The problem to minimize power losses in an electrical network subject to voltage and power constraints is in general hard to solve. However, it has recently been discovered that semidefinite programming relaxations in...
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This paper deals with the fractional-order memristive, memcapacitative, and meminductive systems and their utilization in design of the new circuits with memory. We provide a mathematical description of such systems b...
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This paper deals with the fractional-order memristive, memcapacitative, and meminductive systems and their utilization in design of the new circuits with memory. We provide a mathematical description of such systems by using a technique of the fractional calculus. Some possible applications of “mem” systems are mentioned in article as well.
In this paper we propose a distributed algorithm for solving separable convex optimization problems on graphs arising for example from estimation and control in networks. We derive a primal-dual decomposition algorith...
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This paper investigates the boost phase＇s longitudinal autopilot of a ballistic missile equipped with thrust vector control. The existing longitudinal autopilot employs time-invariant passive resistor-inductor-capaci...
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This paper investigates the boost phase＇s longitudinal autopilot of a ballistic missile equipped with thrust vector control. The existing longitudinal autopilot employs time-invariant passive resistor-inductor-capacitor （RLC） network compensator as a control strategy, which does not take into account the time-varying missile dynamics. This may cause the closed-loop system instability in the presence of large disturbance and dynamics uncertainty. Therefore, the existing controller should be redesigned to achieve more stable vehicle response. In this paper, based on gain-scheduling adaptive control strategy, two different types of optimal controllers are proposed. The first controller is gain-scheduled optimal tuning-proportional-integral-derivative （PID） with actuator constraints, which supplies better response but requires a priori knowledge of the system dynamics. Moreover, the controller has oscillatory response in the presence of dynamic uncertainty. Taking this into account, gain-scheduled optimal linear quadratic （LQ） in conjunction with optimal tuning-compensator offers the greatest scope for controller improvement in the presence of dynamic uncertainty and large disturbance. The latter controller is tested through various scenarios for the validated nonlinear dynamic flight model of the real ballistic missile system with autopilot exposed to external disturbances.
In order to capture a selective packaging mechanism among eight RNA segments in influenza A viruses, we assume that almost nucleotides in the positions of packaging signals must be simultaneously changed. In this pape...
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ISBN:
(纸本)9781467327428
In order to capture a selective packaging mechanism among eight RNA segments in influenza A viruses, we assume that almost nucleotides in the positions of packaging signals must be simultaneously changed. In this paper, we formulate such positions as correlated mutations based on a joint entropy ratio, develop a method of finding all of them by using set enumeration with pruning and apply to nucleotide sequences among RNA segments in H3N2 influenza viruses.
For a nonlinear dynamic system that is modeled by differential equations, the output response of nonlinear systems can be obtained by simulating the nonlinear systems in the time domain. It is not generally desirable ...
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ISBN:
(纸本)9780889868724
For a nonlinear dynamic system that is modeled by differential equations, the output response of nonlinear systems can be obtained by simulating the nonlinear systems in the time domain. It is not generally desirable to compute the output response analytically considering formidable complexities that may involve. Indeed, the results can be extremely complex even for some simple structured nonlinear dynamic systems. However, such preference of numerical approach over analytic one is not justified since the numerical approach provide little valuable understandings of the intrinsic characteristics of the dynamic system itself. In order to understand how different parts of the system, parameters of the model and different frequency components within the input interact with each other, an analytic approach to the output response of nonlinear system has been demonstrated in this article. A power series method is developed to compute the output response of nonlinear systems under periodic excitation based on the Volterra series expansion theory of nonlinear systems. At the end of the article, an example has been given to demonstrate the potential application of the power series method.
A new method for the direct adaptive regulation of unknown nonlinear dynamical systems is proposed in this paper,paying special attention to the analysis of the model order *** method uses a neurofuzzy (NF) modeling o...
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A new method for the direct adaptive regulation of unknown nonlinear dynamical systems is proposed in this paper,paying special attention to the analysis of the model order *** method uses a neurofuzzy (NF) modeling of the unknown system,which combines fuzzy systems (FSs) with high order neural networks (HONNs).We propose the approximation of the unknown system by a special form of an NF-dynamical system (NFDS),which,however,may assume a smaller number of states than the original unknown *** omission of states,referred to as a model order problem,is modeled by introducing a disturbance term in the approximating *** development is combined with a sensitivity analysis of the closed loop and provides a comprehensive and rigorous analysis of the stability *** adaptive modification method,termed ‘parameter hopping’,is incorporated into the weight estimation algorithm so that the existence and boundedness of the control signal are always *** applicability and potency of the method are tested by simulations on well known benchmarks such as ‘DC motor’ and ‘Lorenz system’,where it is shown that it performs quite well under a reduced model order ***,the proposed NF approach is shown to outperform simple recurrent high order neural networks (RHONNs).
The accelerating development and usage of autonomous robots has led to increased interest in decentralised systems and the cooperation of individual elements within a swarm, in particular the ability to self-organise ...
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In this paper an anti-slip predictive controller is designed and implemented in order to control the rear wheels of a V-PRA (Variable Powered Rear Axle) vehicle. The control algorithm is EPSAC, a Model based Predictiv...
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This paper presents the utilisation of continuous ant colony optimisation algorithm intended for active vibration control of flexible beam structures. Ant colony optimisation algorithm is used to realise a direct cont...
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