• Structural Engineering and Mechanics
• /
• v.51 no.3
• /
• pp.519-530
• /
• 2014

This paper attempts to investigate the nonlinear dynamic analysis of strong nonlinear problems by proposing a new analytical method called Hamiltonian Approach (HA). Two different cases are studied to show the accuracy and efficiency of the method. This approach prepares us to obtain the nonlinear frequency of the nonlinear systems with the first order of the solution with a high accuracy. Finally, to verify the results we present some comparisons between the results of Hamiltonian approach and numerical solutions using Runge-Kutta's [RK] algorithm. This approach has a powerful concept and the high accuracy, so it can be apply to any conservative nonlinear problems without any limitations.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1996.10a
• /
• pp.310-312
• /
• 1996

In this paper, we propose a design method for nonlinear SISO system using Takagi-Sugeno fuzzy model and Genetic Algorithm. Our method can reduce the number of design parameters and has advantage of small search space of Genetic Algorithm. The proposed nonlinear controller, which can be implemented by fuzzy controller and simple nonlinear controller, cancels the original nonlinear dynamics and gives the optimal nonlinear dynamics. We illustrated the performance of the proposed controller by simple simulation example.

• Journal of Navigation and Port Research
• /
• v.33 no.9
• /
• pp.629-634
• /
• 2009

Vessels stability problems need to resolve the nonlinear mathematical models of rolling motion. For nonlinear systems subjected to random excitations, there are very few special cases can obtain the exact solutions. In this paper, the specific differential equations of rolling motion for intact ship considering the restoring and damping moment have researched firstly. Then the partial stochastic linearization method is applied to study the response statistics of nonlinear ship rolling motion in beam seas. The ship rolling nonlinear stochastic differential equation is then solved approximately by keeping the equivalent damping coefficient as a parameter and nonlinear response of the ship is determined in the frequency domain by a linear analysis method finally.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.4 no.3
• /
• pp.259-265
• /
• 2004

In this study, a hybrid genetic algorithm merged with simulated annealing is presented to solve nonlinear channel blind equalization problems. The equalization of nonlinear channels is more complicated one, but it is of more practical use in real world environments. The proposed hybrid genetic algorithm with simulated annealing is used to estimate the output states of nonlinear channel, based on the Bayesian likelihood fitness function, instead of the channel parameters. By using the desired channel states derived from these estimated output states of the nonlinear channel, the Bayesian equalizer is implemented to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a conventional genetic algorithm(GA) and a simplex GA. In particular, we observe a relatively high accuracy and fast convergence of the method.

• Journal of Institute of Control, Robotics and Systems
• /
• v.8 no.11
• /
• pp.984-990
• /
• 2002

We propose a new type of nonlinear fixed interval smoother to which an existing nonlinear smoother is modified. The nonlinear smoother is derived from two-filter formulas. For the backward filter. the propagation and the update equation of error states are derived. In particular, the modified update equation of the backward filter uses the estimated error terms from the forward filter. Data fusion algorithm, which combines the forward filter result and the backward filter result, is altered into the compatible form with the new type of the backward filter. The proposed algorithm is more efficient than the existing one because propagation in backward filter is very simple from the implementation point of view. We apply the proposed nonlinear smoothing algorithm to off-line navigation system and show the proposed algorithm estimates position, and altitude fairly well through the computer simulation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.10a
• /
• pp.346-352
• /
• 1998

In this paper, we give some geometric condition for a stochastic nonlinear system and we propose a control method for a stochastic nonlinear system using neural networks. Since a competitive learning neural networks has been developed based on the stochastic approximation method, it is regarded as a stochastic recursive filter algorithm. In addition, we provide a filtering and control condition for a stochastic nonlinear system, called perfect filtering condition, in a viewpoint of stochastic geometry. The stochastic nonlinear system satisfying the perfect filtering condition is decoupled with a deterministic part and purely semi martingale part. Hence, the above system can be controlled by conventional control laws and various intelligent control laws. Computer simulation shows that the stochastic nonlinear system satisfying the perfect filtering condition is controllable. and the proposed neural controller is more efficient than the conventional LQG controller and the canoni al LQ-Neural controller.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2009.10a
• /
• pp.239-240
• /
• 2009

Vessels stability problems need to resolve the nonlinear mathematical models of rolling motion. For nonlinear systems subjected to random excitations, there are very few special cases can obtain the exact solutions. In this paper, the specific differential equations of rolling motion for intact ship considering the restoring and damping moment have researched firstly. Then the partial stochastic linearization method is applied to study the response statistics of nonlinear ship rolling motion in beam seas. The ship rolling nonlinear stochastic differential equation is then solved approximately by keeping the equivalent damping coefficient as a parameter and nonlinear response of the ship is determined in the frequency domain by a linear analysis method finally.

• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.1134-1136
• /
• 1996

A necessary and suficient conditions is proposed for feedback linearizable SISO systems with unknown constant parameters. It is shown that the systems which satisfy the proposed conditions can be transformed into a controllable linear system with unknown parameter and it can be stabilized using the nonlinear feedback linearizing controller. We also present the analysis and implementation of a nonlinear feedback linearizing control for an Electro-Magnetic Suspension (EMS) system. We show that an EMS system is nonlinear feedback linearizable and satisfies the proposed conditions, and hence that the proposed nonlinear feedback controller for an EMS system is robust against mass parameter perturbation and force disturbance.

• Proceedings of the KOSOMBE Conference
• /
• v.1993 no.11
• /
• pp.163-166
• /
• 1993

It has been shown that some of physiological systems have nonlinear dynamics. The evidences of these nonlinear behaviors make us analyze physiological systems in the new viewpoint. And, nonlinear dynamics can be represented by chaotic behaviors, which is studied by several methods - correlation dimension, return map, power spectrum analysis, etc. This study is on the analysis of nonlinear characteristics of ECG. Data have been acquired from the 20 children (10 - 13 years old). and 30 students (20 -24 years old). We have calculated parameters HR, PR, VAT, TD, TRD from data. and estimated correlation dimension, return map, power spectrum. Results show the nonlinear characteristics of ECG.

• International Journal of Control, Automation, and Systems
• /
• v.3 no.spc2
• /
• pp.296-301
• /
• 2005

As a new control strategy, the Nonlinear PID (NLPID) controller has been introduced successfully in power systems. The controller is free of planting model groundwork during the design procedure and is therefore able to be achieved quite simply. In this paper, a nonlinear PID controller used for a superconducting magnetic energy storage (SMES) unit connected to a power system is proposed. The purpose of designing such a controller is to improve the stability of the power system in a relatively wide operation range. The design procedure takes into account the active and reactive power cooperative control scheme as well as the simple structure so as to be more apt to practical utilization. Simulation is carried out to investigate the performance of the proposed controller in a high order nonlinear power system model under the. MATLAB environment. The results show satisfactory performance and good robustness of the controller. The feasibility of the controller is testified as well.