This paper presents a type of vibration energy harvester combining a piezoelectric cantilever and a single degree of freedom (SDOF) elastic system. The main function of the additional SDOF elastic system is to magnify...
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This paper presents a type of vibration energy harvester combining a piezoelectric cantilever and a single degree of freedom (SDOF) elastic system. The main function of the additional SDOF elastic system is to magnify vibration displacement of the piezoelectric cantilever to improve the power output. A mathematical model of the energy harvester is developed based on Hamilton's principle and Rayleigh-Ritz method. Furthermore, the effects of the structural parameters of the SDOF elastic system on the electromechanical outputs of the energy harvester are analyzed numerically. The accuracy of the output performance in the numerical solution is identified from the finite element method (FEM). A good agreement is found between the numerical results and FEM results. The results show that the power output can be increased and the frequency bandwidth can be improved when the SDOF elastic system has a larger lumped mass and a smaller damping ratio. The numerical results also indicate that a matching load resistance under the short circuit resonance condition can obtain a higher current output, and so is more suitable for application to the piezoelectric energy harvester.
System reconfiguration is often the only means of preserving the continuity of business-critical services after a successful penetration attack. When a fragment of the system has to be isolated (to prevent escalation ...
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ISBN:
(纸本)9781612082097
System reconfiguration is often the only means of preserving the continuity of business-critical services after a successful penetration attack. When a fragment of the system has to be isolated (to prevent escalation of damages caused by the incident), then the other system components need to take over the functions normally performed by the affected servers. The paper addresses a specific aspect of this reconfiguration - the need to predict its impact on the availability of the services. It proposes an efficient approach, based on network simulation, for assessing the response times of services after reconfiguration. This takes into consideration the identified resource consumption interactions between the co-located services. All the presented simulation results are verified on testbed installations. The accuracy of the simulation method allows prediction of the risk of system overloading as an effect of reconfiguration.
This paper addresses the motion planning problem of the trident snake robot consisting of a triangular body equipped with 2-link branches with actuated joints. The kinematics of the robot are represented by a driftles...
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The paper surveys the ideas of cooperation between parametric and nonparametric (kernel-based) algorithms of nonlinear block-oriented system identification. Various strategies are proposed, dependently on the system s...
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Learning classifier systems (LCSs) are rule-based, evolutionary learning systems. Recently, there is a growing interest among the researchers in exploring LCSs implemented in a real-valued environment, due to its prac...
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In the paper we present a new method for solving optimal control problems of a class of hybrid systems. We describe the new effective algorithm based on memetic algorithm (MA) for optimal control of switched systems. ...
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ISBN:
(纸本)9781457718687
In the paper we present a new method for solving optimal control problems of a class of hybrid systems. We describe the new effective algorithm based on memetic algorithm (MA) for optimal control of switched systems. We concentrate on a class of problems in which a pre-specified sequence of active subsystems is known. Our aim is to find both the optimal switching instants and the optimal continuous inputs. The new approach, which we propose, decomposes the cost functional of the basic optimal control problem in Bolza form in two terms. The first term depends explicitly on a value of state variables at the final time. The second term depends on state and control trajectories. In oreder to solve those two tasks we used MA as the multi-objective optimization algorithm. In this paper we considered a fundamental bi-criteria case with two mentioned before functions: the value of state variables at the final time and the state and control trajectories. In order to find an approximation of Pareto frontier, we proposed new effective method based on genetic algorithm (GA) and local search (LS). Problems properties were taken into consideration in the design of our new approach of solving it. They were used to construct new algorithm inspired by the LS NSGA-II, which performed rather well in multi-criteria scheduling problem. Since simple genetic algorithms are efficient heuristics in searching for optimal solutions, but lack the accuracy of some more computational complex algorithms, a hybrid algorithm was constructed. It uses fast non-dominated sorting, in order to evaluate child population and allocate solutions to corresponding Pareto frontiers. I addition a local search method was used, in order to find more differentiated and better solutions. Clustering solutions from Pareto frontiers also improved diversity of solutions in child population. This approach can be used as a start point for searching for algorithm for solving optimal control problems of switched systems wi
Learning Classifier Systems (LCS) became a large branch of machine learning applications that received a lot of attention recently. Our model of LCS - rGCS or real-value Grammar Classifier System - uses grammar infere...
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In the paper we recover the static characteristic of Wiener-Hammerstein (sandwich) system from inputoutput data. The system is excited and disturbed by random processes with arbitrary distribution. Two kernel-based es...
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We consider the cyclic production system providing on output the mixture of various products. Each product is produced by certain chain of operations, i. e. the unique sequence followed from the technological order. E...
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In the paper we show a new three-stage algorithm identifying the Hammerstein system nonlinearity. The algorithm is designed to work when a poor a priori knowledge is available and when the measurement data set is smal...
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