The Experts below are selected from a list of 275487 Experts worldwide ranked by ideXlab platform

E. A. Misawa - One of the best experts on this subject based on the ideXlab platform.

Li Zhou - One of the best experts on this subject based on the ideXlab platform.

Tarunraj Singh - One of the best experts on this subject based on the ideXlab platform.

  • Time-Optimal Output Transition for Minimum-Phase Systems
    Journal of Dynamic Systems Measurement and Control, 2013
    Co-Authors: Jennifer Haggerty, Tarunraj Singh
    Abstract:

    The time-optimal output transition Control problem for stable or marginally stable systems with minimum-phase zeros is discussed in this paper. A double integrator system with a real left-half plane zero is used to illustrate the development of the time-optimal output transition Controller. It is shown that an exponentially decaying postactuation Control Profile is necessary to maintain the output at the desired final location. It is shown that the resulting solution to the output transition time-optimal Control Profile can be generated by a time-delay filter whose zeros and poles cancels the poles and zeros of the system to be Controlled. The design of the time-optimal output transition problem is generalized and illustrated on the benchmark floating oscillator problem.

  • CHARACTERISTICS OF DEFLECTION-LIMITED TIME-OPTIMAL Control OF THE BENCHMARK PROBLEM
    2008
    Co-Authors: Matthew Vossler, Tarunraj Singh
    Abstract:

    The focus of this paper is on the design of time optimal Control Profiles for flexible structures subject to deflectio n constraints. The benchmark floating oscillator is used to illus trate the variation in the structure of the Control Profile as a func tion of permissible deflection. The transition from a 5 switc h bang-bang to a 7 switch bang-bang to finally, a 7 switch Profile which includes non-saturating intervals, is demonstrated . The loss of anti-symmetry of the Control Profile and the transiti on of the structures of the deflection constrained time-optimal c ontrol Profiles for damped systems is also presented.

  • TIME OPTIMAL Control OF FLEXIBLE SYSTEMS SUBJECT TO FRICTION
    Optimal Control Applications and Methods, 2008
    Co-Authors: Jae Jun Kim, Rajaey Kased, Tarunraj Singh
    Abstract:

    This paper presents a technique for the determination of time-optimal Control Profiles for rest-to-rest maneuvers of a mass–spring system, subject to Coulomb friction. A parameterization of the Control input that accounts for the friction force, resulting in a linear analysis of the system is proposed. The optimality condition is examined for the Control Profile resulting from the parameter optimization problem. The development is illustrated on a single input system where the Control input and the friction force act on the same body. The variation of the optimal Control structure as a function of final displacement is also exemplified on the friction benchmark problem. Copyright © 2007 John Wiley & Sons, Ltd.

  • Fuel/Time Optimal Control of Flexible Space Structures: A Frequency Domain Approach
    Journal of Vibration and Control, 1999
    Co-Authors: Rolf Hartmann, Tarunraj Singh
    Abstract:

    This paper considers the design of open-loop fuel/time optimal Controllers for flexible space struc tures using a frequency domain approach. The Control system consists of a time-delay filter whose output signal is the optimal Control Profile when it is subject to a step input. A constrained parameter optimization problem is formulated to minimize a weighted combination of fuel consumed and total maneuver time for a rest-to-rest maneuver. The parameters to be optimized for are the delays of a time-delay filter. The number of switches of the fuel/time optimal Control Profile is shown to be a function not only of number of flexible modes but also of the weighting parameter, which is illustrated via numerical examples.

  • Robust Time-Optimal Control of Flexible Structures With Parametric Uncertainty
    Journal of Dynamic Systems Measurement and Control, 1997
    Co-Authors: Shin-whar Liu, Tarunraj Singh
    Abstract:

    The design of robust time-optimal Controllers using the sensitivity concept is presented in this paper. A parameter optimization problem is solved using the Switch Time Optimization algorithm to determine a bang-bang Control Profile that minimizes the maneuver time subject to the constraint that the sensitivity of the final states with respect to system parameters are zero. The proposed approach is illustrated on the benchmark floating oscillator problem and a slewing flexible beam whose equations of motion are nonlinear. Simulation results illustrate the reduction of residual vibrations of the system subject to the robust Control Profile, compared to the time-optimal Control Profile.

Christelle Pittet - One of the best experts on this subject based on the ideXlab platform.

  • A Three-step Decomposition Method for Solving the Minimum-Fuel Geostationary Station Keeping of Satellites Equipped with Electric Propulsion
    Acta Astronautica, 2019
    Co-Authors: Clément Gazzino, Denis Arzelier, Luca Cerri, Damiana Losa, Christophe Louembet, Christelle Pittet
    Abstract:

    In this paper, a Control scheme is elaborated in order to perform the station keeping of a geostationary satellite equipped with electric propulsion while minimizing the fuel consumption. The use of electric thrusters imposes to take into account some additional non linear and operational constraints that make the overall station keeping optimal Control problem difficult to solve directly. That is why the station keeping problem is decomposed in three successive Control problems. The first one consists in solving a classical optimal Control problem with an indirect method initialized by a direct method without enforcing the thrusters operational constraints. Starting from this non feasible solution for the genuine problem, the thrusters operating constraints are incorporated in the second problem, whose solution produces a feasible but non optimal Control Profile via two different ways. Finally, the third optimizes the commutation times thanks to a method borrowed to the switched systems theory. Simulation results on a realistic example validate the benefit of this particular Control scheme in the reduction of the fuel consumption for the geostationary station keeping problem.

