Narrow Results

The main contribution of this paper is to formulate the problem of optimal design of renewable wind/solar/biomass hybrid system for grid-independent applications in a region of Iran and to compare the genetic algorithm (GA) and performance of particle swarm optimization (PSO) on this optimization problem. There are many types of research on solar and wind hybrid energy systems, but research on solar/wind/biomass hybrid energy systems is rare. The biomass energy system can be used as a support and complementary system along with wind and solar energy systems. This paper studies the optimum design of a biomass/PV/wind energy system for independent applications. The objective of the optimum design problem is to minimize the total net present cost (TNPC) of the PV/wind/biomass system during its lifetime subject to some constraints by adjusting three decision variables, namely the swept area of wind turbines, the area of PV panels and the capacity of biogas generators. For this aim, two efficient metaheuristic techniques of GA and PSO are used to solve the optimization problem. Simulation results show that PV/biomass system is the most cost-effective one for supplying the demanded load. Moreover, PSO leads to better results than GA.

Bulk ZnO has traditionally been regarded as multifunctional materials for energy and optoelectronics applications. Recently, exploring this material at the nanoscale has been reported and seeking a proper substrate is highly desired. In this work, the structural and electronic properties of graphene like ZnO two-dimensional (2D) monolayer are investigated by first principles calculation based on density functional theory. The alignment of the valence and conduction bands of ZnO with the state of Cu substrate is analyzed. Particularly the attention has been focused on the establishment of a Schottky contact and interfacial charge transfer between the 2D ZnO monolayer and Cu substrate. It is predicted that the electronic charges are accumulated on the Zn and O atoms due to d–d hybridization between Cu and Zn. Our study reveals that the significant interaction between the ZnO and Cu can greatly modify the electronic properties of the ZnO and suggests potential applications in nanoelectronic devices.

This letter reports the finding of a chaotic attractor in a very simple three-dimensional autonomous hybrid system, which is obtained by applying a discontinuous feedback to a stable linear system. This attractor is different from the known chaotic attractors investigated in the literature and is globally attractive.

The problem of hybrid chaos synchronization is investigated, where a digital response subsystem is designed to synchronize with an analog drive subsystem. The approach taken is a new prediction-based digital redesign for a continuous-time observer embedded in the response via an optimal linearization approach of the nonlinear chaotic systems. Three typical but topologically quite different chaotic systems, Chua's circuit, Duffing oscillator, and Chen's system, are simulated thereby validating the novel design proposed in this paper.

This paper presents a time-delayed impulsive feedback approach to the problem of stabilization of periodic orbits in chaotic hybrid systems. The rigorous stability analysis of the proposed method is given. Using the time-delayed impulsive feedback method, we analyze the problem of detecting various periodic orbits in a special class of hybrid system, a switched arrival system, which is a prototype model of many manufacturing systems and computer systems where a large amount of work is processed in a unit time. We also consider the problem of stabilization of periodic orbits of chaotic piecewise affine systems, especially Chua's circuit, which is another important special class of hybrid systems.

The dynamics of differential-difference-algebraic equations is studied. The paper extends the study of the local bifurcations to transcritical and pitchfork bifurcation under certain nondegenerate conditions using Lyapunov–Schmidt reduction. Furthermore, an improved version of singularity induced bifurcation theorem is given in this paper.

This paper presents a neural network-based digital redesign approach for digital control of continuous-time chaotic systems with unknown structures and parameters. Important features of the method are that: (i) it generalizes the existing optimal linearization approach for the class of state-space models which are nonlinear in the state but linear in the input, to models which are nonlinear in both the state and the input; (ii) it develops a neural network-based universal optimal linear state-space model for unknown chaotic systems; (iii) it develops an anti-digital redesign approach for indirectly estimating an analog control law from a fast-rate digital control law without utilizing the analog models. The estimated analog control law is then converted to a slow-rate digital control law via the prediction-based digital redesign method; (iv) it develops a linear time-varying piecewise-constant low-gain tracker which can be implemented using microprocessors. Illustrative examples are presented to demonstrate the effectiveness of the proposed methodology.

A new network data transmission strategy was proposed in [Zhang & Chen, 2005], where the resulting nonlinear system was analyzed and the effectiveness of the transmission strategy was demonstrated via simulations. In this paper, we further generalize the results of Zhang and Chen [2005] in the following ways: (1) Construct first-return maps of the nonlinear systems formulated in [Zhang & Chen, 2005] and derive several existence conditions of periodic orbits and study their properties. (2) Formulate the new system as a hybrid system, which will ease the succeeding analysis. (3) Prove that this type of hybrid systems is not structurally stable based on phase transition which can be applied to higher-dimensional cases effortlessly. (4) Simulate a higher-dimensional model with emphasis on their rich dynamics. (5) Study a class of continuous-time hybrid systems as the counterparts of the discrete-time systems discussed above. (6) Propose new controller design methods based on this network data transmission strategy to improve the performance of each individual system and the whole network. We hope that this research and the problems posed here will rouse the interest of researchers in such fields as control, dynamical systems and numerical analysis.

