State and input simultaneous estimation for a class of nonlinear systems

This paper addresses the problem of estimating simultaneously the state and input of a class of nonlinear systems. Here, the systems nonlinear part comprises a Lipschitz nonlinear function with respect to the state and input, and a state-dependent unknown function including additive disturbance as well as uncertain/nonlinear/time-varying terms. Upon satisfying some conditions, the observer design problem can be solved via a Riccati inequality or a LMI-based technique with asymptotic estimation guaranteed. A numerical example is included for illustration.

Nonlinear dynamic modeling of ionic polymer conductive network composite actuators using rigid finite element method

Ionic polymer conductive network composite (IPCNC) actuators are a class of electroactive polymer composites that exhibit some interesting electromechanical characteristics such as low voltage actuation, large displacements, and benefit from low density and elastic modulus. Thus, these emerging materials have potential applications in biomimetic and biomedical devices. Whereas significant efforts have been directed toward the development of IPMC actuators, the establishment of a proper mathematical model that could effectively predict the actuators' dynamic behavior is still a key challenge. This paper presents development of an effective modeling strategy for dynamic analysis of IPCNC actuators undergoing large bending deformations. The proposed model is composed of two parts, namely electrical and mechanical dynamic models. The electrical model describes the actuator as a resistive-capacitive (RC) transmission line, whereas the mechanical model describes the actuator as a system of rigid links connected by spring-damping elements. The proposed modeling approach is validated by experimental data, and the results are discussed. © 2014 Elsevier B.V. All rights reserved.

Robust nonlinear distributed controller design for active and reactive power sharing in islanded microgrids

This paper presents a robust nonlinear distributed controller design for islanded operation of microgrids in order to maintain active and reactive power balance. In this paper, microgrids are considered as inverter-dominated networks integrated with renewable energy sources (RESs) and battery energy storage systems (BESSs), where solar photovoltaic generators act as RESs and plug-in hybrid electric vehicles as BESSs to supply power into the grid. The proposed controller is designed by using partial feedback linearization and the robustness of this control scheme is ensured by considering structured uncertainties within the RESs and BESSs. An approach for modeling the uncertainties through the satisfaction of matching conditions is also provided in this paper. The proposed distributed control scheme requires information from local and neighboring generators to communicate with each other and the communication among RESs, BESSs, and control centers is developed by using the concept of the graph theory. Finally, the performance of the proposed robust controller is demonstrated on a test microgrid and simulation results indicate the superiority of the proposed scheme under different operating conditions as compared to a linear-quadratic-regulator-based controller.

Observations on the nonlinear unloading behavior of advanced high strength steels

The unloading behavior was compared for three different steel grades: a dual-phase steel, a transformation-induced plasticity steel, and a twinning-induced plasticity steel. Steels that harden by phase transformation or deformation twinning exhibited a smaller component of microplastic strain during unloading and a smaller reduction in the chord modulus compared to the conventional hardening steel. As a result, unloading is closer to pure elastic unloading when the TRIP effect or TWIP effect is active.

Robust nonlinear controller design for three-phase grid-connected photovoltaic systems under structured uncertainties

This paper presents a robust nonlinear controller design for a three-phase grid-connected photovoltaic (PV) system to control the current injected into the grid and the dc-link voltage for extracting maximum power from PV units. The controller is designed based on the partial feedback linearization approach, and the robustness of the proposed control scheme is ensured by considering structured uncertainties within the PV system model. An approach for modeling the uncertainties through the satisfaction of matching conditions is provided. The superiority of the proposed robust controller is demonstrated on a test system through simulation results under different system contingencies along with changes in atmospheric conditions. From the simulation results, it is evident that the robust controller provides excellent performance under various operating conditions. © 2014 IEEE.

Global finite-time stabilisation for a class of stochastic nonlinear systems by output feedback

In this paper, the problem of global finite-time stabilisation by output feedback is considered for a class of stochastic nonlinear systems. First, based on homogeneous systems theory and the adding a power integrator technique, a homogeneous reduced order observer and control law are constructed in a recursive manner for the nominal system. Then, the homogeneous domination approach is used to deal with the nonlinearities in drift and diffusion terms; it is shown that the proposed output-feedback control law can guarantee that the closed-loop system is global finite-time stable in probability. Finally, simulation examples are carried out to demonstrate the effectiveness of the proposed control scheme.

Some properties of finite-time stable stochastic nonlinear systems

In this paper we study some properties of finite-time stable stochastic nonlinear systems. We begin by showing several continuous dependence theorems of solutions on initial values under some conditions on the coefficients of stochastic systems. We then derive some regular properties of its stochastic settling time for a finite-time stable stochastic nonlinear system. We show continuity, positive definiteness and boundedness of the expected stochastic settling time under appropriate conditions. Finally, a Lyapunov function is constructed by making use of the expectation of the stochastic settling time, and the infinitesimal generator of the stochastic system defined on the Lyapunov function is also given, and hence resulting in a converse Lyapunov theorem of finite-time stochastic stability.

