Bioreactor is one of the prime processing units widely employed to produce important chemical and biochemical compounds. In this paper, a hybrid heuristic algorithm has been attempted to tune PID controller for nonlin...
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ISBN:
(纸本)9781479949816
Bioreactor is one of the prime processing units widely employed to produce important chemical and biochemical compounds. In this paper, a hybrid heuristic algorithm has been attempted to tune PID controller for nonlinear Bioreactor model. The hybrid algorithm is a combination of Bacterial Foraging optimization (BFO) and particleswarmoptimization (PSO) algorithm. Multiobjective performance indexes such as Integral Square Error, peak overshoot are considered to guide this algorithm for discovering best possible value of controller parameters. The controller tuning procedure is individually discussed for both stable and unstable steady state operating region of simulated bio-reactor model. The effectiveness of the proposed scheme has been validated through a comparative study with BFO, PSO based controller tuning methods proposed in the literature. The results show that, the hybrid method provides improved performance in reference tracking and load disturbance rejection with minimal ISE value.
particle swarm optimization algorithm is a simple and effective modern optimizationalgorithm, but it has the problem of being prone to premature and its convergence rate is slow. A new improved PSO algorithm is hence...
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ISBN:
(纸本)9781479951512
particle swarm optimization algorithm is a simple and effective modern optimizationalgorithm, but it has the problem of being prone to premature and its convergence rate is slow. A new improved PSO algorithm is hence proposed. In the iteration of the proposed algorithm, the particles are distinguished to be active or stable according to their velocity information. For the active particles, to maintain the diversity of population, they are replaced by selection from its previous generation's position and its reverse point, which combines the strategy of opposition-based learning. While for the stable particles, to enhance the convergence speed and increase the local search capability, they are improved by conjugate gradient method. The proposed improved PSO algorithm has come through numerical experiments of classic test functions. The results showed that, compared with other improved algorithms, this proposed improved PSO algorithm is feasible and effective.
The electromagnetic shunt damping absorber (EMSDA) is developed based on electromagnetic shunt damping mechanism. The governing equation of planar vibration system equipped with the EMSDA is derived. An optimization m...
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The electromagnetic shunt damping absorber (EMSDA) is developed based on electromagnetic shunt damping mechanism. The governing equation of planar vibration system equipped with the EMSDA is derived. An optimization method is presented to determine the main working parameters of EMSDA on the basis of the built theoretical model. The objective function minimizing the response variance of system under white noise excitation is formulated. The particle swarm optimization algorithm is employed in optimization. The simulated and experimental studies on vibration control by use of EMSDA are conducted. The results show that the electromagnetic shunt damping absorber can attenuate significantly the structural vibration.
This paper presents the application of a Metaheuristic optimizationalgorithm for determining the parameters of a PI controller and the values of the state and measurement noise of Kalman Filter. The particleswarm op...
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ISBN:
(纸本)9781479920600
This paper presents the application of a Metaheuristic optimizationalgorithm for determining the parameters of a PI controller and the values of the state and measurement noise of Kalman Filter. The particleswarmoptimization is a new technique that is used to solve complex problems. It minimizes a cost function under the cooperation of many individuals. Kalman Filter is used here to estimate the stator currents and rotor fluxes of the induction motor. The performances of the extended Kalman Filter and the adaptive Kalman Filter are analyzed. They are applied to estimate stator currents;rotor fluxes and rotor speed of the induction motor, and thus help to overcome the speed sensor, which is expensive and bulky. The extended Kalman Filter requires extending the state vector to rotor speed, which implies to use the linearization of the model. The adaptive Kalman Filter consists of determining the rotor speed adaptation law. The stability of the estimation error is proved using a Lyapunov function.
The electric multiple units (EMU) provide a transport service in the dynamical running environment, which should meet the requirements of safety, punctuality, precise train stopping, energy conservation and comfort si...
