The direct power control (DPC) algorithm is one of the most popular linear techniques used to implement notable controllers, known for their simplicity and fast dynamic response. However, this approach has drawbacks t...
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The direct power control (DPC) algorithm is one of the most popular linear techniques used to implement notable controllers, known for their simplicity and fast dynamic response. However, this approach has drawbacks that cause a decrease in the current quality and disturbances in the network. Therefore, this experimental work presents a simple and efficient solution that uses a proportional-integral regulator based on a genetic algorithm to regulate the power quality. The designed approach uses a pulse width modulation to produce control pulses for the operation of the rotor inverter of a doubly-fed induction generator-based multi-rotor wind system. This approach is first verified in MATLAB using a 1500 kW generator operating under different working conditions. Furthermore, the processor-in-the-loop (PIL) test using dSPACE 1104 is used to verify the efficacy and ability of the designed approach in enhancing the effectiveness of the power system under study. The results obtained in all tests demonstrate that compared to DPC, the designed approach reduces active power ripples with estimated percentages of 71.42%, 66.67%, and 70%, and the reactive power overshoot value is reduced with estimated percentages of 92.85%, 56.48%, and 79.21%. In addition, the experimental results (using the PIL test) confirm the ability of the designed control algorithm to enhance the energy and current quality, which makes this designed technique a suitable solution in the field of control.
This paper introduces an efficient model-based DC fault detection and location scheme for voltage source converter (VSC)-based multi-terminal high voltage DC (MTHVDC) systems. The main idea of the proposed approach is...
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This paper introduces an efficient model-based DC fault detection and location scheme for voltage source converter (VSC)-based multi-terminal high voltage DC (MTHVDC) systems. The main idea of the proposed approach is to use the difference signal between the real and estimated currents of the HVDC line as the signature to detect the faulty conditions. The state-space model of the HVDC line is established and used together with the Kalman filter (KF) algorithm for optimal estimation of the DC current at the sending end of the line. The observability of the developed state-space model is analytically proved. The developed model is also used to locate the fault point by post-processing of the measured data with the least-squares method. The main superiorities of the proposed approach are its high accuracy and excellent robustness against measurement noises/errors. These features are demonstrated through extensive MATLAB simulations of a typical three-terminal radial MTHVDC system. Likewise, the real-time feasibility of the proposed approach is guaranteed by some processor-in-the-loop tests. The results show that the proposed method achieves excellent fault detection and location performance, while the measurements are contaminated with noises as strong as 30 dB.
Designing the boundary layer thickness and switching gain in the nonlinear part of sliding mode controller (SMC) is one of the main subjects in SMC design that needs human experience, knowledge on the amplitude of dis...
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Designing the boundary layer thickness and switching gain in the nonlinear part of sliding mode controller (SMC) is one of the main subjects in SMC design that needs human experience, knowledge on the amplitude of disturbances, and information about the bounds of system uncertainties. In this paper, to reduce the trial-and-error effort by the designer(s) two different fitness functions in the horizontal and vertical planes are presented and a heuristic method is used for their optimization. The optimal switching gain in the proposed approach properly compensates the unmodeled dynamics, model uncertainty, and external disturbances. Chattering phenomenon in control signals and noise measurement effect are reduced by the optimal selection of boundary layer thickness. This proposed method is applied to an autonomous underwater vehicle (AUV) and evaluated through the real-time and cost-effective manner. The execution code is implemented on a single-board computer (SBC) through the xPC Target and is evaluated by the processor-in-the-loop (PIL) test. The results of the PIL test in the two different test cases indicate that the chattering phenomenon and amplitude of control signal applied to the actuators are reduced in comparison with the three conventional approaches in the AUV motion control.
A randomized sampling-based path planning algorithm for holonomic mobile robots in complex configuration spaces is proposed in this article. A complex configuration space for path planning algorithms may cause differe...
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A randomized sampling-based path planning algorithm for holonomic mobile robots in complex configuration spaces is proposed in this article. A complex configuration space for path planning algorithms may cause different environmental constraints including the convex/concave obstacles, narrow passages, maze-like spaces and cluttered obstacles. The number of vertices and edges of a search tree for path planning in these configuration spaces would increase through the conventional randomized sampling-based algorithm leading to exacerbation of computational complexity and required runtime. The proposed path planning algorithm is named fuzzy greedy rapidly-exploring random tree (FG-RRT). The FG-RRT is equipped with a fuzzy inference system (FIS) consisting of two inputs, one output and nine rules. The first input is a Euclidean function applied in evaluating the quantity of selected parent vertex. The second input is a metaheuristic function applied in evaluating the quality of selected parent vertex. The output indicates the competency of the selected parent vertex for generating a random offspring vertex. This algorithm controls the tree edges growth direction and density in different places of the configuration space concurrently. The proposed method is implemented on a Single Board Computer (SBC) through the xPC Target to evaluate this algorithm. For this purpose four test-cases are designed with different complexity. The results of the processor-in-the-loop (PIL) tests indicate that FG-RRT algorithm reduces the required runtime and computational complexity in comparison with the conventional and greedy RRT through fewer number of vertices in planning an initial path in significant manner.
Performance of sliding mode controller (SMC) in the autonomous underwater vehicle (AUV) is affected by the nonlinear parameters selection, which are: boundary layer thickness and switching gain. Human expertise, knowl...
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ISBN:
(纸本)9781450365635
Performance of sliding mode controller (SMC) in the autonomous underwater vehicle (AUV) is affected by the nonlinear parameters selection, which are: boundary layer thickness and switching gain. Human expertise, knowledge on disturbance amplitude and information about the bounds of system uncertainties are required to design these parameters. In order to decrease these requirements an auto-tuning SMC (AT-SMC) with optimal parameters in the nonlinear part of the controller is proposed in this article. For this purpose, a fitness function is presented and a heuristic algorithm is applied for minimizing it. The AT-SMC is implemented on an Axiomtek 84710 through the xPC Target and then the abilities of that in AUV flight control is evaluated through the processor-in-the-loop (PIL) test. By this way, the execution codes of proposed method before the harbor acceptance tests (HAT) and sea acceptance tests (SAT) are verified and so the cost of field tests are reduced in a significant manner The results of the PIL tests in AUV flight control indicate that the AT-SMC reduces the chattering phenomenon and overshoot in comparison with the conventional SMC.
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