In this paper, the stabilization problems of a class of new hyperchaotic systems with fully unknown parameters are concerned. Based on the adaptive control idea, two novel adaptive state feedback controllers are desig...
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In this paper, the stabilization problems of a class of new hyperchaotic systems with fully unknown parameters are concerned. Based on the adaptive control idea, two novel adaptive state feedback controllers are designed to implement the asymptotic stabilization of this kind of new hyperchaotic system by choosing appropriate controller structure and parametric updating law, respectively. The effectiveness of the proposed adaptive control method is verified by simulation results.
This paper presents a reinforcement learning algorithm and provides conditions for global convergence to Nash equilibria. For several reinforcement learning schemes, including the ones proposed here, excluding converg...
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ISBN:
(纸本)9781612848006
This paper presents a reinforcement learning algorithm and provides conditions for global convergence to Nash equilibria. For several reinforcement learning schemes, including the ones proposed here, excluding convergence to action profiles which are not Nash equilibria may not be trivial, unless the step-size sequence is appropriately tailored to the specifics of the game. In this paper, we sidestep these issues by introducing a new class of reinforcement learning schemes where the strategy of each agent is perturbed by a state-dependent perturbation function. Contrary to prior work on equilibrium selection in games, where perturbation functions are globally state dependent, the perturbation function here is assumed to be local, i.e., it only depends on the strategy of each agent. We provide conditions under which the strategies of the agents will converge to an arbitrarily small neighborhood of the set of Nash equilibria almost surely. We further specialize the results to a class of potential games.
Multi parametric quadratic programming is an alternative means of implementing conventional predictive control algorithms whereby one transfers much of the computational load to offline calculations. This paper demons...
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Multi parametric quadratic programming is an alternative means of implementing conventional predictive control algorithms whereby one transfers much of the computational load to offline calculations. This paper demonstrates how one can formulate a robust MPC problem as a quadratic program and hence make it amenable to MPQP solutions. The paper then derives some MPQP solutions and discusses the efficacy of these.
This paper addresses the dissolved oxygen tracking problem in multi-zone bioreactor. The proposed approach utilizes decentralized control system incorporating fuzzy multiregional PI controllers so that satisfactory co...
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This paper addresses the dissolved oxygen tracking problem in multi-zone bioreactor. The proposed approach utilizes decentralized control system incorporating fuzzy multiregional PI controllers so that satisfactory controller performance can be robustly and reliably achieved over a whole process operating range. A fuzzy supervisor of the completely decentralized control system is introduced in order to meet a global actuator capacity constraint. An overall control system can be implemented by using fairly standard equipment that is commonly available at a plant site.
Most of iterative learning control (ILC) methods requires that the relative degree of the plant is less than 2 for a linear system or the plant is passive for a non-linear system. A new model reference parametric adap...
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Most of iterative learning control (ILC) methods requires that the relative degree of the plant is less than 2 for a linear system or the plant is passive for a non-linear system. A new model reference parametric adaptive iterative learning control using the command generator tracker (CGT) theory is proposed in this paper. The method can be applied to control a plant with a higher relative degree and it only requires to iteratively adjust n m + 2 parameters for an SISO plant. Therefore, the ILC control system is very simple. The proposed method is in the spirit of simple adaptive control which has received intensive researches during past two decades. Simulation results show the effectiveness and usefulness of the proposed method.
In this paper we propose a new efficient algorithm of noise suppression in color images. The new technique of multichannel image enhancement is capable of reducing impulsive and Gaussian noise and it outperforms the s...
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In this paper we propose a new efficient algorithm of noise suppression in color images. The new technique of multichannel image enhancement is capable of reducing impulsive and Gaussian noise and it outperforms the standard methods of noise reduction. In this paper a new smoothing operator, based on a random walk model and on a fuzzy similarity membership function of pixels connected by digital paths is introduced. The efficiency of the proposed method has been tested on the standard color images using the widely used objective image quality measures.
This paper proposes a convex approach to the Frisch-Kalman problem that identifies the linear relations among variables from noisy observations. The problem was proposed by Ragnar Frisch in 1930s, and was promoted and...
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ISBN:
(数字)9781728113982
ISBN:
(纸本)9781728113999
This paper proposes a convex approach to the Frisch-Kalman problem that identifies the linear relations among variables from noisy observations. The problem was proposed by Ragnar Frisch in 1930s, and was promoted and further developed by Rudolf Kalman later in 1980s. It is essentially a rank minimization problem with convex constraints. Regarding this problem, analytical results and heuristic methods have been pursued over a half century. The proposed convex method in this paper is demonstrated to outperform several commonly adopted heuristics when the noise components are relatively small compared with the underlying data.
This paper formulates the problem of aircraft conflict avoidance as a multiphase mixed-integer optimal control problem. In order to find optimal maneuvers, accurate models of aircraft nonlinear dynamics and flight env...
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ISBN:
(纸本)9781467320658
This paper formulates the problem of aircraft conflict avoidance as a multiphase mixed-integer optimal control problem. In order to find optimal maneuvers, accurate models of aircraft nonlinear dynamics and flight envelop constraints are used. Wind forecast and obstacles in airspace due to hazardous weather are included. The objective is to design aircraft maneuvers that ensure safety while minimizing fuel consumption. The solution approach is based on conversion of the multiphase mixed-integer optimal control problem into a mixed-integer nonlinear programming problem. Two case studies for the Airbus 320 aircraft illustrate the approach.
This paper applies a recent full-matrix multi-input-multi-output QFT controller design methodology to simultaneously regulate nitrogen and phosphorus concentrations in the effluent of a wastewater treatment plant (WWT...
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This paper applies a recent full-matrix multi-input-multi-output QFT controller design methodology to simultaneously regulate nitrogen and phosphorus concentrations in the effluent of a wastewater treatment plant (WWTP) according to environmental standard policies. The robust controller is based on two terms: a non-diagonal pre-compensator for decoupling and a diagonal controller for robust performance and stability. Simulation results show the benefits of the control strategy for WWTP-type complex processes with large channel-interaction and uncertainty.
This work aims to investigate conditions for normality and non-degeneracy of the maximum principle for general state-constrained optimal control problems in which the state constraints are given by equalities and ineq...
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This work aims to investigate conditions for normality and non-degeneracy of the maximum principle for general state-constrained optimal control problems in which the state constraints are given by equalities and inequalities. Non-degeneracy is proved under a regularity condition formulated in terms of the limiting normal cone to the feasible control set. The same regularity condition implies normality of the maximum principle if one of the end-points is free.
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