Enhanced accuracy and adaptability: An ISSA-optimized MPC approach for AGV trajectory tracking

Tan Zhang; Chengjun Ding; Tengfei Ma; Zijian Li; Zhikai Jing; Jinshen Yu; Jingyu Ge; Ping Duan; Jianing Zhang

doi:10.1371/journal.pone.0345476

Peer Review History

Original SubmissionMarch 4, 2026
18 Mar 2026 Decision Letter - Jinhao Liang, Editor -->PONE-D-26-10662-->-->Enhanced Accuracy and Adaptability: An ISSA-Optimized MPC Approach for AGV Trajectory Tracking-->-->PLOS One Dear Dr. Ding, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by May 02 2026 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. 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The conclusions must be drawn appropriately based on the data presented. --> Reviewer #1: Yes Reviewer #2: Partly ******** -->2. Has the statistical analysis been performed appropriately and rigorously? --> Reviewer #1: Yes Reviewer #2: No ****** -->3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.--> Reviewer #1: Yes Reviewer #2: Yes ****** -->4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.--> Reviewer #1: Yes Reviewer #2: Yes ****** -->5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)--> Reviewer #1: This manuscript proposes an adaptive trajectory tracking control framework for automated guided vehicles (AGVs) by integrating an Improved Sparrow Search Algorithm (ISSA) with Model Predictive Control (MPC) to optimize controller parameters online. The paper develops kinematic and dynamic models of a forklift-type AGV and validates the proposed strategy through simulation and real-vehicle implementation. The topic is relevant to intelligent logistics and AGV control, and the integration of optimization algorithms with MPC is a meaningful direction for improving adaptability. However, the manuscript still presents several limitations in terms of methodological clarity, theoretical justification, and depth of analysis. In its current form, the technical contributions and the advantages of the proposed approach are not sufficiently articulated. Therefore, I recommend major revision before the manuscript can be considered for publication. 1.The core contribution of the manuscript lies in improving the Sparrow Search Algorithm and using it to optimize MPC parameters online. However, the paper mainly introduces several heuristic modifications, including Tent chaotic initialization, disturbance factors, and Cauchy mutation, without clearly explaining the theoretical motivation behind these design choices. It would strengthen the manuscript if the authors could more clearly explain why these specific mechanisms improve the search behavior of the algorithm and how they address the limitations of the standard SSA in the context of MPC parameter tuning. 2.The paper states that ISSA is used to periodically optimize the weight parameters of the MPC cost function, but the integration between the optimization algorithm and the MPC controller is not fully clarified. In particular, the manuscript does not clearly describe how frequently the optimization is executed, how the optimization variables are defined, and how the updated parameters influence the control process over time. A clearer explanation of the interaction between ISSA and the MPC control loop would improve the transparency and reproducibility of the proposed framework. 3.The AGV dynamic model is derived based on several simplifying assumptions, such as small slip angles, planar motion, and simplified tire force relationships. While such assumptions are common in vehicle modeling, the manuscript does not sufficiently discuss their potential impact on control accuracy or the validity of the model under different operating conditions. A deeper discussion of the modeling limitations and their implications for the proposed control strategy would improve the technical rigor of the study. 4.The manuscript frequently claims that the improved algorithm enhances global exploration capability, prevents premature convergence, and improves tracking performance. However, these claims are primarily explained qualitatively. The paper would benefit from a more analytical discussion of how the algorithm modifications influence optimization behavior and why these changes are expected to produce better parameter tuning results for MPC. 5.Although the introduction reviews several trajectory tracking control approaches, the manuscript does not clearly position the proposed method within the broader research landscape of adaptive MPC and intelligent optimization-based controller tuning. Many existing studies have explored similar strategies that combine metaheuristic algorithms with MPC. The authors should more clearly highlight what differentiates their approach from existing methods and clarify the specific technical gap that this work aims to address. 