Trajectory Tracking Based on Active Disturbance Rejection Control for Compound Unmanned Aircraft
Round 1
Reviewer 1 Report
1. What is the main question addressed by the research?
In this paper, supported the institution of a mathematical model of the motion characteristics for the compound unmanned aircraft, the Simulink simulation model of the managementled plant is about up. The control strategy with totally different flight modes and therefore the mechanical phenomenon following system based on Active Disturbance Rejection management (ADRC) are designed. Then Genetic Algorithm-Particle Swarm improvement (GA-PSO) is employed to optimize the controller parameters to resolve the matter that the controller parameters are troublesome to tune. The simulation take a look at of route tracking control and spiral climb with different flight modes verified that the fastness, stability, anti-interference and hardiness of the ADRC mechanical phenomenon following system are higher than that of pid trajectory tracking control system.
2. Do you consider the topic original or relevant in the field? Does it address a specific gap in the field?
The subject is original and has been evaluated to fill a gap in the literature.
3. What does it add to the subject area compared with other published material?
In this paper, a non-linear flight dynamics model is used as compound unmanned aircraft and active disturbance rejection control system is designed for it.
4. What specific improvements should the authors consider regarding the methodology? What further controls should be considered?
In the recommended references, there are approaches to evaluate possible malfunctions in the flight control system. It can also be evaluated for hybrid structure in artificial neural networks and processes based on fuzzy logic.
5. Are the conclusions consistent with the evidence and arguments presented and do they address the main question posed?
The results were well reviewed and considered consistent with the study.
6. Are the references appropriate?
Some references are out of date: 3-5, 7, 13-16, 27, 28. Suggested references listed below or other references related to the subject should be included in the study instead of these references.
Kilic, U., & Unal, G. (2021). Sensor fault detection and reconstruction system for commercial aircrafts. The Aeronautical Journal, 1-17.
Unal, G. (2021), "Fuzzy robust fault estimation scheme for fault tolerant flight control systems based on unknown input observer", Aircraft Engineering and Aerospace Technology, Vol. 93 No. 10, pp. 1624-1631. https://doi.org/10.1108/AEAT-12-2020-0302.
Kilic, U. And Unal, G. (2021), "Aircraft air data system fault detection and reconstruction scheme design", Aircraft Engineering and Aerospace Technology, Vol. 93 No. 6, pp. 1104-1114. https://doi.org/10.1108/AEAT-01-2021-0018.
Unal, G. (2021), "Integrated design of fault-tolerant control for flight control systems using observer and fuzzy logic", Aircraft Engineering and Aerospace Technology, Vol. 93 No. 4, pp. 723-732. https://doi.org/10.1108/AEAT-12-2020-0293.
Kaba, A., & Kıyak, E. (2020). Optimizing a Kalman filter with an evolutionary algorithm for nonlinear quadrotor attitude dynamics. Journal of Computational Science, 39, 101051.
7. Please include any additional comments on the tables and figures.
Figures 10-12 and 14-16 are difficult to examine. It would be appropriate to present these figures as larger if possible.
Author Response
Dear Reviewer:
Thank you for your valuable advice!
I have revised the original manuscript according to your opinions. The following is my detailed explanation for the revision of each review opinion. Attached are my revised manuscript.
Advice 1: Some references are out of date: 3-5, 7, 13-16, 27, 28. Suggested references listed below or other references related to the subject should be included in the study instead of these references.
Explanation 1: The suggested references have been updated.
Advice 2: Figures 10-12 and 14-16 are difficult to examine. It would be appropriate to present these figures as larger if possible.
Explanation 2: The typeface in the figures has been enlarged and the vectorization figures have been adopted.
Kind regards,
Master Bohai Deng
Reviewer 2 Report
* The introduction needs to be restructured. The introduction should be written in an inverted pyramid structure, i.e., from the general/global problem (motivation) to the particular technical problem.
* For the particular problem, in my opinion, there are some relevant sources but the text should be better organized and evaluated them in a critical way, identifying gaps in the information and relating them to the selected problem and especially with the proposed solution alternative. The introduction needs to incorporate the most recent ideas and cutting-edge features of the alternatives proposed in the literature. It must include an analysis of the advantages/disadvantages/limitations, pros and cons of the solutions reported in the literature as well as a detailed review of the most recent theories, ideas, tools, methodologies, techniques and technologies, even used in other contexts, that should be considered to propose a solution that overcomes the limitations of existing ones.
* In the literature there are hundreds of works about tuning different controllers with different genetic algorithms and including PSO, why this paper is new?
* Some figures are very small. Please improve the quality of the figures. Use vectorized figures for a better display.
* The proposed strategy needs to be compared against a recent relevant strategy. The comparison with a PID is unfair. There are a lot of recent strategies aimed at trajectory tracking for UAVs under disturbances and uncertainty, for instance, one relevant strategy is Filtered observer-based ida-pbc control for trajectory tracking of a quadrotor, IEEE Access, 2021. This can also help in the literature analysis.
* The Abstract and Conclusions presented in the manuscript are not presented well and require revision to sufficiently point towards novel/substantial finding(s)/contribution(s) of the study. Therefore, both sections require revision in terms of highlighting relevant contributions and enhancing the quality of the write-up.
* There are a lot of language problems in the paper. Typos, grammar, and also a lot of general sentences are repeated. The paper is very hard to read.
Author Response
Dear Reviewer:
Thank you for your valuable advice!
