Non-linear dynamics and control of an automotive suspension system based on local and global bifurcation analysis

2017 ◽  
Vol 13 (4) ◽  
pp. 340 ◽  
Author(s):  
Yeou Feng Lue ◽  
Shun Chang
Author(s):  
Ginestra Bianconi

This chapter is entirely devoted to characterizing non-linear dynamics on multilayer networks. Special attention is given to recent results on the stability of synchronization that extend the Master Stability Function approach to the multilayer networks scenario. Discontinous synchronization transitions on multiplex networks recently reported in the literature are also discussed, and their application discussed in the context of brain networks. This chapter also presents an overview of the major results regarding pattern formation in multilayer networks, and the proposed characterization of multivariate time series using multiplex visibility graphs. Finally, the chapter discusses several approaches for multiplex network control where the dynamical state of a multiplex network needs to be controlled by eternal signals placed on replica nodes satisfying some structural constraints.


Author(s):  
A. S. White

This chapter examines the established Systems Dynamics (SD) methods applied to software projects in order to simplify them. These methods are highly non-linear and contain large numbers of variables and built-in decisions. A SIMULINK version of an SD model is used here and conclusions are made with respect to the initial main controlling factors, compared to a NASA project. Control System methods are used to evaluate the critical features of the SD models. The eigenvalues of the linearised system indicate that the important factors are the hiring delay time, the assimilation time, and the employment time. This illustrates how the initial state of the system is at best neutrally stable with control only being achieved with complex non-linear decisions. The purpose is to compare the simplest SD and control models available required for “good” simulation of project behaviour with the Abdel-Hamid software project model. These models give clues to the decision structures that are necessary for good agreement with reality. The final simplified model, with five states, is a good match for the prime states of the Abdel-Hamid model, the NASA data, and compares favourably to the Ruiz model. The linear control system model has a much simpler structure, with the same limitations. Both the simple SD and control models are more suited to preliminary estimates of project performance.


Author(s):  
Susan Basile ◽  
Xiaopeng Zhao ◽  
Mingjun Zhang

Electroporation has become an important tool for drug delivery such as gene therapy. The technique uses electric pulses to create transient pores in the cell membrane. To ensure proper uptake of targeted molecules, it is essential to create sufficiently large pores, which remain open long enough. In this work, we explore evolution of the pores using dynamical analysis and control of electroporation based on a simplified two-dimensional model. A detailed bifurcation analysis reveals the existence of saddle-node bifurcations, which induce hysteresis into the system dynamics. The bifurcation analysis also sheds light on the relation between the applied voltage and the pore radius. Based on the dynamics and bifurcation analysis, we design a feedback control algorithm that is able to achieve any desired pore size. Numerical examples demonstrate the control strategy is robust. The control algorithm will improve the operation of electroporation in drug delivery.


Author(s):  
W K Chung ◽  
H S Cho

Non-linear characteristics and uncertainty in manipulator dynamics caused by payload effects are major hurdles in controller design. To overcome such hurdles the authors have introduced an automatic balancing concept which has been proved to reduce the non-linear complexity in manipulator dynamics as well as to remove gravity loading. This paper examines the characteristic features of balanced manipulator dynamics in more detail and presents an efficient control algorithm suitable for the dynamics. Since the dynamics of a balanced manipulator are characterized by partially configuration-independent inertial properties, the present algorithm adopts two different control concepts ‘the computed torque control’ for the joint having coupled, configuration-dependent inertia and ‘an optimal constant feedback control’ for the joints having configuration-independent inertia. To evaluate the proposed control algorithm, simulation studies were made over a wide range of manipulator speeds and payloads. Based upon the simulation results, the efficiency of the controller is discussed in detail.


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