6.The background should give a more detailed literature review on the path-tracking of the AGV. Some recent work, such as “A Polytopic Model-based Robust Predictive Control Scheme for Path Tracking of Autonomous Vehicles, IEEE Transactions on Intelligent Vehicles, vol. 9, no. 2, pp. 3928-3939, Feb. 2024” and “ETS-Based Human–Machine Robust Shared Control Design Considering the Network Delays, IEEE Transactions on Automation Science and Engineering, vol. 22, pp. 17501-17511, 2025” can be referred. Reviewer #2: The authors presented an adaptive trajectory tracking strategy for automated guided vehicles (AGVs) by combining Model Predictive Control (MPC) with an Improved Sparrow Search Algorithm (ISSA). They established a kinematic and a simplified three-degree-of-freedom (3-DOF) dynamic model for a forklift-type AGV. To overcome the limitations of fixed-weight MPC, the authors propose tuning the time-domain parameters online using ISSA, which is enhanced via Tent chaotic mapping for population initialization, dynamic disturbance factors, and Cauchy mutation operators to balance global and local searches. The proposed AT-ISSA-MPC controller is validated against a standard Fixed Time-domain MPC (FT-MPC) through ROS/Gazebo simulations and a real-world test on a forklift AGV operating at 0.5m/s. Decision: Major revision Comments are attached separately. ****** -->6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? 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Attachments Attachment Submitted filename: Review.docx https://doi.org/10.1371/journal.pone.0345476.r001
Revision 1
3 Apr 2026 Author Response We sincerely thank the editor and reviewers for their valuable feedback, which has helped us improve the quality of the manuscript. The comments from the editor and reviewers are listed below in bold and italicized font, and specific issues have been numbered. Our responses are provided in normal font, and the changes/additions to the manuscript are highlighted in blue. As the paper template does not indicate section numbers, the corresponding section numbers are specified as follows: 0 Introduction 1 Establishment of the AGV motion model 1.1 Kinematic model 1.2 Dynamic model 2 MPC controller design 2.1 Linearization and discretization of nonlinear systems 2.2 Output prediction equations 2.3 Objective function design 2.4 Reformulation as a quadratic programming problem for solution 2.5 Feedback correction 3 Adaptive time-domain MPC controller design 3.1 Impact of time-domain parameters on tracking performance 3.2 Improved sparrow search algorithm 3.2.1 Discovery phase with dynamically adjusted exploration and exploitation 3.2.2 Adaptive mutation in the follower phase 3.2.3 Dynamic boundary constraints in the sentinel phase 3.3 Fitness function selection 3.4 Tent chaotic map 4 Simulation analysis and experimental verification 4.1 Simulation analysis of the double lane change maneuver 4.2 Simulation analysis of the straight-line maneuver 4.3 Forklift-type AGV experimental validation 5 Conclusion The specific responses to the editor and reviewers' comments are as follows: 1. Journal Requirements 1.1 Response to Requirement 1 Requirement 1: Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at: https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf Response 1: We sincerely thank the editor for the reminder. We have carefully reviewed the formatting requirements of PLOS ONE (including the two templates you provided: the main text formatting guide and the title page formatting guide) and will comprehensively revise the format, file naming, and other aspects of the manuscript to ensure full compliance with the journal’s style requirements. 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We fully understand the importance of sharing code for enhancing research transparency and reproducibility. The source code for this study was developed within a technology transfer project in collaboration with an enterprise, and its ownership is jointly held by both parties. After consultation with the enterprise, due to intellectual property considerations, including pending patents, they have requested that the code not be publicly released at this stage. In light of these confidentiality requirements, we are currently unable to make the code publicly available. However, once the intellectual property issues are resolved, we would be happy to consider reasonable requests for access to the code for the purpose of verifying the results of this study. 1.3 Response to Requirement 3 Requirement 3: We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match. 