Event-Triggered Optimal Control for Macro–Micro Composite Stage System via Single-Network ADP Method

Chen, Xun; Chen, Xin; Bai, Weiwei; Guo, Zijie

doi:10.1109/tie.2020.2984462

Cited by 12 publications

(7 citation statements)

References 42 publications

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“…It is a kind of event accumulation behavior caused by zero inter execution time. For the Zeno behavior, 18,34 give similar proofs, indicating that when Assumption 3 is satisfied, the minimal sampling time is a positive constant away from zero. Thus, Zeno behavior can be excluded.…”

Section: Theoremmentioning

confidence: 76%

Event‐based robust performance guarantee for nonaffine plants via system identification

Wang

Zhou

et al. 2023

Intl J Robust & Nonlinear

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In this paper, by making use of recurrent neural networks (RNNs), a novel event-based robust optimal controller is designed for a category of continuous-time (CT) nonlinear nonaffine systems with disturbances. For tackling the optimal-robust problem transformation and the performance guarantee, a system identifier is developed to reconstruct the system, and an event-triggered critic-only strategy is investigated to replace the traditional time-based actor-critic structure. The RNN is adopted to reconstruct the nonaffine system as an identifier for obtaining the affine model. It simplifies the system structure and reduces computational burdens. In addition, the stability of the unknown nominal system learned by the RNN is proved. Then, using the obtained system identifier and the adaptive critic learning structure, the proposed event-triggered robust control with performance guarantee is realized. At last, the effectiveness of the given design method is verified by two simulation examples.

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Section: Theoremmentioning

confidence: 76%

Event‐based robust performance guarantee for nonaffine plants via system identification

Wang

Zhou

et al. 2023

Intl J Robust & Nonlinear

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“…This section discusses the research status of incorporating digital twins into the smart design of UPM equipment, as well as its components, such as bearing slideways, spindle-drive, stage module, servo module, and clamping module, as shown in Table 1. Bearing slideways Obtain a trade-off among feed velocity, achievable precision and resulting friction force Predict the performance of the designed bearing slideways in the operating process [9] Spindle-drive Achieve a balance among the anti-vibration capability, torque/speed range, and cost Timely and cost-economically verify its performance instead of destructive tests [10] Stage module Capable of sub-micron/nanometer positioning resolution and/or accuracy Optimize the adaptive control algorithm [11] Servo module Suffer from a lag phenomenon in dynamic tracking of the tool path Eliminate nonlinear factors including the friction effect of moving mechanism with nonlinear characteristics [12] Clamping module Achieve a balance among locating tolerance, minimum clamping force, and fixturing accuracy and stability Support real-time, geometry data-driven dynamic decision of the clamping forces and positioning [13]…”

Section: Digital Twins For Smart Design Of Upmmentioning

confidence: 99%

“…The macro-micro composite method, which comprises the macro-motion part and the micro-motion part, is a popular concept in ultra-precision stage research, due to its long-stroke, high-velocity, and high-precision metrics. To achieve an improvement of the machining accuracy and efficiency, Chen et al [11] proposed an event-triggered optimal control method for macromicro composite stage systems via a single-network adaptive dynamic programming method. The major barrier that impedes the establishment of the digital twin of the stage module is the simulation modeling and optimizing of the fast adaptive control algorithm.…”

Section: Digital Twins-based Stage System Module Designmentioning

confidence: 99%

Digital Twins-Based Smart Design and Control of Ultra-Precision Machining: A Review

Leng

2021

Symmetry

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Ultra-Precision Machining (UPM) is a kind of highly accurate processing technology developed to satisfy the manufacturing requirements of high-end cutting-edge products including nuclear energy producers, very large-scale integrated circuits, lasers, and aircraft. The information asymmetry phenomenon widely exists in the design and control of ultra-precision machining. It may lead to inconsistency between the designed performance and operational performance of the UPM equipment on stiffness, thermal stability, and motion accuracy, which result from its design, manufacturing, and control, and determine the form accuracy and surface roughness of machined parts. The performance of the UPM equipment should be improved continuously. It is still challenging to realize the real-time and self-adaptive control, in which building a high-fidelity and computationally efficient digital twin is a valuable solution. Nevertheless, the incorporation of the digital twin technology into the UPM design and control remains vague and sometimes contradictory. Based on a literature search in the Google Scholar database, the critical issues in the UPM design and control, and how to use the digital twin technologies to promote it, are reviewed. Firstly, the digital twins-based UPM design, including bearings module design, spindle-drive module design, stage system module design, servo module design, and clamping module design, are reviewed. Secondly, the digital twins-based UPM control studies, including voxel modeling, process planning, process monitoring, vibration control, and quality prediction, are reviewed. The key enabling technologies and research directions of digital twins-based design and control are discussed to deal with the information asymmetry phenomenon in UPM.

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“…Recently, the event-triggering mechanism [6] has been applied to design control strategies that update parameters, generate, and send new control signals to actuators only when new events occur; otherwise, they stop updating and transfer the previous control signals using zero-order holders (ZOH). The ET control policies have been proven to be effective for linear and nonlinear systems [7], [8] with industrial applications [9], [10]. Sahoo et al [7] employed the event-triggering principle and game theory to design a control scheme with disturbance rejection for linear systems.…”

Section: Introductionmentioning

confidence: 99%

Event-Triggered Robust Optimal Control for PMSM With Unknown Internal Dynamics, Disturbances, and Constrained Inputs

Tan,

Cong,

Cong

2024

IEEE Access

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In industry, for driving a permanent magnet synchronous motor (PMSM), it is more favorable to optimize control performances and reduce computational complexity and communication waste from a controller to actuators. For that reason, this paper employs an event-triggering mechanism to design a robust optimal control strategy for PMSM. Firstly, the PMSM model is presented as a strict-feedback nonlinear system with unknown internal dynamics, disturbances, and constrained inputs. Then, an eventtriggered (ET) feedforward control strategy is introduced to convert the separated speed and current dynamics into an augmented system. Secondly, an ET-robust optimal feedback control strategy and an ET disturbance compensation strategy are designed using adaptive dynamic programming (ADP) and zero-sum game theory. All controller parameters are tuned online without identifying unknown dynamics or using a persistent excitation condition. It is shown that system stability and the exclusion of Zeno's behavior are fulfilled. Finally, compared with the existing time-triggering control strategies in simulation and experiments with TMS320F28335 of Texas Instruments, the proposed strategy is more effective in reducing the burden of computation bandwidth and communication load. INDEX TERMS PMSM drives Event-triggering Optimal control Input constraints Disturbances Drift parameters.

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Event-Triggered Optimal Control for Macro–Micro Composite Stage System via Single-Network ADP Method

Cited by 12 publications

References 42 publications

Event‐based robust performance guarantee for nonaffine plants via system identification

Event‐based robust performance guarantee for nonaffine plants via system identification

Digital Twins-Based Smart Design and Control of Ultra-Precision Machining: A Review

Event-Triggered Robust Optimal Control for PMSM With Unknown Internal Dynamics, Disturbances, and Constrained Inputs

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