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您的检索式：作者名="Frank LLEWIS"
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| 1 | Error-based adaptive optimal tracking control of nonlinear discrete-time systems显示文摘In this paper,for the output tracking problem of nonlinear discrete-time systems,a performance index is newly defined using the adaptive dynamic programming(ADP)technique to completely eliminate tracking errors in theory.In contrast to traditional definitions of performance indices in other ADP-based methods,the proposed performance index is not only designed from the perspective of output tracking errors but also introduced errors of system states and control inputs at adjacent stages,which is suitable for practical situations in many industrial applications,such as the alumina production,the flotation process,and the mineral grinding process.We proved that the obtained controller can make the system output fully track the given reference trajectory by applying the iterative criteria of the ADP technique.In addition,the proposed algorithm was implemented using a data-driven technique and neural networks to avoid analyzing and deducing the complicated dynamics of actual industrial processes.Finally,using historical data for a forced-circulation evaporation system in the alumina production process,the effect of the proposed approach was verified through a numerical simulation and compared with that of the proportional-integral controller. | Chun LI Jinliang DING Frank LLEWIS Tianyou CHAI | 2024 | Science China(Information Sciences)2024，67，1： | 0 |
| 2 | Reinforcement learning for optimal tracking of large-scale systems with multitime scales显示文摘This paper aims to solve an optimal tracking control(OTC)problem of large-scale systems with multitime scales and coupled subsystems using singular perturbation(SP)theory and reinforcement learning(RL)techniques.A considerable contribution of this paper is the development of a data-driven SP-based RL method for the OTC of unknown large-scale systems with multitime scales.To achieve this,a multitime scale tracking problem was decomposed into a linear quadratic tracker problem for slow subsystems and a dynamical game problem for fast subsystems using the SP theory.Then,the distributed composite feedback controllers were found using a distributed off-policy integral RL algorithm that uses only measured data from the system in real time.Thus,the operational index can follow its prescribed target value via an approximately optimal approach.Theoretical analysis and proof are presented to demonstrate that the sum of the performances of reduced-order subsystems is approximately equal to the performance of the original large-scale system.Finally,numerical and practical examples are provided to validate the effectiveness of the proposed method. | Jinna LI Hao NIE Tianyou CHAI Frank LLEWIS | 2023 | Science China(Information Sciences)2023，66，7： | 0 |
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