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(1) Removal from the Acknowledgments section We have removed the following funding-related text from the Acknowledgments section of the manuscript: “This work was supported by the Tianjin Science and Technology Plan Project (Grant No. 25ZXRGGX00310) and the Shijiazhuang Science and Technology Cooperation Special Project (Grant No. SJZZXA25003).” The Acknowledgments section now contains only personal acknowledgments, as follows: “Thanks to Prof. Chengjun Ding for his guidance. Thanks to Tan Zhang, Jingyu Ge, Tengfei Ma, Zijian Li, Zhikai Jing, Jinshen Yu and Jianing Zhang for their assistance in the project.” (2) Updated Funding Statement Please replace the current Funding Statement (“The authors received no specific funding for this work.”) with: “This work was supported by the Tianjin Science and Technology Plan Project (Grant No. 25ZXRGGX00310) and the Shijiazhuang Science and Technology Cooperation Special Project (Grant No. SJZZXA25003).” We have ensured that no funding information appears elsewhere in the manuscript. As we could not locate the Funding Statement option in the submission system, we kindly request that you update it on our behalf. 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Response 5: Thank you for your inquiry regarding our Data Availability Statement. We have carefully reviewed PLOS’s policy on the minimum dataset. Regarding shareable data: We have provided all processed data necessary to generate the figures and statistical analyses presented in the manuscript. These data, including the trajectories in the path tracking plots and the error metrics reported in the results, are available in the Supporting Information file (Figures_and_Related_Data.zip). This dataset is sufficient to verify the comparative performance conclusions presented in this study. Regarding restricted raw data: The complete raw data logs (e.g., high-frequency sensor data streams, internal control signals) are owned by our industrial partner as part of a technology transfer agreement and are subject to a pending patent. Due to these intellectual property and confidentiality considerations, the full raw dataset cannot be made publicly available. 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We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission: 1) You may seek permission from the original copyright holder of Figure 11 to publish the content specifically under the CC BY 4.0 license. We recommend that you contact the original copyright holder with the Content Permission Form (http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text: “I request permission for the open-access journal PLOS ONE to publish XXX under the Creative Commons Attribution License (CCAL) CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. 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If applicable, please specify in the figure caption text when a figure is similar but not identical to the original image and is therefore for illustrative purposes only. Response 6: Thank you for your careful review of Fig. 11. We would like to clarify that this figure is entirely original and created by the authors. The forklift-type AGV shown in Fig. 11 is a self-developed prototype modified from a traditional electric forklift. The photograph was taken by the authors, and all annotations were manually added. No third-party copyrighted materials are included in this figure. Therefore, this figure fully complies with the CC BY 4.0 license requirements, and no external copyright permission is needed. Please let us know if any further documentation or confirmation is required. 1.7 Response to Requirement 7 Requirement 7: If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise. Response 7: Thank you for your attention. We have evaluated the literature recommended by the reviewer and related studies, and carefully reviewed the suggested references, confirming that they are highly relevant to this work. Therefore, we have incorporated them into the revised manuscript. Specifically, the following references have been added to the Introduction section to support the literature review on adaptive MPC and trajectory tracking control (Page 2): 25. Jinhao Liang, Qingyun Tian, Jiwei Feng, Dawei Pi, Guodong Yin. A Polytopic Model-Based Robust Predictive Control Scheme for Path Tracking of Autonomous Vehicles. IEEE Transactions on Intelligent Vehicles. 2024; 9(2): 3928-3939. DOI: 10.1109/TIV.2023.3340668 26. Jinhao Liang, Yanbo Lu, Faan Wang, Jiwei Feng, Dawei Pi, Guodong Yin. ETS-Based Human–Machine Robust Shared Control Design Considering the Network Delays. IEEE Transactions on Automation Science and Engineering. 2025; 22: 17501-17511. DOI: 10.1109/TASE.2024.3383094 35. Qi Xia, Peng Chen, Guoyan Xu, Bin Zhou, Guizhen Yu. Reinforcement Learning-Based Adaptive Safety Tracking Controller for Autonomous Mining Trucks. IEEE Transactions on Vehicular Technology. 2025; 74(7): 10122-10136. DOI: 10.1109/TVT.2025.3546647 36. Kairui Chen, Yixiang Gu, Weicong Huang, Zhonglin Zhang, Zian Wang, Xiaofeng Wang. Fixed-Time Adaptive Event-Triggered Guaranteed Performance Tracking Control of Nonholonomic Mobile Robots under Asymmetric State Constraints. Mathematics. 2024; 12(10): 1471. https://doi.org/10.3390/math12101471 37. Huarong Zheng, Rudy R. Negenborn, Gabriël Lodewijks. Fast ADMM for Distributed Model Predictive Control of Cooperative Waterborne AGVs. IEEE Transactions on Control Systems Technology. 2017; 25(4): 1406-1413. DOI: 10.1109/T Attachments Attachment Submitted filename: Response to Reviewers.pdf https://doi.org/10.1371/journal.pone.0345476.r002
