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Understanding the Study of Complex Systems

Question:

Discuss about the Dynamics of complex systems built coupled physical.

The main objective of control and dynamics of the complex system in mechanical engineering is to understand the complex system through the study of the model and boundaries in the complex system. The design of the machines are getting complex along with the functions of the machines. The main challenge is to increase the productivity in a cost effective way. The design of automatic control theory is developed by the use of control engineering. This kind of implementations sometimes overlaps with the application of the engineering of the other field like electrical engineering. The practice of control engineering is consists of the usage of sensors and the automation of the system. Systems, which are designed to perform without the human interactions are called automates system. The use and implementation of automated system are being developed in the controlling of the air craft and the transportation system. The design of the automated control system depends mainly in the derivation of various mathematical functions. The study of control theory is in the domain of mechanical engineering , however the use of control theory can be on various fields like biology, electrical, chemical and financial modeling. Though there the basic components and ideas of the controlling of the complex system is static, there are certain improvements and innovations are made based on the theories.

The main objective of the paper is to understand the relationship between the different components of a complex system. It contains the description of dynamic laws and behavior of specified components and sub components.


The paper analysis the working principals of a complex system by observing the work flow between the various components of the system and their dependency on the network functionality between them. The results from the findings are compared with the mathematical figures.

The paper has made it’s contribute by discussing to observe the complexity of the control system. Understanding the principals of the control system will help to modify and develop more effective systems.

The main objective of the paper is to identify the control over non- linear system by network structure. The robust control strategy of a system depends on the feedback structure of the network.

In order to find the effect of the network structure, a frame work is developed. The developed framework is applied on the control system having a complex network structure. The findings of the result determine the robustness of the system.

The complexity of the system may decrease the level of robustness of the system. The findings of the paper will help to understand the effect of the feedback strategy and will help to modify it accordingly in order to improve the robustness of the system.

The main objective of this paper is to observe the relationship between cost of the system and the complexity of the machine. It has been found that with the increase of complexity of the system the cost of machine is also increased.

Designing Automated Control Systems


The paper has described some industrial situations where the complexity of the machine has delivered more sophisticated services but it also increase the production cost. In this paper the other factors of increased cost has been searched and a comparative framework has been proposed to reduce the cost while using the complex machine

The proposed framework can reduce the cost of using the complex system in the industry. The adoption of the system can help the industry to get a better productivity within a reasonable cost.

In this paper the inter relation between the different layers of a complex system is discussed. The effects of the different layers on the other layers are also discussed in order to understand the system clearly.

In order to understand the inter relationship between a multi layer system, a simple model with individual agents is developed.  In order to understand the communication error, minimum and maximum power gain, and the coupling of the system and effects of size of the system the agent based stimulation id used.

The result indicates that at macro level the wave like behavior is caused by changes of individual agents in decision layer. The power consumption of the system depends on the network topologies used in the system.

One of the application of the use and control of the complex system is self driving cars also referred as intelligent vehicles. The paper has tried to propose a new and improved model that will improve the quality of control of the self driving cars.


In order to do the paper has proposed a frame work of the model where the car will send and receive the advanced feedback based on the situation. It also proposed the further improvement on the control system of the vehicle. In order to do this the paper has considered certain recommendations such as feedback control improvement and robust execution.

The automated vehicles are regarded as emerging innovation in the technological field. The automaton of the vehicles is depended on various domains of technology. The paper contributes by providing the on formation about the development of the design and the improvement of the control system of the vehicle.

The aero space structure contains complex mechanical stops and non linear in structure. The main aim of this paper is to investigate the complex system of aero space structure and experimentally observe the non linearity.

In order to observe and understand the structure advanced numerical simulations are used. Modal iteration and piecewise linear nonlinearities are discussed regarding this. In this context a full set model is build , which will cooperate the finding process.

The advancement of the technology requires the advanced model of aero space structure. This article has tried to identify the area of improvements in the structure by observing the detailed complexity of the whole model.

The paper has discussed about the background of supervisory control in case of discreet event system. The paper has also proposed a model regarding this.

In order to discuss the supervisory control the detailed discussion about the control architecture has done. In order to manage the state explosion symbolic computation and control architecture has been proposed.

Impact of Network Structure and Interrelations on Control System Robustness

Discreet system has certain impacts on the control engineering. Certain modification of the supervisory control can improve the discreet event system. It has certain application on the important system like designing the automotive system. It also helps to improve the productivity of the manufacturing system.

