Adaptive synchronization of chaos in permanent magnet synchronous motors based on passivity theory

An adaptive synchronization control method is proposed for chaotic permanent magnet synchronous motors based on the property of a passive system.We prove that the controller makes the synchronization error system between the driving and the response systems not only passive but also asymptotically stable.The simulation results show that the proposed method is effective and robust against uncertainties in the systemic parameters.     

Control and synchronization of a hyperchaotic system based on passive control

In this paper, a new hyperchaotic system is proposed, and the basic properties of this system are analyzed by means of the equilibrium point, a Poincar map, the bifurcation diagram, and the Lyapunov exponents. Based on the passivity theory, the controllers are designed to achieve the new hyperchaotic system globally, asymptotically stabilized at the equilibrium point, and also realize the synchronization between the two hyperchaotic systems under different initial values respectively. Finally, the numerical simulation results show that the proposed control and synchronization schemes are effective.     

An alternative approach to the linear theory of viscoelasticity and some characteristic effects being distinctive of the type of material

In the introduction some postulates on which the linear theory of viscoelasticity is based are recalled, and the postulate of passivity is substituted by a stronger postulate called detailed passivity.Next, a symmetric formulation of this theory is presented which is founded in a well-balanced way on the limiting properties of elasticity and viscosity. This leads to the introduction of the basic functions of creep compliance J ⁺(t) and stressing viscosity ⁺(t) associated to one another, whereas the basic functions retardation fluidity ⁺(t) and relaxation modulus G ⁺(t) emerge as their time derivatives. Correspondingly, four complex basic functions are defined as their Carson transforms.In addition to the proper retardation and relaxation terms, these basic functions contain the non-disappearing constants of either instantaneous compliance J ₀ or instantaneous viscosity ₀ and also of either ultimate fluidity or ultimate modulus G . Therefrom ensues a classification of linear viscoelastic materials into four types: instantaneous elasticity or viscosity is allowed to combine with ultimate viscosity or elasticity. The latter alternative, signifying fluidlike or solidlike materials, leads, of course, to a quite different behavior in many situations; however, remarkable distinctive features are associated to the first one as well.A few respective examples are outlined: 1) propagation of shear waves in a half-space with periodic and step-shaped excitation, 2) dissipation of work in a torsional vibration damper, and 3) shear flow between two parallel porous plates with injection and suction.Finally, materials with viscous initial behavior are defended against the notion that they be of no or almost no real significance.Delivered as a Plenary Lecture at the Fourth European Rheology Conference, Seville (Spain), 4–9 September 1994. The herein only outlined topics are taken from a recently pulished monograph (Geisekus, 1994) in which complete derivations of the results and more detailed discussions are given.Dedicated to Professor K. Walters on the occasion of his 60th birthday.     

Exponential passivity of neural networks with time-varying delay and uncertainty

In this Letter, delay-dependent exponential passivity condition for delayed neural networks is obtained. Then, the result is extended to two types of uncertainties. Two numerical examples are given to demonstrate the effectiveness of the proposed criteria.     

Durability of aluminum cooling system in electric power plants

The final step in gas turbine electric power production plants is the cooling of water after the turbine expansion. In some thermal plants, the temperature reduction of the recycling fluid is partially obtained by heat exchanging with the atmosphere by passing the fluid through huge aluminum heat exchangers. From the corrosion point of view, most critical is the starting step of the power plant, when the aluminum cooling system comes in contact with water for the first time and reaches a surface condition in dynamic equilibrium with the liquid. This paper describes a systematic study of aluminum surface evolution in the cooling system of an electric power plant during the first weeks of operation. Some aluminum samples were placed inside the cooling system in significant locations and removed after scheduled times. The surface conditions of the samples were characterized using surface analyses, electrochemical techniques and microscopic observations. At the same time, the chemical conditions of the recycling fluids were monitored. The obtained results describe the corrosion resistance of the aluminum surface as a function of the conditioning time, proving the growth of a partially protective layer able to produce corrosion decrease during the service time of the energy production plant. Copyright © 2009 John Wiley & Sons, Ltd.     

State estimation of memristor‐based recurrent neural networks with time‐varying delays based on passivity theory

This article deals with the state estimation problem of memristor‐based recurrent neural networks (MRNNs) with time‐varying delay based on passivity theory. The main purpose is to estimate the neuron states, through available output measurements such that for all admissible time delay, the dynamics of the estimation error is passive from the control input to the output error. Based on the Lyapunov–Krasovskii functional (LKF) involving proper triple integral terms, convex combination technique, and reciprocal convex technique, a delay‐dependent state estimation of MRNNs with time‐varying delay is established in terms of linear matrix inequalities (LMIs). The information about the neuron activation functions and lower bound of the time‐varying delays is fully used in the LKF. Then, the desired estimator gain matrix is accomplished by solving LMIs. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed theoretical results. © 2013 Wiley Periodicals, Inc. Complexity 19: 32–43, 2014     

基于无源化的细胞神经网络超混沌系统同步

根据细胞神经网络超混沌系统的特点，求得混沌驱动系统与响应系统之间的误差系统.基于该误差系统，提出了混沌系统的同步条件：使同步误差大范围渐近稳定，然后采用非线性系统的无源化方法设计了使误差系统大范围渐近稳定的反馈镇定器.四阶细胞神经网络超混沌系统的计算机仿真验证了该方法的有效性. 关键词： 混沌同步 误差系统 无源化 细胞神经网络超混沌系统     

Formation control for nonholonomic agents using passivity techniques

This paper studies the problem of the formation control for the multiple nonholonomic agents on a plane. A dynamic feedback linearization method is used to transform the dynamical model of each agent into two third-order integrator chains. A decentralized formation control law with the inter-agent damping .injection is derived. The asymptotical stability of the overall system is proven using the Lyapunov method. The simulation of the formation maneuver of a planar vehicle shows the effectiveness of the proposed method.