Optimal control and synchronization of Lorenz system with complete unknown parameters

The paper discusses the optimal control and synchronization problems of Lorenz systems with fully unknown parameters. Based on the Liapunov–Bellman technique, the optimal control law with three-state variables feedback is derived such that the trajectory of the Lorenz system is optimally stabilized to an equilibrium point of the uncontrolled system. Further, another optimal control law is also applied to achieve the state synchronization of two identical Lorenz systems. Numerical results to demonstrate the effectiveness of the proposed control scheme.     

Linear square optimal control problem for stochastic difference equations with unknown parameters

The problems of stability and optimal control for stochastic difference equations are receiving important attention now (see, for example, [1–3]). In this paper, the optimal control in final form is obtained for optimal control problem of stochastic linear difference equation with unknown parameters and square cost functional. For stochastic functional differential equations, analogous result are obtained in [4].     

Circuit realization,chaos synchronization and estimation of parameters of a hyperchaotic system with unknown parameters

In this article, the adaptive chaos synchronization technique is implemented by an electronic circuit and applied to the hyperchaotic system proposed by Chen et al. We consider the more realistic and practical case where all the parameters of the master system are unknowns. We propose and implement an electronic circuit that performs the estimation of the unknown parameters and the updating of the parameters of the slave system automatically, and hence it achieves the synchronization. To the best of our knowledge, this is the first attempt to implement a circuit that estimates the values of the unknown parameters of chaotic system and achieves synchronization. The proposed circuit has a variety of suitable real applications related to chaos encryption and cryptography. The outputs of the implemented circuits and numerical simulation results are shown to view the performance of the synchronized system and the proposed circuit.     

Numerical computation of optimal control problems with unknown final time

This paper presents a numerical computational method for the solution of optimal control problems with unknown final time. The method presented is based on a transformation and a modified quasilinearization technique. A numerical example is included for illustration.     

Model-free control of Lorenz chaos using an approximate optimal control strategy

In this paper, we are concerned with model-free control of the Lorenz chaotic system, where only the online input and output are available while the mathematic model of the system is unknown. The problem is formulated from an optimal control perspective and solved using an iterative method. The convergence of the iteration and the stability of the control law are proven in theory. Simulations validate theoretical conclusions and demonstrate the effectiveness of the proposed method.     

Adaptive deadband control of a drifting process with unknown parameters

Adjusting a drifting process to minimize the expected sum of quadratic off-target and fixed adjustment costs is considered under unknown process parameters. A Bayesian approach based on sequential Monte Carlo methods is presented. The benefits of the resulting “deadband” adjustment policy are studied.     

Structure-exploiting polynomial chaos for uncertain optimal control problems with sparse derivative generation

We present advances in structure-exploiting non-intrusive polynomial chaos methods for the numerical solution of nonlinear optimal control problems with parametric uncertainties. In particular, we make use of the special structure induced by the spectral projection to reuse model derivatives and exploit sparsity information leading to a fast automatic sensitivity generation. This greatly reduces the computational effort of Newton-type methods for the solution of the resulting high-dimensional surrogate problem. The results are complemented by a complexity comparison and a numerical case study. (© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Adaptive control of Markov processes with incomplete state information and unknown parameters

Recent results for parameter-adaptive Markov decision processes (MDP's) are extended to partially observed MDP's depending on unknown parameters. These results include approximations converging uniformly to the optimal reward function and asymptotically optimal adaptive policies.This research was supported in part by the Consejo del Sistema Nacional de Educación Tecnologica (COSNET) under Grant 178/84, in part by the Air Force Office of Scientific Research under Grant AFOSR-84-0089, in part by the National Science Foundation under Grant ECS-84-12100, and in part by the Joint Services Electronics Program under Contract F49602-82-C-0033.     

Three-species food web model with impulsive control strategy and chaos

A three-species ecological model with impulsive control strategy is developed using the theory and methods of ecology and ordinary differential equation. Conditions for extinction of the system are given based on the theory of impulsive equation and small amplitude perturbation. Using comparison involving multiple Lyapunov functions, the system is shown to be permanent. Further, the influence of the impulsive perturbation on the inherent oscillation are studied numerically and is found to depict rich dynamics, such as the period-doubling bifurcation, the period-halving bifurcation, a chaotic band, a narrow or wide periodic window, and chaotic crises. In addition, the largest Lyapunov exponent is computed. This computation demonstrates the chaotic dynamic behavior of the model. The qualitative nature of concerned strange attractors is also investigated through their computed Fourier spectra. The foregoing results have the potential to be useful for the study of the dynamic complexity of ecosystems.     

A stochastic programming model to find optimal sample sizes to estimate unknown parameters in an LP

An LP is considered where the technology coefficients are unknown and random samples are taken to estimate them. A stochastic programming problem is formulated to find the optimal sample sizes where it is required that a confidence interval should cover the unknown deterministic optimum value by a given probability and the cost of sampling be minimum.     

Adaptive control and synchronization of a four-dimensional energy resources system with unknown parameters

This paper is involved with control and synchronization of a new four-dimensional energy resources system with unknown parameters. Based on the Lyapunov stability theorem, by designed adaptive controllers and parameter update laws, this system is stabilized to unstable equilibrium and synchronizations between two systems with different unknown system parameters are realized Numerical simulations are given for the purpose of illustration and verification.     

