• Steel and Composite Structures
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• v.13 no.4
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• pp.397-408
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• 2012

This paper describes the refined 3-D finite element (FE) modeling of composite frames composed of concrete-filled steel tubular (CFST) columns and steel-concrete composite beams based on the test to get a better understanding of the seismic behavior of the steel-concrete composite frames. A number of material nonlinearities and contact nonlinearities, as well as geometry nonlinearities, were taken into account. The elastoplastic behavior, as well as fracture and post-fracture behavior, of the FE models were in good agreement with those of the specimens. Besides, the beam and panel zone deformation of the analysis models fitted well with the corresponding deformation of the specimens. Parametric studies were conducted based on the refined finite elememt (FE) model. The analyzed parameters include slab width, slab thickness, shear connection degree and axial force ratio. The influences of these parameters, together with the presence of transverse beam, on the seismic behavior of the composite frame were studied. And some advices for the corresponding seismic design provisions of composite structures were proposed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.4
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• pp.335-341
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• 2010

To improve the performance of inner loop based on PD controller for a unmanned helicopter, neural networks are applied. The performance of PD controller designed on the response characteristics of error dynamics decreases because of uncertain nonlinearities of the system. The nonlinearities are decoupled to modified dynamic inversion model(MDIM) and are compensated by the neural networks. For the training of the neural networks, online weight adaptation laws which are derived from Lyapunov's direct method are used to guarantee the stability of the controller. The results of the improved performance of PD controller by neural networks are illustrated in the simulation of unmanned helicopter with nonlinearities,

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.399-405
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• 2007

This paper deals with the controller for a stable walking of a humanoid robot using genetic algorithm. A humanoid robot has instability during walking because it isn't fixed on the ground, and its nonlinearities of the joints increase its instability. If controller isn't robust, the robot may fall down at the ground during walking because of its nonlinearities. To solve this problem, robust controller is required to reduce the effect of nonlinearities and to gain the good tracking performance. In this paper, motion controller that is based on fuzzy-sliding mode controller is proposed. This controller can remove the effect of the saturation by limitation of the input voltage. It also includes compensator for reducing the effect of the nonlinearity by backlash and PI controller improving the tracking performance. In here, genetic algorithm is used for searching the optimal gains of the controller. From the given controller, a humanoid robot can moved more preciously. All the processes are investigated through simulations and are verified experimentally in a real joint system for a humanoid robot.

• Structural Engineering and Mechanics
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• v.54 no.2
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• pp.291-304
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• 2015

Compared with the identification of linear structures, it is more challenging to conduct identification of nonlinear structure systems, especially when the locations of structural nonlinearities are not clear in structural systems. Moreover, it is highly desirable to develop methods of parametric identification using partial measurements of structural responses for practical application. To cope with these issues, an identification method is proposed in this paper for the detection and parametric identification of structural nonlinear restoring forces using only partial measurements of structural responses. First, an equivalent linear structural system is proposed for a nonlinear structure and the locations of structural nonlinearities are detected. Then, the parameters of structural nonlinear restoring forces at the locations of identified structural nonlinearities together with the linear part structural parameters are identified by the extended Kalman filter. The proposed method simplifies the identification of nonlinear structures. Numerical examples of the identification of two nonlinear multi-story shear frames and a planar nonlinear truss with different nonlinear models and locations are used to validate the proposed method.

• Wind and Structures
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• v.12 no.2
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• pp.103-120
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• 2009

Articulated tower platforms due to its compliant nature are more susceptible to the dynamic effects of wind than conventional fixed platforms. Dynamic response analysis of a double hinged articulated tower excited by low frequency wind forces with random waves is presented in this paper. The exposed super structure of the platform, housing the drilling and production facilities is subjected to mean and fluctuating wind loads, while the submerged portion is acted upon by wind driven waves. The fluctuating component of the wind velocity is modeled by Emil Simiu's spectrum, while the sea state is characterized by Pierson-Moskowitz spectrum. Nonlinearities in the system due to drag force, added mass, variable submergence and instantaneous tower orientation are considered in the analysis. To account for these nonlinearities, an implicit time integration scheme (Newmark's-${\beta}$) has been employed which solves the equation of motion in an iterative fashion and response time histories are obtained. The power spectra obtained from random response time histories show the significance of low frequency responses.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.329-337
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• 2000

