This paper introduced the basic principle and mathematical model of stochastic resonance(SR). For the deficiency of the traditional adaptive SR is that only a single parameter can be optimized while the other paramete...
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This paper introduced the basic principle and mathematical model of stochastic resonance(SR). For the deficiency of the traditional adaptive SR is that only a single parameter can be optimized while the other parameters in the system being fixed. This paper presents a new adaptive SR, It based on PSO, which realizes multi-parameter synchronous optimization. This method reserve the synergistic effect between one structure parameter and another. It determine the signal-noise-ratio of the output of the system as the fitness function of genetic algorithm and it can quickly select the adaptive multi-parameters in SR system. As a result, weak periodical components in orignal signals are sufficiently detected. The experimental result shows that this method has some advantages, such as simple algorithms,good rapidity high accuracy and fine applicability.
The firefly algorithm (FA) is a new population-based metaheuristic bioinspired on the behavior of the flashing characteristics of fireflies. As a population-based algorithm, the FA suffers from large execution times s...
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This paper investigates several control strategies that potential to perform well in regulating and tracking set point of pneumatic actuator system and able to reject disturbance. The system consists of 5-port proport...
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This paper investigates several control strategies that potential to perform well in regulating and tracking set point of pneumatic actuator system and able to reject disturbance. The system consists of 5-port proportional valve with the dead-band flow and double rod cylinders that exhibit significant friction. Two control strategies of PID and NPID controllers with four different configurations with and without dead-zone compensators (DZC) are simulated. Three different input signals including step, sinusoidal and random waveforms are used to evaluate the performance of the proposed techniques. The effectiveness of NPID+DZC has been successfully demonstrated and proved through simulation and experimental studies.
In this paper,we proposed a hybrid method in extracting the attitude parameters of unmanned aerial vehicle(UAV), which is based on computer vision and improved artificial bee colony(ABC) *** is used as a characteristi...
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ISBN:
(纸本)9781479900305
In this paper,we proposed a hybrid method in extracting the attitude parameters of unmanned aerial vehicle(UAV), which is based on computer vision and improved artificial bee colony(ABC) *** is used as a characteristic line, whose two parameters,Φandσare utilized to obtain UAV's parameters:roll angleΨand pitch angleθ.Defogging Algorithm is used to make the original pictures clearer and gain the transmission image for horizon *** UAV could obtain the horizon through improved ABC *** also analyzed the relationship between line parameters and UAV parameters and calculated the UAV *** results verified the feasibility and effectiveness of our presented approach.
In the paper predictive model reference control based on Laguerre network using the closed loop with integrator is presented. The performances of this control structure are compared with those of the internal model co...
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In the paper predictive model reference control based on Laguerre network using the closed loop with integrator is presented. The performances of this control structure are compared with those of the internal model control designed using the model reference control principle.
This paper makes a step towards practical applicability of the optimal control for industrial penicillin production. Using the nonlinear gradient method as the key optimization tool, two ways of measurement feedback i...
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This paper makes a step towards practical applicability of the optimal control for industrial penicillin production. Using the nonlinear gradient method as the key optimization tool, two ways of measurement feedback incorporation into the optimization procedure are proposed. Firstly, the receding horizon approach (whose linear variant is widely spreading in the field of operation of various industrial processes) is investigated considering different lengths of optimization horizon. Secondly, the shrinking horizon approach inspired by the character of the solved task with terminal criterion is examined. In order to make the latter comparable to the receding horizon approach, various sampling periods of the input signal are considered. Utilization of the nonlinear continuous time model of the controlled process clearly distinguishes this paper from the earlier publications. The behavior of both approaches is tested on a set of numerical experiments with the focus on performance under constrained computational resources. The obtained results demonstrate the superiority of shrinking horizon approach and its strong computational restriction resistance.
Due to the increase in worldwide energy demand, wind energy technology has been developed rapidly over the past years. With a fast growing of wind power installed capacity, an efficient monitoring system for wind ener...
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Due to the increase in worldwide energy demand, wind energy technology has been developed rapidly over the past years. With a fast growing of wind power installed capacity, an efficient monitoring system for wind energy conversion system (WEC) is required to ensure operational reliability, high availability of energy production and at the same time reduce operating and maintenance (O&M) costs. The state of the art methodologies for WEC condition monitoring are signal analysis, observer-based approach, neural networks, etc. In this paper, an effective and easy adaptable multivariate data-driven method for wind turbine monitoring and fault diagnosis is introduced, which consists of three parts: 1) off-line training process 2) on-line monitoring phase 3) on-line diagnosis phase. The performance of this method is validated for detection of sensor abnormalities that have occurred in real wind turbines.
In this paper, a mathematical modeling of pneumatic actuator system is developed by using RLS algorithm. An ARX model is chosen for the model structure. In order to cater the time-varying parameter of pneumatic system...
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In this paper, a mathematical modeling of pneumatic actuator system is developed by using RLS algorithm. An ARX model is chosen for the model structure. In order to cater the time-varying parameter of pneumatic system, a self-tuning controller is implemented based on the pole-assignment controller. An online RLS algorithm update the parameter estimation at every sample interval. The pole-assignment control parameter is then updated accordingly to the changes of the system parameters. Result of the system performance is compared with the conventional PID controller optimized by PSO algorithm. It is observed that the self-tuning controller performed well with almost zero error at steady state condition and overshoot less than 1%.
In a series of paper the authors proposed a new frequency-domain approach to identify poles in discrete-time linear systems. The discrete rational transfer function is represented in a rational Laguerre-basis, where t...
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ISBN:
(纸本)9781479909964
In a series of paper the authors proposed a new frequency-domain approach to identify poles in discrete-time linear systems. The discrete rational transfer function is represented in a rational Laguerre-basis, where the basis elements are expressed by powers of the Blaschke-function. This function can be interpreted as a congruence transform on the Poincaré unit disc model of the hyperbolic geometry. The identification of a pole is given as a hyperbolic transform of the limit of a quotient-sequence formed from the Laguerre-Fourier coefficients. In this paper the opportunities of reliably computing the poles are analyzed, and some algorithms are proposed for practical use.
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