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A novel discrete-time neurodynamic algorithm for future constrained quadratic programming with wheeled mobile robot control

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Abstract

The problem of discrete-time dynamic constrained quadratic programming including equality and inequality constraints is formulated and investigated, simply termed future constrained quadratic programming (FCQP) problem in this paper. To obtain the optimal solution of such an FCQP problem in real time and with high precision, a novel discrete-time zeroing neurodynamic (DTZN) algorithm, which is developed by combining the corresponding continuous-time zeroing neurodynamic model and a five-step explicit linear multi-step (ELMS) rule, is proposed and termed ELMS-type five-step DTZN (5SDTZN) algorithm. Then, the convergence and precision of the ELMS-type 5SDTZN algorithm are analyzed theoretically. For comparison, three other DTZN algorithms as well as discrete-time gradient and varying-parameter neurodynamic algorithms are also presented. Afterward, through numerical verifications and comparisons, the efficacy and superiority of the ELMS-type 5SDTZN algorithm for solving the FCQP problem are illustrated. Finally, the applicability of the ELMS-type 5SDTZN algorithm for the coordinated repetitive motion control of a wheeled mobile robot with physical constraints is demonstrated.

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The data used in this paper to support the results of this study are available from the first author upon reasonable request.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant 62006254, in part by the Guangdong Basic and Applied Basic Research Foundation under Grant 2019A1515012128, and in part by the Science and Technology Plan Project of Guangzhou under Grant 202102080656.

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Authors and Affiliations

  1. School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, 518107, China

    Binbin Qiu, Xiao-Dong Li & Song Yang

  2. School of Information and Intelligent Engineering, Guangzhou Xinhua University, Dongguan, 523133, China

    Xiao-Dong Li

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  1. Binbin Qiu
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  2. Xiao-Dong Li
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  3. Song Yang
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Correspondence to Xiao-Dong Li.

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Qiu, B., Li, XD. & Yang, S. A novel discrete-time neurodynamic algorithm for future constrained quadratic programming with wheeled mobile robot control. Neural Comput & Applic 35, 2795–2809 (2023). https://doi.org/10.1007/s00521-022-07757-6

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