Approximate Solutions of Nonlinear Pendulum with Fractional Damping

Because of many real problems are better characterized using fractional-order models, fractional calculus has recently become an intensively developing area of calculus not only among mathematicians but also among physicists and engineers as well. Fractional oscillator and fractional damped structure have attracted the attention of researchers in the field of mechanical and civil engineering [1-6]. This study is dedicated mainly a pendulum with fractional viscous damping. The mathematic model of pendulum is a cubic nonlinear equation governing the oscillations of systems having a single degree of freedom, via Riemann-Liouville fractional derivative. The method of multiple scales is performed to solve the equation by assigning the nonlinear and damping terms to the ε-order. Finally, the effects of the coefficient of a fractional damping term on the approximate solution are observed.

A geometric interpretation of maximal Lyapunov exponent based on deviation curvature

In this study, we discuss a relationship between the behavior of nonlinear dynamical systems and geometry of a system of second-order differential equations based on the Jacobi stability analysis. We consider how a maximal Lyapunov exponent is related to the geometric quantities. As a result of a theoretical investigation, the maximal Lyapunov exponent can be represented by a nonlinear connection and a deviation curvature. Thus, this means that the Jacobi stability given by the sign of the deviation curvature affects the change of the maximal Lyapunov exponent. Additionally, for an equation of nonlinear pendulum, we numerically confirm the theoretical results. We observe that a change of the maximal Lyapunov exponent is related to a change of an average deviation curvature. These results indicate that the deviation curvature and Jacobi stability are essential for considering the change of maximal Lyapunov exponent.

Elastic multi-blisters induced by geometric constraints

We study a prototypical system describing instability effects due to geometric constraints in the framework of nonlinear elasticity. By considering the equilibrium configurations of an elastic ring constrained inside a rigid circle with smaller radius, we analytically determine different possible shapes, reproducing well-known physical phenomena. As we show, both single- (with different complexity) and multi-blister configurations can be observed, but the lowest energy always corresponds to single-blister solutions. Important physical insight is attained through an analogy between the elastica and the dynamics of a nonlinear pendulum. A complete geometric characterization is attained, proving symmetry and other relevant properties. The effectiveness of the model is tested against a simple experiment by considering a thin polymer strip constrained in a rigid cylinder.

Neural Network based Direct MRAC Technique for Improving Tracking Performance for Nonlinear Pendulum System

This paper investigates the application of a neural network-based model reference adaptive intelligent controller for controlling the nonlinear systems. The idea is to control the plant by minimizing the tracking error between the desired reference model and the nonlinear system using conventional model reference adaptive controller by estimating the adaptation law using a multilayer backpropagation neural network. In the conventional model reference adaptive controller block, the controller is designed to realize the plant output converges to reference model output based on the plant, which is linear. This controller is effective for controlling the linear plant with unknown parameters. However, controlling of a nonlinear system using MRAC in real-time is difficult. The Neural Network is used to compensate the nonlinearity and disturbance of the nonlinear pendulum that is not taken into consideration in the conventional MRAC therefore, the proposed paper can significantly improve the system behaviour and force the system to behave the reference model and reduce the error between the model and the plant output. Adaptive law using Lyapunov stability criteria for updating the controller parameters online has been formulated. The behaviour of the proposed control scheme is verified by developing the simula-tion results for a simple pendulum. It is shown that the proposed neural network-based Direct MRAC has small rising time, steady-state error and settling time for a different disturbance than Conventional Direct MRAC adaptive control.

A Novel Robust Control of Uncertain Furuta Pendulum Based on a General Lyapunov Function

A novel robust approach for the obedience control of Furuta pendulum with uncertainty is proposed. The uncertainty considered in this paper is (possibly fast) time-varying and bounded, which may exist in any stage of the pendulum subsystem. By the Lagrangian formulation of the nonlinear pendulum system, a robust control, based on a general Lyapunov function, is designed to render the Furuta pendulum a position obedience. As a consequence of the Lyapunov approach, the control design is not restricted to linearize the pendulum system. The system performance under the proposed control is guaranteed as uniform boundedness and uniform ultimate boundedness. The salient features of this new control are demonstrated both analytically and numerically. The experiment is conducted in the Furuta pendulum system to prove the validity and effectiveness of the control design.