Optimisation of nonlinear motion cueing algorithm based on genetic algorithm

Motion cueing algorithms (MCAs) are playing a significant role in driving simulators, aiming to deliver the most accurate human sensation to the simulator drivers compared with a real vehicle driver, without exceeding the physical limitations of the simulator. This paper provides the optimisation design of an MCA for a vehicle simulator, in order to find the most suitable washout algorithm parameters, while respecting all motion platform physical limitations, and minimising human perception error between real and simulator driver. One of the main limitations of the classical washout filters is that it is attuned by the worst-case scenario tuning method. This is based on trial and error, and is effected by driving and programmers experience, making this the most significant obstacle to full motion platform utilisation. This leads to inflexibility of the structure, production of false cues and makes the resulting simulator fail to suit all circumstances. In addition, the classical method does not take minimisation of human perception error and physical constraints into account. Production of motion cues and the impact of different parameters of classical washout filters on motion cues remain inaccessible for designers for this reason. The aim of this paper is to provide an optimisation method for tuning the MCA parameters, based on nonlinear filtering and genetic algorithms. This is done by taking vestibular sensation error into account between real and simulated cases, as well as main dynamic limitations, tilt coordination and correlation coefficient. Three additional compensatory linear blocks are integrated into the MCA, to be tuned in order to modify the performance of the filters successfully. The proposed optimised MCA is implemented in MATLAB/Simulink software packages. The results generated using the proposed method show increased performance in terms of human sensation, reference shape tracking and exploiting the platform more efficiently without reaching the motion limitations.

Nonlinear large deformation dynamic analysis of electroactive polymer actuators

Electroactive polymers have attracted considerable attention in recent years due to their sensing and actuating properties which make them a material of choice for a wide range of applications including sensors, biomimetic robots, and biomedical micro devices. This paper presents an effective modeling strategy for nonlinear large deformation (small strains and moderate rotations) dynamic analysis of polymer actuators. Considering that the complicated electro-chemo-mechanical dynamics of these actuators is a drawback for their application in functional devices, establishing a mathematical model which can effectively predict the actuator's dynamic behavior can be of paramount importance. To effectively predict the actuator's dynamic behavior, a comprehensive mathematical model is proposed correlating the input voltage and the output bending displacement of polymer actuators. The proposed model, which is based on the rigid finite element (RFE) method, consists of two parts, namely electrical and mechanical models. The former is comprised of a ladder network of discrete resistive-capacitive components similar to the network used to model transmission lines, while the latter describes the actuator as a system of rigid links connected by spring-damping elements (sdes). Both electrical and mechanical components are validated through experimental results.

Stochastic stability of nonlinear discrete-time Markovian jump systems with time-varying delay and partially unknown transition rates

This paper is concerned with stochastic stability of a class of nonlinear discrete-time Markovian jump systems with interval time-varying delay and partially unknown transition probabilities. A new weighted summation inequality is first derived. We then employ the newly derived inequality to establish delay-dependent conditions which guarantee the stochastic stability of the system. These conditions are derived in terms of tractable matrix inequalities which can be computationally solved by various convex optimized algorithms. Numerical examples are provided to illustrate the effectiveness of the obtained results.

Stability analysis of a general family of nonlinear positive discrete time-delay systems

In this paper, we propose a new approach to analyse the stability of a general family of nonlinear positive discrete time-delay systems. First, we introduce a new class of nonlinear positive discrete time-delay systems, which generalises some existing discrete time-delay systems. Second, through a new technique that relies on the comparison and mathematical induction method, we establish explicit criteria for stability and instability of the systems. Three numerical examples are given to illustrate the feasibility of the obtained results.

Analytical thermal study on nonlinear fundamental heat transfer cases using a novel computational technique

In this paper a novel computational technique called Parameterized Perturbation Method (PPM) is used to obtain the solutions of nonlinear fundamental heat conduction equations. Three well known problems in the area of heat transfer are addressed to be solved. An analytical investigation is carried out for: (a) the temperature distribution in a fin with a temperature-dependent thermal conductivity, (b) the cooling of the lumped system with variable specific heat, and (c) the temperature distribution of a convective-radiative fin. The validity of the results of PPM solution was verified via comparison with numerical results obtained using a fourth order Runge-Kutta method. These comparisons revealed that PPM is a powerful approach for solving these problems. Also, the results showed that the main attributions of this method are very straightforward calculations and low computational burden compared to previous analytical and numerical approaches.

Nonlinear DSTATCOM controller design for distribution network with distributed generation to enhance voltage stability

This paper presents a nonlinear controller design for a DSTATCOM connected to a distribution network with distributed generation (DG) to regulate the line voltage by providing reactive power compensation.The controller is designed based on the partial feedback linearization which transforms the nonlinear system into a reduced-order linear system and an autonomous system whose dynamics are known as internal dynamics of the system. This paper also investigates the stability of internal dynamics of a DSTATCOM as it is a basic requirement to design partial feedback linearizing controllers. The performance of the proposed controller is evaluated in terms reactive power compensation to enhance the voltage stability of distribution with DG.