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ISBN:
(纸本)9781479958252
The electric multiple units (EMU) provide a transport service in the dynamical running environment, which should meet the requirements of safety, punctuality, precise train stopping, energy conservation and comfort simultaneously. However, since pervious manual operation method of EMU is mainly based on a given V-S curve (velocity versus position curve) and drivers' experience, it cannot meet the multi-objective operation requirements in real time. In order to improve the operation strategy, this paper develops a multiobjective online optimization model for the EMU operation based on speed limit curve. Then, we optimize the operation strategy using a modified multi-objective particle swarm optimization algorithm on line, so as to obtain the Pareto optimal solution set. Further, based on the delay state of EMU running process, we pick out the optimal operation strategy from the Pareto set. Finally, the running process of the EMU operated on the optimal operation strategy can satisfy the multi-objective requirements. And the experimental results on the field data of CRH380AL (China railway high-speed EMU type-380AL) running process show the real time effectiveness of the proposed approach.
The purpose of this paper is to add particle swarm optimization algorithm to Generalized Regression Neural Network for predicting egg Haugh value and evaluating freshness degree of eggs. Firstly process the egg images...
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ISBN:
(纸本)9783037859391
The purpose of this paper is to add particle swarm optimization algorithm to Generalized Regression Neural Network for predicting egg Haugh value and evaluating freshness degree of eggs. Firstly process the egg images with light-transmitting were obtained by the computer vision device including denoising, threshold segmentation, conversing HSI Color model and calculating the averages of hue, saturation, and intensity in the center of the image. Secondly analyze GRNN, and then particleswarmalgorithm to optimize according to the predicted formula being derived. Thirdly train Improved GRNN and predicate Haugh value by HSI parameter data as the sample. The value of residual errors of Improved GRNN model are 6.38, the correct discerning rate of grading table eggs is 91.2%. It proves better than traditional BP neural network in terms of predicted accuracy and robustness.
In this paper, the problem of both bandwidth and power allocation for two-way multiple relay systems in overlay cognitive radio (CR) set-up is investigated. In the CR overlay mode, primary users (PUs) cooperate with c...
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ISBN:
(纸本)9781479935123
In this paper, the problem of both bandwidth and power allocation for two-way multiple relay systems in overlay cognitive radio (CR) set-up is investigated. In the CR overlay mode, primary users (PUs) cooperate with cognitive users (CUs) for mutual benefits. In our framework, we propose that the CUs are allowed to allocate a part of the PUs spectrum to perform their cognitive transmission. In return, acting as an amplify-and-forward two-way relays, they are used to support PUs to achieve their target data rates over the remaining bandwidth. More specifically, CUs acts as relays for the PUs and gain some spectrum as long as they respect a specific power budget and primary quality-of-service constraints. In this context, we first derive closed-form expressions for optimal transmit power allocated to PUs and CUs in order to maximize the cognitive objective. Then, we employ a strong optimization tool based on particle swarm optimization algorithm to find the optimal relay amplification gains and optimal cognitive released bandwidths as well. Our numerical results illustrate the performance of our proposed algorithm for different utility metrics and analyze the impact of some system parameters on the achieved performance.
In order to estimate the coherent source, a modified multiple signal classification (MUSIC) algorithm is introduced. And a novel arrangement method for the non-uniform linear array by particleswarmoptimization (PSO)...
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ISBN:
(纸本)9783038350019
In order to estimate the coherent source, a modified multiple signal classification (MUSIC) algorithm is introduced. And a novel arrangement method for the non-uniform linear array by particleswarmoptimization (PSO) algorithm is proposed. This method needs merely a signal source whose direction-of-arrival (DOA) has been exactly known. The proposed method has a simple processing and a strong stabilization. It could be applied to optimized arbitrary array configuration. The simulation verifies that the performance of DOA estimation is improved effectively, which has proved the validity of the proposed method.
Due to the increased complexity of port operations, port project portfolio management has become more and more essential. However, in port project portfolio management, the demand for resources is usually uncertain. I...
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ISBN:
(纸本)9781479953721
Due to the increased complexity of port operations, port project portfolio management has become more and more essential. However, in port project portfolio management, the demand for resources is usually uncertain. In order to reduce the cost and the difficulty of resource allocation, we pay more attention to balancing resource allocation than minimizing the maximum value of the consumption of resources. Thus we consider a resource leveling problem in port project portfolio management. In this paper, we introduce a combination of entropy weight and particle swarm optimization algorithm. This proposed method is applied to a case study. And the results show that this method can achieve satisfactory performance in practice.
Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is...
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ISBN:
(纸本)9780735412415
Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (T-p : I -> I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks.
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