This paper proposes an efficient current control algorithm and a suitable power conversion system of a multiple-module transverse flux permanent magnet generator (MM-TFPMG) for large-scale direct-drive wind turbines. ...
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ISBN:
(纸本)9781457705427;9781457705410
This paper proposes an efficient current control algorithm and a suitable power conversion system of a multiple-module transverse flux permanent magnet generator (MM-TFPMG) for large-scale direct-drive wind turbines. The MM-TFPMG is composed of multiple-module structures based on an independent three-phase configuration. In this paper, the single-phase current control applying the d-q transformation and the independent three-phase dqn-axes current control are proposed for the generator-side control of the MM-TFPMG. The control performance and characteristics of the single-phase dq-axes current control with a variable cutoff frequency and the independent three-phase dqn-axes current control using a concept of vector control are analyzed. As a result, the independent three-phase dqn-axes current control by using the vector control is an appropriate method to efficiently control the generator-side of the MM-TFPMG. The proposed algorithm is easily implemented and has less computation resource. Moreover, the control performance is better than the independent single-phase dq-axes current control despite the change of wind speed. The validity and usefulness of the proposed independent three-phase dqn-axes current control algorithm are verified and compared through several experimental results.
In this work, we design and implement a control and sensing system for a three-finger robot hand. The system effectively controls the joint angles and forces of the hand. Then, the grasping capability of the hand is d...
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ISBN:
(纸本)9781457721366
In this work, we design and implement a control and sensing system for a three-finger robot hand. The system effectively controls the joint angles and forces of the hand. Then, the grasping capability of the hand is demonstrated using the system. The MSP430 is employed as the microcontroller for the position and force feedback control circuit. For the position control, the adaptive PD controller is employed, while the traditional PID controller is used for the force control. In addition, using the force/position hybrid control method, the aforementioned two controllers are integrated. We adapt the commercially-available pressure sensor elements to build a multi-axis sensing system. The required platform for the demonstration of the control and sensing system are also developed. We use an x-y table to emulate the arm of a robot hand. The developed control/driving/sensing circuit boards are attached on the x-y table. Labview is employed as the software platform for the high-level control commands. Furthermore, the codes developed in Labview are connected with Matlab for computing with other control algorithms, such as the force closure. Moreover, with the measured force data collected by sensing system, it is demonstrated that the hand can be real-time controlled to steadily grasping an object.
The recent penetration of distributed green energy, distribution intelligence, and plug-in electric vehicles (EVs) calls for a better information organization in an Energy Internet. Such an information system usually ...
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ISBN:
(纸本)9781538614280
The recent penetration of distributed green energy, distribution intelligence, and plug-in electric vehicles (EVs) calls for a better information organization in an Energy Internet. Such an information system usually considers mostly the static grids. In this paper, we propose a test-bed not only for the static grid but also for the dynamic devices such as electric vehicles. To reduce the physical size of such a test-bed, we design the robot to have two wheels. To avoid human interruption to the test, we replace the manual charging procedure with wireless charging. To enable the EV robot for self-balancing with its two wheels, we implanted the EV robot with a control algorithm based on a neural network. To provide the EV robots with charging instructions, a joint optimization is carried out by considering both the economic factor on the customer side and the grid security constraint on the utility side. Numerical results demonstrate the testbed's capability of handling many EV robots.
A fuzzy predictive controller using particle swarm optimization (PSO) approach is proposed. The aim is to develop an efficient algorithm that is able to handle the relatively complex optimization problem with minimal ...
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A fuzzy predictive controller using particle swarm optimization (PSO) approach is proposed. The aim is to develop an efficient algorithm that is able to handle the relatively complex optimization problem with minimal computational time. This can be achieved using reduced population size and small number of iterations. In this algorithm, instead of using the uniform distribution as in the conventional PSO algorithm, the initial particles positions are distributed according to the normal distribution law, within the area around the best position. The radius limiting this area is adaptively changed according to the tracking error values. Moreover, the choice of the initial best position is based on prior knowledge about the search space landscape and the fact that in most practical applications the dynamic optimization problem changes are gradual. The efficiency of the proposed control algorithm is evaluated by considering the control of the model of a 4 x 4 Multi-Input Multi-Output industrial boiler. This model is characterized by being nonlinear with high interactions between its inputs and outputs, having a nonminimum phase behaviour, and containing instabilities and time delays. The obtained results are compared to those of the control algorithms based on the conventional PSO and the linear approach.
Presents corrections to the paper, “A new algorithm for time-delay estimation in ultrasonic echo signals,” (Shaswary, E., et al; IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 62, no. 1, pp. 236–241, Jan. 2...
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Presents corrections to the paper, “A new algorithm for time-delay estimation in ultrasonic echo signals,” (Shaswary, E., et al; IEEE Trans. Ultrason. Ferroelectr. Freq. Control, vol. 62, no. 1, pp. 236–241, Jan. 2015).
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