This paper presents a new method based on the polytopic linear differential inclusion and the robust mixed H2/∞ filtering for the design of the nonlinear filter with non-Gaussian noises. The main goal is to solve the...
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ISBN:
(纸本)9781467355322
This paper presents a new method based on the polytopic linear differential inclusion and the robust mixed H2/∞ filtering for the design of the nonlinear filter with non-Gaussian noises. The main goal is to solve the problems of the complexity and large calculation number in the general nonlinear filter and the filtering design problem for systems with the non-Gaussian noises. The noises considered in the paper involve two different kinds of noises: white noises and energy bounded noises. Differing from the linearization in most nonlinear filters, the estimation error system for the nonlinear system is represented by an uncertain polytopic linear model, based on which, the rectification equations for the predicted errors are designed following the robust mixed H2/∞ filtering. The state estimates for the nonlinear system are given through updating the predictions by the rectified quantities, where, the state predicted quantities of the nonlinear system are gained by the prediction equation of the EKF. The evident advantage of the new filter is the filter coefficients of the rectification equation are constant, without the need to evaluate the Jacobian matrixes. As a result, the calculation number for the new filter is decreased much and the real-time performance of the new filter is much better than the EKF, though the accuracy is a little decline. Its effectiveness is demonstrated by using an example and the statistics result of the calculation number for the filters in the example.
This paper presents a novel maximum power point (MPP) tracking (MPPT) method to increase photovoltaic (PV) system performance during partially shaded conditions (PSCs). The method is based on voltage scanning method. ...
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This paper presents a novel maximum power point (MPP) tracking (MPPT) method to increase photovoltaic (PV) system performance during partially shaded conditions (PSCs). The method is based on voltage scanning method. Voltage band method and restricted voltage scanning method is used to increase the scanning speed. A method is proposed to determine whether partial shading occurs. The main advantage of the proposed method is the ability to search the global peak fast. Simulation results shows the good performance of proposed method.
An optimal time-varying sliding mode controller based on SDRE approach is proposed in this paper for re-entry vehicle attitude control in the presence of parametric uncertainties and external disturbances. Firstly, an...
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ISBN:
(纸本)9781467355339
An optimal time-varying sliding mode controller based on SDRE approach is proposed in this paper for re-entry vehicle attitude control in the presence of parametric uncertainties and external disturbances. Firstly, an optimal time-varying sliding surface is obtained through the minimization of a given performance index function and the philosophy of time-varying sliding mode control. Subsequently, a discontinuous control law is designed for guaranteeing the existence of the sliding mode throughout the entire response of the system. Therefore, the global robustness can be ensured. Simulation example is finally given to illustrate the effectiveness of the proposed controller.
A chaotic particle swarm optimization (CPSO) algorithm is proposed by introducing chaos state into the original Particle Swarm Optimization (PSO) which aims to solving the flaws of easy plunging into local optimum and...
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ISBN:
(纸本)9781467355339
A chaotic particle swarm optimization (CPSO) algorithm is proposed by introducing chaos state into the original Particle Swarm Optimization (PSO) which aims to solving the flaws of easy plunging into local optimum and losing search ability in the last period for the fast particle velocity decrease. CPSO algorithm takes advantage of the ergodicity, randomicity, and regularity of chaos to make chaotic searching for the global extremun at the same time with the particle swarm optimization. This algorithm synthesizes the high efficiency of global optimization of PSO algorithm and the ergodicity and randomicity of local search of chaotic algorithm. This paper utilizes aforementioned algorithm to identify the Bouc-Wen hysteresis model for piezoelectric ceramic actuators (PCA). The experimental results show that the model identified by CPSO algorithm has better performance than that by PSO algorithm.
This paper presents observer-based fuzzy control for nonlinear fractional-order systems with the fractional order α satisfying 1 < α < 2 via fuzzy T-S models. Using the properties of the Kronecker product and ...
This paper presents observer-based fuzzy control for nonlinear fractional-order systems with the fractional order α satisfying 1 < α < 2 via fuzzy T-S models. Using the properties of the Kronecker product and LMI approach, the feedback and observer gain matrices are designed. By this method, the state of nonlinear system described as the fuzzy T-S model is convergent to the equilibrium and the observer error is convergent to zero. Finally, the simulation result of a numerical example is given to illustrate the effectiveness of this method.
