In this paper, the finite-time stabilization problem of chained form systems with parametric uncertainties is investigated. A novel switching control strategy is proposed for adaptive finite-time control design with the help of Lyapunov-based method and time-rescaling technique. With the proposed control law, the uncertain closed-loop system under consideration is finite-time stable within a given settling time. An illustrative example is also given to show the effectiveness of the proposed controller.
This paper is concerned with the finite-time synchronization problem for a class of cross-strict feedback underactuated hyperchaotic systems. Using finite-time control and backstepping control approaches, a new robust adaptive synchronization scheme is proposed to make the synchronization errors of the systems with parameter uncertainties zero in a finite time. Appropriate adaptive laws are derived to deal with the unknown parameters of the systems. The proposed method can be applied to a variety of chaotic systems which can be described by the so-called cross-strict feedback systems. Numerical simulations are given to demonstrate the efficiency of the proposed control scheme.
Adaptive Neuro-Fuzzy Inference System (ANFIS) with first order Sugeno consequent is used widely in modeling applications. Though it has the advantage of giving good modeling results in many cases, it is not capable of modeling highly non-linear systems with high accuracy. In this paper, an efficient way for using ANFIS with Sugeno second order consequents is presented. Better approximation capability of Sugeno second order consequents compared to lower order Sugeno consequents is shown. Subtractive clustering is used to determine the number and type of membership functions. A hybrid-learning algorithm that combines the gradient descent method and the least squares estimate is then used to update the parameters of the proposed Second Order Sugeno-ANFIS (SOS-ANFIS). Simulation of the proposed SOS-ANFIS for two examples shows better results than that of lower order Sugeno consequents. The proposed SOS-ANFIS shows better initial error, better convergence, quicker convergence and much better final error value.
In this paper, the problem of adaptive output feedback stabilization is investigated for a class of nonlinear systems with sensor uncertainty in measured output and a growth rate of polynomial-of-output multiplying an unknown constant in the nonlinear terms. By developing a dual-domination approach, an adaptive observer and an output feedback controller are designed to stabilize the nonlinear system by directly utilizing the measured output with uncertainty. Besides, two types of extension are made such that the proposed methods of adaptive output feedback stabilization can be applied for nonlinear systems with a large range of sensor uncertainty. Finally, numerical simulations are provided to illustrate the correctness of the theoretical results.
Females of the parasitoid wasp Dinocampus coccinellae are known to parasitise both male and female coccinellid hosts. It is suggested that female hosts provide more resources for developing wasp larvae because they tend to be larger than male hosts, and female coccinellids have a much greater food intake than males. Thus the wasp's lifetime reproductive success should be increased by ovipositing preferentially in female rather than male hosts when given a choice. Laboratory experiments, using Coccinella septempunctata as a host, show that such a preference does exist. Wasps preferentially oviposit in females, and this preference is not simply a result of the larger mean size of females compared to males. These results corroborate higher rates of prevalence in female compared to male hosts reported previously.
Dinocampus coccinellae females which eclose in mid-summer have the opportunity to oviposit in overwintered or in newly eclosed coccinellid hosts. Given the short further longevity of overwintered hosts, offspring fitness would be increased by ovipositing preferentially in young hosts. Laboratory choice tests show that female D. coccinellae do exhibit such a preference.
Diapause is a common dormancy strategy exhibited by many species of invertebrates and insects to temporarily avoid seasonally recurring unfavourable conditions for their development, most usually in winter. Less frequently, a prolonged diapause lasting two or more years is described in species living in unpredictable environments where it is adaptive, but with significant costs. In this paper we examine the occurrence of prolonged diapause in the lycaenid butterfly Tomares ballus. Pupae of this species undergo an obligate diapause from mid-May to late January the following year. However, during our rearing experiments (from 2009 to 2016) the emergence of adults occurred sequentially and a fraction of the pupae remained in diapause for up to seven years. The annual percentage emergence after the first year of diapause was 45.6%, and only barely exceeded 50.0% in 2015. Remarkably, 12 pupae (11.4% of the initial brood) remained in diapause in their eighth year. The negative exponential equation fitted to the emergence data suggests that further emergences may occur within the next five years. Therefore, the potential for successful prolonged diapause of T. ballus pupae may be more than 10 years. The adaptive value of this strategy is discussed in relation to the effects of adverse and unpredictable weather during the flight period of the butterfly, intra-guild competition, parasitoids and changes in habitat quality. We suggest that this strategy may also be exhibited by other species of Mediterranean lycaenids., Rafael Obregón, Juan Fernández Haeger, Diego Jordano., and Obsahuje bibliografii
We investigate the control of dynamical networks for the case of nodes, that although different, can be make passive by feedback. The so-called V-stability characterization allows for a simple set of stabilization conditions even in the case of nonidentical nodes. This is due to the fact that under V-stability characterization the dynamical difference between node of a network reduces to their different passivity degrees, that is, a measure of the required feedback gain necessary to make the node stable at a desired solution. We propose a pinning control strategy that extends this approach to solve the tracking problem, furthermore using an adaptive controller approach we provide a methodology to impose a common reference trajectory to a network of different nodes by pinning only a few of them to the desired solution. We illustrate our results with numerical simulation of well-known benchmark systems.
A method based on the adaptive-network-based fuzzy inference system (ANFIS) is presented for computing the narrow aperture dimension of the pyramidal horn. Eight optimization algorithms, least-squares, hybrid learning, Nelder-Mead, genetic, differential evolution, particle swarm, simulated annealing, and clonal selection, are used to optimally determine the design parameters of the ANFIS. The narrow aperture dimension computed by using the ANFIS is used in the optimum gain pyramidal horn design. The computed gains of the designed pyramidal horns are in a very good agreement with the desired gains. When the performances of ANFIS models are compared with each other, the best result is obtained from the ANFIS model trained by the least-squares algorithm.
Adaptavní optické systémy se vyznačují schopností měnit své optické vlastnosti na požádání a v reálném čase. V tomto příspěvku jsou diskutovány základní prvky adaptivních optických systémů využívaných v astronomii ke kompenzaci vlivu atmosféry na zobrazení velkých pozemských teleskopů., Adaptive optical systems are those whose optical responses can be adjusted on demand, in real time. Here we discuss the basics of adaptive optical systems utilised in astronomy for compensation of aberrations due to atmospheric turbulence, which seriously impairs the performance of uncorrected large ground-based telescopes., Jaroslav Řeháček, Bohumil Stoklasa., and Obsahuje seznam literatury