I have revised the original manuscript according to your opinions. The following is my detailed explanation for the revision of each review opinion. Attached is my revised manuscript.
Advice 1: There are a lot of language problems in the paper. Typos, grammar, and also a lot of general sentences are repeated. The paper is very hard to read.
Explanation 1: The language of the whole paper has been carefully examined and revised.
Advice 2: The introduction needs to be restructured. The introduction should be written in an inverted pyramid structure, i.e., from the general/global problem (motivation) to the particular technical problem.
Explanation 2: The inverted pyramid structure has been adopted. The introduction has been rewritten.
Advice 3: In the literature there are hundreds of works about tuning different controllers with different genetic algorithms and including PSO, why this paper is new?
Explanation 3: GA-PSO algorithm proposed in this paper combines the advantages of genetic algorithm and particle swarm optimization algorithm, which is improved with the help of the sigmoid function in crossover and mutation probability, adaptive inertia weight coefficient of particle update speed. The main purpose of developing GA-PSO algorithm is to solve the problem that ADRC parameters are difficult to tune. In the research of a trajectory tracking control system based on the ADRC for the compound unmanned aircraft, the parameter tuning method is new. According to the simulation results in Section 3, GA-PSO has good parameter tuning effect.
Advice 4: Some figures are very small. Please improve the quality of the figures. Use vectorized figures for a better display.
Explanation 4: The typeface in the figures has been enlarged and the vectorization figures have been adopted.
Advice 5: The proposed strategy needs to be compared against a recent relevant strategy. The comparison with a PID is unfair.
Explanation 5: The compound unmanned aircraft has more complex dynamics. For the controlled plant, there are internal dynamical uncertainties and external disturbance. The linear controller based on linear dynamics model is not suitable. In this paper, aimed at the nonlinear dynamics model of the compound unmanned aircraft, a nonlinear controller based on ADRC is proposed to obtain better control effect, which is used as control strategy in different flight mode. The proposed strategy is designed because the PID control strategy has its deficiency in the application of the compound unmanned aircraft. Therefore, the comparison with a PID is conducted. The PID strategy is a typical linear controller, and ADRC is a nonlinear controller. It is appropriate to compare the control effect of ADRC with PID for the subject.
Advice 6: The Abstract and Conclusions presented in the manuscript are not presented well and require revision to sufficiently point towards novel/substantial finding(s)/contribution(s) of the study. Therefore, both sections require revision in terms of highlighting relevant contributions and enhancing the quality of the write-up.
Explanation 6: The Abstract and Conclusions have been revised with your advice.
Kind regards,
Master Bohai Deng
Round 2
Reviewer 2 Report
The authors have made some effort to improve their paper. However, I still have some concerns.
The PSO justification is not convincing. The justification in the paper boils down to: "All above optimization algorithms have good application simulation results, but these algorithms are difficultly utilized into the compound unmanned aircraft... (The PSO) reduces the parameter tuning difficulty". Why is it difficult to apply if the tuning is offline? You have to be more specific on the disadvantages. Present the drawbacks from a technical perspective.
The proposed strategy needs to be compared against a recent relevant strategy. The comparison with a PID is unfair. As I mentioned in my previous review, there are recent strategies for trajectory tracking for UAVs under disturbances and uncertainty. Why not use at least one of the strategies in the introduction of your paper? Why not use the PSO to tune the PID control parameters for a more even comparison?
The language still needs to be improved.
Finally, as a personal request, please prepare the revision without using the strikethrough text. It is very difficult to review. Just mark the changes with the highlight tool or use colored text.
Author Response
Dear Reviewer:
Thank you for your valuable advice!
I have revised the manuscript according to your opinions. The following is my detailed explanation for the revision of each review opinion. Attached is the revised manuscript.
Advice 1: The PSO justification is not convincing. The justification in the paper boils down to: "All above optimization algorithms have good application simulation results, but these algorithms are difficultly utilized into the compound unmanned aircraft... (The PSO) reduces the parameter tuning difficulty". Why is it difficult to apply if the tuning is offline? You have to be more specific on the disadvantages. Present the drawbacks from a technical perspective.
Explanation 1: The justification given before is not accurate and has been revised. The main purpose of developing GA-PSO algorithm is to solve the problem that ADRC parameters are difficult to tune. In the research of a trajectory tracking control system based on the ADRC for the compound unmanned aircraft, the parameter tuning method is new. According to the simulation results in Section 3, GA-PSO has good parameter tuning effect.
Advice 2: The proposed strategy needs to be compared against a recent relevant strategy. The comparison with a PID is unfair. As I mentioned in my previous review, there are recent strategies for trajectory tracking for UAVs under disturbances and uncertainty. Why not use at least one of the strategies in the introduction of your paper? Why not use the PSO to tune the PID control parameters for a more even comparison?
Explanation 2: I have to admit the fact it’s difficult for me to design a new controller to realize trajectory tracking for the compound unmanned aircraft in a short time. But I used the GA-PSO to tune the PID control parameters for a more even comparison, which improves the control effect. And I will use other recent nonlinear strategies to realize trajectory tracking for UAVs under disturbances and uncertainty in future work.
Advice 3: The language still needs to be improved.
Explanation 3: The language of the whole paper has been carefully examined and improved.
The changes are highlighted in red.
Kind regards,
Bohai Deng
Author Response File: 
Author Response.docx
Round 3
Reviewer 2 Report
I have no further comments