Budget optimization is an important issue faced by advertisers in search auctions, and has significant impact on the design of various advertising strategies. Given a limited budget on a search market during a certain...
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ISBN:
(纸本)9781479960590
Budget optimization is an important issue faced by advertisers in search auctions, and has significant impact on the design of various advertising strategies. Given a limited budget on a search market during a certain period, an advertiser has to distribute her budget to a series of sequential temporal slots (i.e., days, weeks, or months), during which advertisers must avoid the budget being used up quickly, so as to keep the budget for potential clicks with better performance in the future. Considering the optimal budgets over these temporal slots as fuzzy variables, we establish a two-stage fuzzy budget allocation model, and use particle swarm optimization (PSO) algorithm to solve it in case when these optimal budgets are characterized by discrete fuzzy variables. We also conduct experiments to validate our model and algorithm. The experimental results show that our model can outperform other five budget allocation strategies in terms of reducing the revenue loss of the advertiser.
In search advertisements,advertisers have to seek for an effective allocation strategy to distribute the limited budget over a series of sequential temporal slots(e.g.,days).However,advertisers usually have no suffici...
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In search advertisements,advertisers have to seek for an effective allocation strategy to distribute the limited budget over a series of sequential temporal slots(e.g.,days).However,advertisers usually have no sufficient knowledge to determine the optimal budget for each temporal slot,because there exist much uncertainty in search advertising *** this paper,we present a stochastic model for budget distribution over a series of sequential temporal slots under a finite time horizon,assuming that the best budget is a random *** study some properties and feasible solutions for our model,taking the best budget being characterized by either normal distribution or uniform distribution,***,we also make some experiments to evaluate our model and identify strategies with the real-world data collected from practical advertising *** results show that a)our strategies outperform the baseline strategy that is commonly used in practice;b)the optimal budget is more likely to be normally distributed than uniformly distributed.
In order to get a better dynamic response for actuator in condition of low-speed, a permanent magnet synchronous motor (PMSM) in direct-drive application with the characteristics of high-bandwidth, low-speed and high-...
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In this paper, decentralized filtering of multiagent systems with coupling uncertainties is proposed and investigated. The considered multi-agent system is composed of many agents, each of which evolves with a discret...
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ISBN:
(纸本)9781467355339
In this paper, decentralized filtering of multiagent systems with coupling uncertainties is proposed and investigated. The considered multi-agent system is composed of many agents, each of which evolves with a discrete-time stochastic linear time-varying dynamics, and every agent can be locally influenced by its neighbor agents. Therefore the states evolution of each agent is not only related with its previous states but also related with its neighbors' previous states in the linear dynamic system. Communication limitations existing in the considered multi-agent system restrict that each agent can only observe its own measurements (outputs) and its neighbor agents' outputs while the states are invisible to any agent. Because of communication limitations and information constraints, without knowing the coupling gains of the local interactions, it is not easy for each agent to estimate its states by traditional kalman filter or other state observers, which were extensively discussed in the literature. In this preliminary study, for the considered coupled linear discrete-time multiagent system with uncertain linear local couplings, based on the key idea of state augmentation and the certainty-equivalence principle borrowed from the area of adaptive control, we propose an efficient decentralized kalman filtering scheme, for each agent, to simultaneously estimate the unknown states and coupling parameters, and extensive simulations are conducted, which have clearly verified the effectiveness of the proposed decentralized filtering scheme.
To make humanoid robots walking fast, it's important to improve driving force of their leg joints. Usually, each joint of humanoid robots is driven by a single motor. Dual-motor joint, on the other hand, is one of...
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ISBN:
(纸本)9781467355339
To make humanoid robots walking fast, it's important to improve driving force of their leg joints. Usually, each joint of humanoid robots is driven by a single motor. Dual-motor joint, on the other hand, is one of the candidate solutions to meet the power requirement needed for fast walking. This paper proposed a new dual-motor control model. In the model, two motors are treated as a single control plant instead of two parallel control plants. With the usage of current distributor, the control model can pump different current to each motor freely so as to eliminate the unbalance of the load imposed on each motor. Simulation and experiment show that the proposed model works well under high joint load and it can be used on a fast walking humanoid robot.
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