Structural and magnetic properties of nanocomposites based on nanostructured polyaniline and titania nanotubes

Nanocomposites consisting of self-assembled polyaniline (PANI) nanostructures and titania nanotubes (TiO₂-NT) were synthesized by the oxidative polymerization of aniline with ammonium peroxydisulfate in an aqueous dispersion of TiO₂-NT (outer diameter ~10 nm), without added acid. The influence of initial mole ratio of aniline to TiO₂ (80, 20, and 5) on the morphology, electrical conductivity, molecular structure, crystallinity, and magnetic properties of synthesized PANI/TiO₂ nanocomposites was studied. Transmission electron microscopy, Raman spectroscopy, and X-ray powder diffraction proved that the shape and structure of TiO₂-NT in the final nanocomposites were preserved. The shape of PANI nanostructures formed in the nanocomposites was influenced by the initial aniline/TiO₂-NT mole ratio. Nanotubes and nanorods are predominant PANI nanostructures in the nanocomposite prepared with the highest aniline/TiO₂ mol ratio of 80. The decrease of aniline/TiO₂ molar ratio induced more pronounced formation of nanorod network. The electrical conductivity of PANI/TiO₂ nanocomposites was in the range (1.3–2.4) × 10^?3 S cm^?1. The nanocomposites exhibit weak ferromagnetic behavior. Approximately order of magnitude lower values of coercive field and remanent magnetization were obtained for nanocomposite samples in comparison to pure PANI.     

Study of Dependability Evaluation for Multi‐hierarchical Systems Based on Max–Min Composition

This article presents the model for calculating the performance of dependability for complex technical systems. According to ISO‐IEC 300, dependability is an overall indicator for the quality of service and considers simultaneously reliability, maintainability, and maintenance support. For a proper understanding of the quality of service for any technical system, it is important to define dependability performance at the level of single component as well as at the upper levels—levels of subsystems and entire system. As dependability indicators (reliability, maintainability, and maintenance support) have been defined as linguistic variables, the fuzzy max–min composition has been used for the dependability determination and integration of its indicators. A procedure for the synthesis of single components dependability performance to upper levels in complex technical system is proposed. Max–min composition is again used as a tool for fuzzy synthesis because it enables obtaining the comprehensive and synergetic effect in a process of dependability evaluation. A practical engineering example (mechanical systems at bucket wheel excavator) has been used to demonstrate the proposed dependability synthesis model. Copyright © 2012 John Wiley & Sons, Ltd.     

Intelligent control of DC motor driven electromechanical fin actuator

In this paper modeling, simulation and control of an electromechanical actuator (EMA) system for aerofin control (AFC) with permanent magnet brush DC motor driven by a constant current driver are investigated. Nonlinear model of the EMA-AFC system has been developed and experimentally verified in actuator test bench. Model has been used as the starting point for PID position controller synthesis. To improve performances of the system, computational intelligence has been applied. Genetic PID optimization, genetic algorithm (GA) optimized fuzzy supervisory PID control and finally GA optimized nonlinear PID algorithm modification are proposed. Improved transient response and system behavior have also been experimentally validated.     

ℋ∞control in discrete time: state feedback control and norm bounds

?_∞norm bounds are useful in control design for disturbance rejection. For discrete systems, ?_∞norm optimizing controls can be characterized via the solution of the Discrete Algebraic Riccati Equation, (DARE). In addition, the DARE can be used to characterize controls that guarantee a uniform ?_∞norm bound. In this paper we identify an entire class of state feedback controls that guarantee an ?_∞norm bound, and provide new lower bounds for the ?_∞norm of stable systems, as well as for the best achievable ?_∞norm using state feedback controls.     

Partial exponential stability of semi-state systems

The general class of non-linear non-autonomous semi-state systems is considered from the viewpoint of stability of system motions. A theorem is proved giving necessary and sufficient conditions for partial exponential stability of arbitrary motion of these systems over finite or infinite time intervals.

The results are illustrated by the analysis of a non-linear electrical circuit.     