In this paper, a scalar sign function-based digital design methodology is presented to develop a digital tracking controller for the continuous-time chaotic systems with absolute value state constraints. A scalar sign function, which is the counterpart of the well-known matrix sign function, is utilized to approximately represent the absolute value state term by a rational function. As a result, the original state constrained nonsmooth nonlinear system becomes a smooth nonlinear system having rational nonlinear terms. Then, an optimal linearization technique is applied to the afore-mentioned nonlinear system for finding an optimal linearization model, which has the exact dynamics of the original nonlinear system at any operating point of interest with minimal modeling error in the vicinity of the operating point on the trajectory. To overcome the effect of modeling errors and to quickly track the desired reference signals, a high-gain optimal analog tracker is designed for the obtained linear model. For practical implementation of the high-gain analog tracker, the prediction-based digital redesign technique is utilized to obtain a low-gain digital tracker for digital control of the sampled-data nonlinear system with constrained states. Chua's chaotic circuits are used to demonstrate the effectiveness of the proposed approach.

The bifurcation theory of snap-back repellers in hybrid dynamical systems is developed. Infinite sequences of bifurcations are shown to arise due to the creation of snap-back repellers in noninvertible maps. These are analogous to the cascades of bifurcations known to occur close to homoclinic tangencies for diffeomorphisms. The theoretical results are illustrated with reference to bifurcations in the normal form for border-collision bifurcations.

We try to stabilize unstable periodic orbits embedded in a given chaotic hybrid dynamical system by a perturbation of a threshold value. In conventional chaos control methods, a control input is designed by state-feedback, which is proportional to the difference between the target orbit and the current state, and it is applied to a specific system parameter or the state as a small perturbation. During a transition state, the control system consumes a certain control energy given by the integration of such perturbations. In our method, we change the threshold value dynamically to control the chaotic orbit. Unlike the OGY method and the delayed feedback control, no actual control input is added into the system. The state-feedback is utilized only to determine the dynamic threshold value, thus the orbit starting from the current threshold value reaches the next controlled threshold value without any control energy. We obtain the variation of the threshold value from the composite Poincaré map, and the controller is designed by the linear feedback theory with this variation. We demonstrate this method in simple hybrid chaotic systems and show its control performances by evaluating basins of attraction.

This paper studies the dynamics of the hepatitis B virus (HBV) model and the therapy regimens of HBV disease. First, we propose a new mathematical model of HBV with drug resistance, and then analyze its qualitative and dynamical properties. Combining the clinical data and theoretical analysis, we demonstrate that our model is biologically plausible and also computationally viable. Second, we demonstrate that the intermittent antiviral therapy regimen is one of the possible strategies to treat this kind of complex disease. There are two main advantages of this regimen, i.e. it not only may delay the development of drug resistance, but also may reduce the duration of on-treatment time compared with the long-term continuous medication. Moreover, such an intermittent antiviral therapy can reduce the adverse side effects. Our theoretical model and computational results provide qualitative insight into the progression of HBV, and also a possible new therapy for HBV disease.

Digital stabilization of unstable equilibria of linear systems may lead to small amplitude stochastic-like oscillations. We show that these vibrations can be related to a deterministic chaotic dynamics induced by sampling and quantization. A detailed analytical proof of chaos is presented for the case of a PD controlled oscillator: it is shown that there exists a finite attracting domain in the phase-space, the largest Lyapunov exponent is positive and the existence of a Smale horseshoe is also pointed out. The corresponding two-dimensional micro-chaos map is a multi-baker map, i.e. it consists of a finite series of baker’s maps.

A detailed mathematical analysis of the two-dimensional hybrid model for the lateral dynamics of walking-like mechanical systems (the so-called hybrid inverted pendulum) is presented in this article. The chaotic behavior, when being externally harmonically perturbed, is demonstrated. Two rather exceptional features are analyzed. Firstly, the unperturbed undamped hybrid inverted pendulum behaves inside a certain stability region periodically and its respective frequencies range from zero (close to the boundary of that stability region) to infinity (close to its double support equilibrium). Secondly, the constant lateral forcing less than a certain threshold does not affect the periodic behavior of the hybrid inverted pendulum and preserves its equilibrium at the origin. The latter is due to the hybrid nature of the equilibrium at the origin, which exists only in the Filippov sense. It is actually a trivial example of the so-called pseudo-equilibrium [Kuznetsov et al., 2003]. Nevertheless, such an observation holds only for constant external forcing and even arbitrary small time-varying external forcing may destabilize the origin. As a matter of fact, one can observe many, possibly even infinitely many, distinct chaotic attractors for a single system when the forcing amplitude does not exceed the mentioned threshold. Moreover, some general properties of the hybrid inverted pendulum are characterized through its topological equivalence to the classical pendulum. Extensive numerical experiments demonstrate the chaotic behavior of the harmonically perturbed hybrid inverted pendulum.

