Time-Varying Formation Tracking Control for Unmanned Aerial Vehicles with the Leader’s Unknown Input and Obstacle Avoidance: Theories and Applications

Round 1

Reviewer 1 Report

The article is very interesting and addresses the current research problem of collision avoidance of UAVs. The article is well developed in terms of content and all issues are correctly described. However, I would like to ask you to correctly introduce and include more literature analysis of the research problem addressed. The presented algorithm in the article needs a better description and explanation of all the variables defined in the collision avoidance method. Please describe in detail Figure 1. In Chapter 4, please provide the technical parameters used in the UAV simulations. Please analyse the results obtained in more detail and improve the final conclusions.

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Reviewer 2 Report

Dear Authors,

The manuscript deals with interesting and topical issues. The content presented includes both theoretical analysis as well as simulations and practical tests. Actually, I would not have any major objections to the manuscript if it were not for the references to at least 12 works by the authors (out of 26 citations in total). These citations are correctly applied and are based on the correct content. However, the question arises, have the authors made an in-depth analysis of the work of other authors? Please show the novelty of your article in relation to the works of other authors, and not only in relation to your own works. I consider this to be the main disadvantage of the manuscript in the presented form - it requires improvement.

Is the title of section 3 correct? I don't think so.

The obtained results were not summarized in a synthetic form. The summary is general, short, and does not refer to quantitative results.

The summary is mixed with the research results. The article, especially in the final part, is very chaotic and disordered (mainly in terms of editing, but also in terms of content).

Best regards,
Reviewer

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Reviewer 3 Report

This paper investigates the time-varying formation tracking (TVFT) problems for unmanned aerial vehicle (UAV) swarm systems with the leader's unknown input and collision avoidance mechanism.

Contributions compared to the state-of-the-art on robot formation control are not clear to me.

It is not clear which sensor is used for collision avoidance. How does a robot detect another robot or obstacles?

The dynamic model (2) is too simple.

Conclusion is too short and is not meaningful.

Assumptions 1,2,3 are too strong.

The experiment look very trivial. Obstacle is too small. drones move too slowly.

2D manuever is considered, which is trivial. motion capture provides the global localization of robots, which makes the experiment trivial.

Author Response

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Reviewer 4 Report

Please consider the comments below to improve the paper further:

1   1) Please provide more accurate and informative title for the paper. English of the paper should be polished as well. Title of the paper should reflect the key contributions of the paper. 

      2) Abstract of the paper should be improved. The first sentence can state the importance of the content, then the gaps in the corresponding literature. Key contributions of the paper should be expressed clearly and then the major findings of the paper should be provided.

3   3) Introduction has provided some background researches and highlighted their advantages and disadvantages. However, critical review of the recent and related works are not quite strong. The corresponding gaps should be emphasized strongly and based on these gaps, the claimed contributions of the paper should be justified.

6    4) Please improve the equations by adding brief insights about them. In the current form, they are just given without reflecting the key properties of them.

7   5) Please specify the kind of uncertainties. They can be internal or external, parametric or non-parametric, constant, characteristic or random. Determining their structures and amounts are challenging in the real time applications.

6    6) Autonomous systems should make decisions without requiring a certain model, instead learning through a trial and error process. These inttelligent approaches are essentaiily model free and adaptive which can eliminate the effects of the uncertainties. This paper should review recent and related papers since they are the new hot reserach topics in the corresponding literature. I would suggest these two recent and related papers: “Model Free Adaptive Control of the Under-Actuated Manipulators with the Chaotic Dynamics’’, . “Design and Comparison Base Analysis of Adaptive Estimator for Completely Unknown Linear Systems in the Presence of OE Noise and Constant Input Time Delay”. The first paper develops an intelligent adaptive model free approach for unstable, uncertain, underactuated and chaotic multi-input-multi-output system. The second paper develops a model free adaptive estimator (a kind of observer + controller) for unstable and uncertain systems.

      7) How are the input and intention of the leader (position, direction, target, internal variations) determined and provided for the observer to perform future state estimations?

      8) Please improve the graph theory by adding visual architectures? How are the nodes, connections decided for an unstructured and unknown task?

       9) Why is the first row of the Laplacian matrix zero? It is row rank reduced in the current form.

        10) Equation 2 essentially has no system dynamics. It is directly dirven by the control signal. How can it represent a dynamic, at least a third order UAV?

          11) What is hi(t) in Equation 4?

           12) What is the name of the distributed observer? What is its dimension? What are its inputs and outputs?

             13) How is the control law in Equation 9 derived?

             14) If the target is time varying, how can be the observation error in figures be zero. The UAVs and also their are nonlinear, so some error is expected.

 

Good luck with the improvements...

 

Author Response

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Round 2

Reviewer 2 Report

Thank you for making the suggested corrections. I have no more comments.

Author Response

Thank you very much for your contribution to this manuscript. All your comments are very important, and they have important guiding significance for my future scientific research work.

Reviewer 3 Report

I am not satisfied with the response to my review.

 

Author Response

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Reviewer 4 Report

The paper has been improved and can be accepted.

Author Response

Thank you very much for your comments to this manuscript. They have important guiding significance for my future scientific research work.