A non linear approach for the high performing flight control is discussed in this paper. The feature of multivariable flight control is discussed in this paper along with the mention of dynamic inversion.

In order to achieve the purpose of the paper, an extended state observer is used in order to perform the dynamic linearization. In order to get the preferable dynamic performance a feedback law is applied. Lyapunov   function is used in order to implement the process.

The paper has proposed a method that has significance the aerospace industry. The design of the aircraft is needed to be modified with the advanced control system. The paper can contribute a positive guidance regarding the design methodology.

The paper is concerned about the design of flight control system. The main purpose of the paper is to develop a sustainable flight control system which will serve its purpose and will also manage the control in unpredictable situation.

The methodology in order to achieve the goal is divided into two parts in the paper. The first step develops a primary flight control system that will satisfy all the requirements required for the flight control. The second step is considering the robustness of the flight control system.

The paper contributes useful information in developing a business aircraft using combination of various techniques. The successful implementation of this model can help to modify the control system of the aircraft.

The paper has proposed a model to make a self folding machine or robot. The robot can bold itself in 4 minutes without human interface. This demonstrates the transformation of electrical energy into mechanical function.

Three components are used to develop this robot. The machine is the combination of the application of complex geometry and the mechanics. It is an example autonomous and self controlled machine.

The construction of this complex object is useful resource for research in the field of robotics where the control of the complex system is required. The intelligent application of the design of the control system can help to develop more advanced  system and machine.

Conclusion

It can be concluded from the above articles study of control and dynamics of the control system can help to contribute in developing the automated system. The objective of the study on this field is advancement of technology. The aim also includes to provide  the society with better services in various fields like  innovations in transportation system, automates traffic control system, creating better control system in the air craft. In order to develop a knowledge about the complex system and machines the research of relevant principals and theories are needed to be developed. The further research is needed to be done in order to minimize the cost of control system and implementing the automation of the system. The findings from this research can also be used in developing the hybrid system. These systems can be used on various industries like manufacturing industry, power grid industry. There are various models, which are proposed in the above articles to improvise the control system of the complex machine. The recommendations of the further research can be made in order to compare the models depends on the various factors and choose the best model for the implementation. However, the articles mentioned has given a positive guideline for the approach.

Reference

Felton, S., Tolley, M., Demaine, E., Rus, D. and Wood, R., 2014. A method for building self-folding machines. Science, 345(6197), pp.644-646.

Gill, S.J., Lowenberg, M.H., Neild, S.A., Crespo, L.G., Krauskopf, B. and Puyou, G., 2015. Nonlinear dynamics of aircraft controller characteristics outside the standard flight envelope. Journal of Guidance, Control, and Dynamics, 38(12), pp.2301-2308.

Ghazi, G. and Botez, R.M., 2015, May. Lateral controller design for the Cessna citation X with handling qualities and robustness requirements. In 62nd CASI Aeronautics Conference and AGM, Montreal, Quebec, Canada.

Wonham, W.M., 2015. Supervisory control of discrete-event systems. Encyclopedia of Systems and Control, pp.1396-1404.

Renson, L., Noël, J.P. and Kerschen, G., 2015. Complex dynamics of a nonlinear aerospace structure: numerical continuation and normal modes. Nonlinear Dynamics, 79(2), pp.1293-1309.

Paden, B., ?áp, M., Yong, S.Z., Yershov, D. and Frazzoli, E., 2016. A survey of motion planning and control techniques for self-driving urban vehicles. IEEE Transactions on Intelligent Vehicles, 1(1), pp.33-55.

Kühnlenz, F. and Nardelli, P.H., 2016. Dynamics of complex systems built as coupled physical, communication and decision layers. PloS one, 11(1), p.e0145135.

Baeten, J.C., van de Mortel-Fronczak, J.M. and Rooda, J.E., 2016. Integration of supervisory control synthesis in model-based systems engineering. In Complex Systems (pp. 39-58). Springer, Cham.

Zañudo, J.G.T., Yang, G. and Albert, R., 2017. Structure-based control of complex networks with nonlinear dynamics. Proceedings of the National Academy of Sciences, 114(28), pp.7234-7239.

Liu, Y.Y. and Barabási, A.L., 2016. Control principles of complex systems. Reviews of Modern Physics, 88(3), p.035006.

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