Hybrid systems combine both continuous and discrete behaviors, which occur frequently in safety-critical applications in various domains including Internet-of-Things (IoT) and Cyber-Physical Systems (CPS) applications such as health care, transportation, and robotics. For safe and reliable information society with IoT and CPS technologies, it is important to establish a way to specify and verify hybrid systems formally. Formal descriptions of hybrid systems may help us to verify desired properties of a given system formally with computer supports. We propose a way to describe a formal specification of a given multitask hybrid system as an observational transition system (OTS) in CafeOBJ algebraic specification language. OTSs are models where systems behaviors are described through observations. CafeOBJ supports specification execution based on a rewrite theory. We verify that OTS/CafeOBJ specifications of hybrid systems satisfy desired property by the proof score method based on equational reasoning implemented in CafeOBJ interpreter. In this paper, we specify a signal control system with an arbitrary number of vehicles by our proposed method, and verify the system satisfies a safety property by the proof score method.

Probabilistic behavior is omnipresent in computer-controlled systems, in particular, so-called safety-critical hybrid systems, due to various reasons, like uncertain environments or fundamental properties of nature. In this paper, we extend the existing hybrid process algebra ACP${}_{hs}^{srt}$ with probability without sacrificing the nondeterministic choice operator. The existing approximate probabilistic bisimulation relation is fragile and not robust in the sense of being dependent on the deviation range of the transition probability. To overcome this defect, a novel approximate probabilistic bisimulation is proposed which is inspired by the idea of Probably Approximately Correct (PAC) by relaxing the constraints of transition probability deviation range. Traditional temporal logics, even probabilistic temporal logics, are expressive enough, but they are limited to producing only true or false responses, as they are still logics and not suitable for performance evaluation. To settle this problem, we present a new performance evaluation language that expands quantitative analysis from the value range of $\{0,1\}$ to real number to reason over probabilistic systems. After that, the corresponding algorithms for performance evaluation are given. Finally, an industrial example is given to demonstrate the effectiveness of our method.

We consider a model for bioremediation of a pollutant by bacteria in a well-stirred bioreactor. A key feature is the inclusion of dormancy for bacteria, which occurs when the critical nutrient level falls below a critical threshold. This feature gives a discrete component to the system due to the change in dynamics (governed by a system of ordinary differential equations between transitions) at switches to/from dormancy. After setting the problem in an appropriate state space, the control is the rate of injection of the critical nutrient and the functional to be minimized is the pollutant level at the final time and the amount of nutrient added. The existence of an optimal control and a discussion of the transitions between dormant and active states are given.

There have been a large number of systems that integrate logic and objects (frames or classes) for knowledge representation and reasoning. Most of those systems give pre-eminence to logic and their objects lack the structure of frames. These choices imply a number of disadvantages, as the inability to represent exceptions and perform default reasoning, and the reduction in the naturalness of representation. In this paper, aspects of knowledge representation and reasoning in SILO, a system integrating logic in objects, are presented. SILO gives pre-eminence to objects. A SILO object comprises elements from both frames and classes. A kind of many-sorted logic is used to express object internal knowledge. Message passing, alongside inheritance, plays a significant role in the reasoning process. Control knowledge, concerning both deduction and inheritance. is separately and explicitly represented via definitions of certain functions, called meta-functions.

Theory is developed for an epidemic model of a seasonally-spreading vector-borne disease using a hybrid system framework. Applicable to diseases spread by mosquitoes (e.g., chikungunya and Zika virus via Aedes albopictus), seasonal variations in transmission are modeled using switching parameters to represent term-time forcing. The vector agent is assumed to exhibit a period of incubation upon infection, modeled using a distribution. Three hybrid control strategies are analyzed in detail: switching cohort immunization, pulse vaccination at pre-specified times, and state-dependent pulse vaccination. Methods from switched systems theory are used to derive threshold disease eradication conditions involving the model parameters; convergence of solutions to a disease-free set or periodic solution is shown. A comprehensive analysis is performed to compare and contrast the different control schemes.

Smoking has many harmful effects due to its toxic chemicals, which cause serious diseases. Our major interest in this research is to formulate a spatiotemporal mathematical model that predicts the evolution of smoking in society using a mathematical model that includes the large mobility of individuals. Indeed, we are concerned to study the global asymptotic stability of the unique positive steady state related to this model. The principal objective of this paper is to show that the smoking has no threshold dynamics as it has been shown for a large sample of epidemic models, and the consumption of cigarettes is always persistent, and based on the assumption of the parameters that verify the Lipschitz condition. We proved that the investigated model is always persistent and the unique positive equilibrium state is always globally stable. The mathematical finding is supported numerically using numerical simulations.