Neimark-Sacker bifurcation and chaos control in Hassell-Varley model

We investigate the complex behaviour of a modified Nicholson–Bailey model. The modification is proposed by Hassel and Varley taking into account that interaction between parasitoids is taken in such a way that the searching area per parasitoid is inversely proportional to the m-th power of the population density of parasitoids. Under certain parametric conditions the unique positive equilibrium point of system is locally asymptotically stable. Moreover, it is proved that system undergoes Neimark-Sacker bifurcation for small range of parameters by using standard mathematical techniques of bifurcation theory. In order to control Neimark-Sacker bifurcation, we apply simple feedback control strategy and pole-placement technique which is a modification of OGY method. Moreover, the hybrid control methodology is also implemented for chaos controlling. Numerical simulations are provided to illustrate theoretical discussion.     

Hurwicz model of uncertain optimal control with jump

How to choose the optimization criterion of the objective function is an important issue for uncertain optimal control. The Hurwicz criterion is a flexible optimization criterion attempting to find the intermediate area between the extremes posed by the optimistic and pessimistic criteria. Based on uncertainty theory, in this paper, we establish a new uncertain optimal control model with jump by making use of Hurwicz criterion to optimize an uncertain objective function. By applying Bellman's principle of optimality, the principle of optimality for the proposed model is presented and then the equation of optimality is derived. Finally, an example is given to show the the effectiveness of the results obtained.     

The complete optimal stars-clustering-tree problem

We consider the following complete optimal stars-clustering-tree problem: Given a complete graph G=(V,E) with a weight on every edge and a collection of subsets of V, we want to find a minimum weight spanning tree T such that each subset of the vertices in the collection induces a complete star in T. One motivation for this problem is to construct a minimum cost (weight) communication tree network for a collection of (not necessarily disjoint) groups of customers such that each group induces a complete star. As a result the network will provide a “group broadcast” property, “group fault tolerance” and “group privacy”. We present another motivation from database systems with replications. For the case where the intersection graph of the subsets is connected we present a structure theorem that describes all feasible solutions. Based on it we provide a polynomial algorithm for finding an optimal solution. For the case where each subset induces a complete star minus at most k leaves we prove that the problem is NP-hard.     

The control of chaotic systems with unknown parameters and external disturbance via backstepping‐like scheme

This article addresses the adaptive control of chaotic systems with unknown parameters, model uncertainties, and external disturbance. We first investigate the control of a class of chaotic systems and then discuss the control of general chaotic systems. Based on the backstepping‐like procedure, some novel criteria are proposed via adaptive control scheme. As an example to illustrate the application of the proposed method, the control and synchronization of the modified Chua's chaotic system is also investigated via a single input. Some numerical simulations are given to demonstrate the robustness and efficiency of the proposed approach. © 2016 Wiley Periodicals, Inc. Complexity 21: 573–583, 2016     

On a class of optimal control problems with distributed and lumped parameters

The optimal control of moving sources governed by a parabolic equation and a system of ordinary differential equations with initial and boundary conditions is considered. For this problem, an existence and uniqueness theorem is proved, sufficient conditions for the Fréchet differentiability of the cost functional are established, an expression for its gradient is derived, and necessary optimality conditions in the form of pointwise and integral maximum principles are obtained.     

A dynamical model of echinococcosis with optimal control and cost-effectiveness

A dynamical model of echinococcosis transmission with optimal control strategies is first presented. The basic reproduction number of the model is determined and employed to study the global stability of the disease-free and endemic equilibrium points. The optimal control problem is formulated and solved analytically. Numerical simulations show that optimal control strategies could effectively reduce the transmission of echinococcosis. The cost-effectiveness analysis suggests that a combination of health education, anthelmintic treatment, and home slaughter inspection could provide the best cost-effective strategy to control the transmission of echinococcosis. Furthermore, it finds that anthelmintic treatment and environmental disinfection may shorten the time of eliminating the disease. The results may be helpful for prevention and control of echinococcosis in Ganzi Tibetan Autonomous Prefecture, China and other areas of echinococcosis.     

On optimal search with unknown detection probabilities

An object is hidden in box i with probability P_i, for i = 1, 2,…, I. A search of a box detects the object, given that it is in the box, with probability d. The detection probability d is fixed but unknown. The asymptotic form of an optimal search policy is related to the behaviour near zero of the prior distribution for d.     

A schistosomiasis compartment model with incubation and its optimal control

A new mathematical model included an exposed compartment is established in consideration of incubation period of schistosoma in human body. The basic reproduction number is calculated to illustrate the threshold of disease outbreak. The existence of the disease free equilibrium and the endemic equilibrium are proved. Studies about stability behaviors of the model are exploited. Moreover, control measure assessments are investigated in order to seek out effective control interventions for anti‐schistosomiasis. Then, the corresponding optimal control problem according to the model is presented and solved. Theoretical analyses and numerical simulations induce several prevention and control strategies for anti‐schistosomiasis. At last, a discussion is provided about our results and further work. Copyright © 2017 John Wiley & Sons, Ltd.     

Adaptive control and synchronization of identical new chaotic flows with unknown parameters via single input

The single input linear feedback control for synchronizing two identical new 3D chaotic flows reported by Li et al. [X.F. Li, K.E. Chlouverakis, D.L. Xu, Nonlinear dynamics and circuit realization of a new chaotic flow: a variant of Lorenz, Chen and Lü, Nonlinear Analysis RWA 10 (4) (2009) 2357-2368] is proposed in this paper. Sufficient conditions of synchronization are obtained for both linear feedback and adaptive control approaches. The problem of adaptive synchronization between two nearly identical chaotic systems with unknown parameters is also studied. Based on the Lyapunov stability theory, two kinds of single input adaptive synchronization controllers are designed and the adaptive parameter update laws are developed.