The Experts below are selected from a list of 588 Experts worldwide ranked by ideXlab platform
Sobolic Frantisek - One of the best experts on this subject based on the ideXlab platform.
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Retrospective Cost Adaptive Control with Concurrent Closed-Loop Identification
2024Co-Authors: Sobolic FrantisekAbstract:Retrospective cost adaptive control (RCAC) is a discrete-time direct adaptive control algorithm for stabilization, command following, and disturbance rejection. RCAC is known to work on systems given minimal modeling information which is the leading Numerator Coefficient and any nonminimum-phase (NMP) zeros of the plant transfer function. This information is normally needed a priori and is key in the development of the filter, also known as the target model, within the retrospective performance variable. A novel approach to alleviate the need for prior modeling of both the leading Coefficient of the plant transfer function as well as any NMP zeros is developed. The extension to the RCAC algorithm is the use of concurrent optimization of both the target model and the controller Coefficients. Concurrent optimization of the target model and controller Coefficients is a quadratic optimization problem in the target model and controller Coefficients separately. However, this optimization problem is not convex as a joint function of both variables, and therefore nonconvex optimization methods are needed. Finally, insights within RCAC that include intercalated injection between the controller Numerator and the denominator, unveil the workings of RCAC fitting a specific closed-loop transfer function to the target model. We exploit this interpretation by investigating several closed-loop identification architectures in order to extract this information for use in the target model.PHDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138440/1/fsobolic_1.pd
Dennis S Bernstein - One of the best experts on this subject based on the ideXlab platform.
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retrospective cost adaptive harmonic disturbance rejection using dereverberated target models
Advances in Computing and Communications, 2021Co-Authors: Nima Mohseni, Dennis S BernsteinAbstract:The present paper focuses on adaptive feedback disturbance rejection for high-order, lightly damped systems using retrospective cost adaptive control (RCAC). RCAC requires a closed-loop target model, which captures key features of the plant dynamics. In the SISO case, this information includes knowledge of the sign of the leading Numerator Coefficient, relative degree, and non-minimum phase zeros. The present paper investigates the feasibility of using a deverberated transfer function (DTF) as the closed -loop target model. A dereverberated model of a lightly damped plant captures the magnitude and phase trend but ignores resonances and antiresonances, thus providing a simplified, low-order model of a lightly damped system. The present paper investigates the performance and robustness of RCAC using a dereverberated target model based on the nominal plant model.
Nima Mohseni - One of the best experts on this subject based on the ideXlab platform.
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retrospective cost adaptive harmonic disturbance rejection using dereverberated target models
Advances in Computing and Communications, 2021Co-Authors: Nima Mohseni, Dennis S BernsteinAbstract:The present paper focuses on adaptive feedback disturbance rejection for high-order, lightly damped systems using retrospective cost adaptive control (RCAC). RCAC requires a closed-loop target model, which captures key features of the plant dynamics. In the SISO case, this information includes knowledge of the sign of the leading Numerator Coefficient, relative degree, and non-minimum phase zeros. The present paper investigates the feasibility of using a deverberated transfer function (DTF) as the closed -loop target model. A dereverberated model of a lightly damped plant captures the magnitude and phase trend but ignores resonances and antiresonances, thus providing a simplified, low-order model of a lightly damped system. The present paper investigates the performance and robustness of RCAC using a dereverberated target model based on the nominal plant model.
Masami Saeki - One of the best experts on this subject based on the ideXlab platform.
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experimental study of virtual disturbance loop shaping method for angular velocity control of a belt drive system
2009 ICCAS-SICE, 2009Co-Authors: Yosuke Sugitani, Masami SaekiAbstract:In our previous study, we have proposed a design method of a static feedback gain for a nonparametric model described by a plant response data. The magnitudes of the sensitivity and complementary sensitivity functions are shaped. An appropriate gain can be obtained by solving a linear matrix inequality. In this paper, the usefulness is shown by applying the method to an experimental setup where a load disc is driven by a DC motor with belts. PI controller, state feedback gain, and the Numerator Coefficient of the observer-based controller are tuned successfully for velocity control.
Yosuke Sugitani - One of the best experts on this subject based on the ideXlab platform.
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experimental study of virtual disturbance loop shaping method for angular velocity control of a belt drive system
2009 ICCAS-SICE, 2009Co-Authors: Yosuke Sugitani, Masami SaekiAbstract:In our previous study, we have proposed a design method of a static feedback gain for a nonparametric model described by a plant response data. The magnitudes of the sensitivity and complementary sensitivity functions are shaped. An appropriate gain can be obtained by solving a linear matrix inequality. In this paper, the usefulness is shown by applying the method to an experimental setup where a load disc is driven by a DC motor with belts. PI controller, state feedback gain, and the Numerator Coefficient of the observer-based controller are tuned successfully for velocity control.