Robust real-time identification for a class of linear time-varying discrete systems

The problem of robust real-time identification of linear single-input-single-output dynamic systems with stochastically time-varying parameters is considered. Two ways of constructing robust algorithms that are able to handle outliers contaminating the gaussian observation disturbance samples are discussed. The first way is based on the general formulation of dynamic stochastic approximation schemes characterized by an adequate non-linear residual transformation, as well as the step-by-step optimization with respect to the weighting matrix of the algorithm. The second way is based on the formulation of one-step optimal estimates. Monte Carlo simulation results illustrate the discussion and show the efficiency of the proposed algorithms in the presence of outliers.     

Decision theoretic approach to real-time robust identification

A decision-theoretic approach to the estimation of unknown parameters from a linear discrete-time dynamic measurement model in the presence of disturbance uncertainty is considered. The unknown disturbance statistics are characterized by a certain class of distributions to which the real disturbance distribution is confined. Using game theory and the asymptotic estimation error covariance matrix as the criteria of how good an estimator is, the stochastic gradient-type algorithm is shown to be optimal in the min-max sense. Since the optimal solution is not tractable in practice, several suboptimal procedures are derived on the basis of suitable approximations. The convergence of the derived algorithms is established theoretically using the ordinary differential equation approach. Monte Carlo simulation results are presented for the quantitative performance evaluation of the algorithms.     

Exact determination of a Lyapunov function and the asymptotic stability domain

The problem of the necessary and sufficient conditions for an exact direct determination of both a Lyapunov function υ and the asymptotic stability domain D of the zero state is solved for time-invariant non-linear continuous-time systems with continuous unique motions. The conditions provide a complete algorithm for their simultaneous determination. They permit arbitrary selection of a positive definite function p for which D ⁺υ = ?p has a solution υ in order to generate a system Lyapunov function υ from D ⁺υ = ?p as for linear time-invariant systems. This expresses their substantial difference from Lyapunov's original results and their developments so far. The latter are expressed in terms of the existence of a system Lyapunov function but the former are not. The theorems of the paper establish a new insight into, and a methodology for, a study of Lyapunov stability properties and other qualitative features of nonlinear dynamic systems. Simple examples illustrate the theorems and the procedure for their application.     

Adaptive neuro fuzzy estimation of underactuated robotic gripper contact forces

It is known that robotic manipulators are highly nonlinear systems, and an accurate mathematical model is difficult to obtain, thus making it difficult tо analyze with conventional analytical methods. Here, a novel design of an adaptive neuro fuzzy inference system (ANFIS) for estimation contact forces of a new adaptive gripper is presented. Since the conventional analytical methods is a very challenging task, fuzzy logic based systems are considered as potential candidates for such an application. The main points of this paper are in explanation of kinetostatic analyzing of the new gripper structure using rigid body model with added compliance in every single joint. The experimental results can be used as training data for ANFIS network for estimation of gripping forces. An adaptive neuro-fuzzy network is used to approximate correlation between contact point locations and contact forces magnitudes. The simulation results presented in this paper show the effectiveness of the developed method. This system is capable to find any change in ratio of positions of the gripper contacts and magnitudes of the contact forces and thus indicates state of both finger phalanges.     

Specific Heat and Magnetocaloric Effect in Ho-Er-Co Solid Solutions

Specific heat measurements have been performed on polycrystalline HoCo₂, ErCo₂ and their solid solutions Ho_1?x Er _x Co₂ (0.1≤x≤0.5). These compounds were synthesized using high-purity rare-earth metals and cobalt. X-ray diffraction patterns taken at room temperature reveal that all compounds have the C15 cubic Laves phase structure. Heat capacity measurements have been performed in the temperature range of 2–300 K without magnetic field and in a magnetic field of 1 and 2 T. The magnetocaloric effect has been estimated in terms of isothermal magnetic entropy change for all solid solutions in magnetic fields up to 2 T. The effect of increasing Er amount in Ho_1?x Er _x Co₂ on the magnetic and magnetocaloric properties will be discussed.