Command Filtered Adaptive Control for Flexible-Joint Robots With Full-State Quantization

This article further investigates the tracking control problem of flexible-joint robot systems. Compared with existing results, all states are assumed to be quantized by a uniform quantizer, which results in discontinuous quantized signals. To address this issue, a new adaptive controller is proposed by introducing a command filter, in which the quantized virtual controller is used as input to obtain continuous signals. Thus, the discontinuity problem is avoided and the quantization influence is further compensated. It can be proven that all signals in the closed-loop system are bounded and tracking errors can converge to an arbitrarily small neighborhood of the origin. Finally, a simulation result is given to verify the practicability of the proposed method.

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Publication Details

Journal
IEEE Transactions on Systems Man and Cybernetics Systems
Published
2024-09-06
DOI
https://doi.org/10.1109/tsmc.2024.3443636
Citations
7
Primary Topic
Adaptive Control of Nonlinear Systems
Type
article
Field-Weighted Citation Impact
2.30

Funders

Controls
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article

Command Filtered Adaptive Control for Flexible-Joint Robots With Full-State Quantization

Wei Sun, Renato De Leone, Xiangpeng Xie, Jing S. Pang
7 citations
IEEE Transactions on Systems Man and Cybernetics Systems
Adaptive Control of Nonlinear Systems
2.30
article

Command Filtered Adaptive Control for Flexible-Joint Robots With Full-State Quantization

Wei Sun, Renato De Leone, Xiangpeng Xie, Jing S. Pang
article en
7 citations

Abstract

This article further investigates the tracking control problem of flexible-joint robot systems. Compared with existing results, all states are assumed to be quantized by a uniform quantizer, which results in discontinuous quantized signals. To address this issue, a new adaptive controller is proposed by introducing a command filter, in which the quantized virtual controller is used as input to obtain continuous signals. Thus, the discontinuity problem is avoided and the quantization influence is further compensated. It can be proven that all signals in the closed-loop system are bounded and tracking errors can converge to an arbitrarily small neighborhood of the origin. Finally, a simulation result is given to verify the practicability of the proposed method.

IEEE Transactions on Systems Man and Cybernetics SystemsVol. 54(12)
Università di Camerino (IT), Liaocheng University (CN), Nanjing University of Posts and Telecommunications (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 11%
Adaptive Control of Nonlinear Systems
2.30
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