  • Solving the Minimum-Fuel Low-Thrust Geostationary Station Keeping Problem via the Switching Systems Theory
    2017
    Co-Authors: Clément Gazzino, Denis Arzelier, Luca Cerri, Damiana Losa, Christophe Louembet, Christelle Pittet
    Abstract:

    The optimal station keeping Control problem of a geostationary satellite equipped with electric thrusters is recast as a switched system commutation times optimisation problem, considering that a system with a bang-bang Control Profile is composed by several subsystems, one for which all the Controls are off and the other ones one for which one of the Controls is on. In order to optimise the commutation times, the optimal firing sequence has to be known in advance. This sequence is provided by a two-step decomposition technique and the proposed method can be interpreted as a third step. Simulation results on a realistic example validate the benefit of this third optimisation step on the Control sequence fuel consumption.

  • A Minimum-Fuel Fixed-Time Low-Thrust Rendezvous Solved with the Switching Systems Theory
    2017
    Co-Authors: Clément Gazzino, Denis Arzelier, Luca Cerri, Damiana Losa, Christophe Louembet, Christelle Pittet
    Abstract:

    In this paper, a fuel optimal rendezvous problem is tackled in the Hill-Clohessy-Wiltshire framework with several operational constraints as bounds on the thrust, non linear non convex and disjunctive operational constraints (on-off Profile of the thrusters, minimum elapsed time between two consecutive firings...). An indirect method and a decomposition technique have already been combined in order to solve this kind of optimal Control problem with such constraints. Due to a great number of parameters to tune, satisfactory results are hard to obtain and are sensitive to the initial condition. Assuming that no singular arc exists, it can be shown that the optimal Control exhibits a bang-bang structure whose optimal switching times are to be found. Noticing that a system with a bang-bang Control Profile can be considered as two subsystems switching from one with Control on to with Control off, and vice-versa, a technique coming from the switching systems theory is used in order to optimise the switching times.

Jie Zhang - One of the best experts on this subject based on the ideXlab platform.

  • BATCH-TO-BATCH OPTIMAL Control OF BATCH PROCESSES BASED ON RECURSIVELY UPDATED NONLINEAR PARTIAL LEAST SQUARES MODELS
    Chemical Engineering Communications, 2006
    Co-Authors: Jie Zhang, Guizeng Wang
    Abstract:

    A batch-to-batch optimal Control approach for batch processes based on batch-wise updated nonlinear partial least squares (NLPLS) models is presented in this article. To overcome the difficulty in developing mechanistic models for batch/semi-batch processes, a NLPLS model is developed to predict the final product quality from the batch Control Profile. Mismatch between the NLPLS model and the actual plant often exists due to low-quality training data or variations in process operating conditions. Thus, the optimal Control Profile calculated from a fixed NLPLS model may not be optimal when applied to the actual plant. To address this problem, a recursive nonlinear PLS (RNPLS) algorithm is proposed to update the NLPLS model using the information newly obtained after each batch run. The proposed algorithm is computationally efficient in that it updates the model using the current model parameters and data from the current batch. Then the new optimal Control Profile is recalculated from the updated model and ...

  • Optimal Control of Fed-Batch Processes Based on Multiple Neural Networks
    Applied Intelligence, 2005
    Co-Authors: Zhihua Xiong, Jie Zhang
    Abstract:

    The performance of empirical model based fed-batch process optimal Control is strongly affected by the model prediction reliability at the end-point of a batch. An optimal Control Profile calculated from an empirical model may not give the best performance when applied to the actual process due to model-plant mismatches. To tackle this issue, a new method for improving the reliability of fed-batch process optimal Control by incorporating model prediction confidence bounds is proposed. Multiple neural networks (MNN) are used to build an empirical model of fed-batch process based on process operation data. Model prediction confidence bounds are calculated based on predictions of all component networks in an MNN model and the model prediction confidence bound at the end-point of a batch is incorporated into the optimization objective function. The modified objective function penalizes wide prediction confidence bounds in order to obtain a reliable optimal Control Profile. The non-linear optimization problem based on MNN with augmented objective function is solved by iterative dynamic programming. The proposed Control strategy is illustrated on a simulated fed-batch ethanol fermentation process. The results demonstrate that the optimal Control Profile calculated from the proposed approach is reliable in the sense that its performance degradation is limited when applied to the actual process.

  • ISNN (3) - Batch-to-Batch optimal Control based on support vector regression model
    Advances in Neural Networks – ISNN 2005, 2005
    Co-Authors: Yi Liu, Zhihua Xiong, Xianhui Yang, Jie Zhang
    Abstract:

    A support vector regression (SVR) model based batch to batch optimal Control strategy is proposed in this paper. Because of model plant mismatches and unknown disturbances the Control performance of optimal Control Profile calculated from empirical model is deteriorated. Due to the repetitive nature of batch processes, it is possible to improve the operation of the next batch using the information of the current and previous batch runs. A batch to batch optimal Control strategy based on the linearization of the SVR model around the Control Profile is proposed in this paper. Applications to a simulated batch styrene polymerization reactor demonstrate that the proposed method can improve process performance from batch to batch in the presence of model plant mismatches and unknown disturbances.