts of system models with interpolated look-up tables, because they are computationally efficient and they can be designed to provide the required accuracy. Since the underlying data are often determined with measurements or simulations, the location of data points can be chosen by the user to some extent. We use data on regular grids and B-splines with uniform knotvectors located at the data grid points, because this results in smooth interpolated look-up tables that can be evaluated very fast. The algorithm for the online evaluation and interpolation can be extended to efficiently provide first and second order derivatives, which are, for example, needed in MPC. We illustrate the use of the implemented methods with the look-up table of the aerodynamic power coefficient of a wind turbine generator and compare computation times for an implementation on a CPU and on an FPGA.
{"title":"Fast and smooth surface B-spline interpolation for regularly spaced data used in system modeling to make MPC real-time feasible*","authors":"R. Mitze, David Dillkötter, S. Gros, A. Schild, M. Mönnigmann","doi":"10.23919/ECC.2018.8550413","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550413","url":null,"abstract":"Advanced control applications require accurate system models. Obviously, these models must be evaluated sufficiently fast in order for a model-based controller to be real-time feasible. This holds for methods that are based on online optimizations, such as model predictive control (MPC), in particular. It is common to describe nonlinear static parts of system models with interpolated look-up tables, because they are computationally efficient and they can be designed to provide the required accuracy. Since the underlying data are often determined with measurements or simulations, the location of data points can be chosen by the user to some extent. We use data on regular grids and B-splines with uniform knotvectors located at the data grid points, because this results in smooth interpolated look-up tables that can be evaluated very fast. The algorithm for the online evaluation and interpolation can be extended to efficiently provide first and second order derivatives, which are, for example, needed in MPC. We illustrate the use of the implemented methods with the look-up table of the aerodynamic power coefficient of a wind turbine generator and compare computation times for an implementation on a CPU and on an FPGA.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121377263","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 : 2018-06-01DOI: 10.23919/ECC.2018.8550250
J. Beuchert, Jnrg Raischl, T. Seel
Swinging up a pendulum on a cart is a well-known demonstration example for trajectory tracking in a nonlinear system. The standard realtime feedback control approach fails if the plant output is not available in real time, e.g. due to large or variable measurement delays. However, the task can be solved in multiple trials by applying feedforward inputs that are improved from trial to trial by Iterative Learning Control (ILC). Our examination demonstrates that an ILC can be used for trajectory tracking close to the singularities and the unstable equilibrium of a non-linear system. Specifically, we present an ILC algorithm for pendulum swing-up by angle trajectory tracking. The controller design is based on a modified plant inversion approach that restricts the learning process to trajectory segments with small tracking errors and sufficient input sensitivity. We show that these restrictions lead to improved learning progress in contrast to conventional learning from the complete trajectory. Controller performance is evaluated in an experimental testbed. The ILC starts from a zero-input trajectory and learns to swing up the pendulum within six iterations. Robustness is analyzed experimentally, and the performance is compared to literature results. The convergence is at least two orders of magnitude faster than the one achieved by other methods that avoid feedback and do not rely on a suitable initial input trajectory.
{"title":"Design of an iterative learning control with a selective learning strategy for swinging up a pendulum","authors":"J. Beuchert, Jnrg Raischl, T. Seel","doi":"10.23919/ECC.2018.8550250","DOIUrl":"https://doi.org/10.23919/ECC.2018.8550250","url":null,"abstract":"Swinging up a pendulum on a cart is a well-known demonstration example for trajectory tracking in a nonlinear system. The standard realtime feedback control approach fails if the plant output is not available in real time, e.g. due to large or variable measurement delays. However, the task can be solved in multiple trials by applying feedforward inputs that are improved from trial to trial by Iterative Learning Control (ILC). Our examination demonstrates that an ILC can be used for trajectory tracking close to the singularities and the unstable equilibrium of a non-linear system. Specifically, we present an ILC algorithm for pendulum swing-up by angle trajectory tracking. The controller design is based on a modified plant inversion approach that restricts the learning process to trajectory segments with small tracking errors and sufficient input sensitivity. We show that these restrictions lead to improved learning progress in contrast to conventional learning from the complete trajectory. Controller performance is evaluated in an experimental testbed. The ILC starts from a zero-input trajectory and learns to swing up the pendulum within six iterations. Robustness is analyzed experimentally, and the performance is compared to literature results. The convergence is at least two orders of magnitude faster than the one achieved by other methods that avoid feedback and do not rely on a suitable initial input trajectory.","PeriodicalId":222660,"journal":{"name":"2018 European Control Conference (ECC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127458851","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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