This study describes a pressure tracking control of hydroforming process which is used for precision forming of sheet metals. The hydroforming operation is performed in the high-pressure chamber strictly controlled by pressure control valve and by the upward motion of a punch moving at a constant speed, The pressure tracking control is very difficult to design and often does not guarantee satisfactory performances be-cause of the punch motion and the nonlinearities and uncertainties of the hydraulic components. To account for these nonlinearities and uncertainties of the process and iterative learning controller is proposed using Cerebellar Model Arithmetic Computer (CMAC). The experimental results show that the proposed learning control is superior to any fixed gain controller in the sense that it enables the system to do the same work more effectively as the number of operation increases. In addition reardless of the uncertainties and nonlinearities of the form-ing process dynamics it can be effectively applied with little a priori knowledge abuot the process.

• Journal of applied mathematics & informatics
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• v.29 no.3_4
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• pp.921-936
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• 2011

In this paper, our main purpose is to establish the existence of weak solutions of a weak solutions of a class of p-q-Laplacian system involving concave-convex nonlinearities: $$\{\array{-{\Delta}_pu-{\Delta}_qu={\lambda}V(x)|u|^{r-2}u+\frac{2{\alpha}}{\alpha+\beta}|u|^{\alpha-2}u|v|^{\beta},\;x{\in}{\Omega}\\-{\Delta}p^v-{\Delta}q^v={\theta}V(x)|v|^{r-2}v+\frac{2\beta}{\alpha+\beta}|u|^{\alpha}|v|^{\beta-2}v,\;x{\in}{\Omega}\\u=v=0,\;x{\in}{\partial}{\Omega}}$$ where ${\Omega}$ is a bounded domain in $R^N$, ${\lambda}$, ${\theta}$ > 0, and 1 < ${\alpha}$, ${\beta}$, ${\alpha}+{\beta}=p^*=\frac{N_p}{N_{-p}}$ is the critical Sobolev exponent, ${\Delta}_su=div(|{\nabla}u|^{s-2}{\nabla}u)$ is the s-Laplacian of u. when 1 < r < q < p < N, we prove that there exist infinitely many weak solutions. We also obtain some results for the case 1 < q < p < r < $p^*$. The existence results of solutions are obtained by variational methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.215-221
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• 2006

This paper is concerned with the control of multiple nonlinearities included in a humanoid robot system. A humanoid robot has some problems such as the structural instability, which leads to consider the control of multiple nonlinearities caused by driver parts as well as gear reducer. Saturation and backlash are typical examples of nonlinearities in the system. The conventional algorithms of backlash control were fuzzy algorithm, disturbance observer and neural network, etc. However, it is not easy to control the system by employing only single algorithm since the system usually includes multiple nonlinearities. In this paper, a switching Pill is considered for a control of saturation and a dual feedback algorithm is proposed for a backlash control. To implement the above algorithms, the system identification is firstly performed for the minimization of the difference between the results of simulation and experiment, and then the switching Pill gains are determined using genetic algorithm with some heuristic approach. The performance of the switching Pill controller for saturation and the dual feedback for backlash control is investigated through the simulation. Finally, it is shown that the implemented control system has good results and can be applied to the real humanoid robot system ISHURO.

• Proceedings of the Optical Society of Korea Conference
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• 1997.08a
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• pp.8-8
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• 1997

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.2
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• pp.125-135
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• 2008

Backlash in the actuator is one of the most important nonlinearities that limit the performance of speed and position control of mechanical systems. In this paper, we propose disturbance observers in order to estimate the effect of nonlinearities and cancel them subsequently. As a result the disturbance observers make the nonlinear system behave linearly. And finally we show that the disturbance observers guarantee the system robustness and the performance to reject the effect of backlash in the face of parameter uncertainties.