4 May 2026 Decision Letter - Jinhao Liang, Editor Enhanced accuracy and adaptability: an ISSA-optimized MPC approach for AGV trajectory tracking PONE-D-26-10662R1 Dear Dr. Ding, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. 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Has the statistical analysis been performed appropriately and rigorously? --> Reviewer #1: Yes Reviewer #2: Yes ****** -->4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.--> Reviewer #1: Yes Reviewer #2: Yes ****** -->5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.--> Reviewer #1: Yes Reviewer #2: Yes ****** -->6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)--> Reviewer #1: This manuscript proposes an adaptive trajectory tracking control framework for automated guided vehicles (AGVs) by integrating an Improved Sparrow Search Algorithm (ISSA) with Model Predictive Control (MPC) to optimize controller parameters online. Reviewer #2: The authors have systematically addressed every major and minor concern raised, significantly elevating the scientific rigor, reproducibility, and practical relevance of the manuscript. Specifically, the following revisions have greatly strengthened the paper: Computational Feasibility: By explicitly providing the control cycle (40 ms) and the measured execution times of the AT-ISSA-MPC algorithm (28.5 ms average, 35.6 ms peak), the authors have completely resolved my concerns regarding the real-time viability of running an online metaheuristic optimizer. The explanation of the decoupled 2-second background trigger was an excellent clarification. Modeling Assumptions: The addition of quantitative boundaries for the dynamic model—specifically capping the operational speed at 1.5 m/s and limiting the linear tire model assumption to slip angles of 3-5 degrees—successfully grounds the theoretical control design in physical, industrial reality. Control-Theoretic Depth: The updated analysis of the double lane change and straight-line deviation scenarios is excellent. The explicit explanation of how the ISSA algorithm dynamically adjusts the prediction (N_p) and control (N_c) horizons to anticipate curves and suppress transient overshoot provides the exact mechanistic depth that was previously missing. Practical Significance: The authors successfully connected their numerical error reductions to real-world industrial constraints. Framing the 49% reduction in peak lateral error in the context of narrow-aisle collision avoidance and precision docking effectively answers the "practical significance" critique. Literature and Citations: The expanded introduction, which now appropriately contextualizes the ISSA approach against modern trends like Reinforcement Learning and ADMM, provides a much stronger theoretical framing for the paper. Additionally, providing concrete citations for the limitations of "traditional methods" reflects sound academic practice. ****** -->7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.--> Reviewer #1: No Reviewer #2: No ******** https://doi.org/10.1371/journal.pone.0345476.r003
Formally Accepted
Acceptance Letter - Jinhao Liang, Editor PONE-D-26-10662R1 PLOS One Dear Dr. Ding, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS One. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset You will receive further instructions from the production team, including instructions on how to review your proof when it is ready. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few days to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. You will receive an invoice from PLOS for your publication fee after your manuscript has reached the completed accept phase. If you receive an email requesting payment before acceptance or for any other service, this may be a phishing scheme. Learn how to identify phishing emails and protect your accounts at https://explore.plos.org/phishing. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Jinhao Liang Academic Editor PLOS One https://doi.org/10.1371/journal.pone.0345476.r004

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