Search

This paper addresses the protection of a high voltage direct current (HVDC) transmission system, utilizing the modular multilevel converter (MMC) topology in addition to incorporating a hybrid transmission corridor (transmission line including overhead line and cable sections). A solution is proposed for identifying the section within which a dc fault is located for the purpose of maintaining power delivery. A detailed model of the MMC-HVDC system is simulated using PSCAD and an in depth fault analysis is performed. A characteristic signal is discovered and then implemented into a novel solution. The end result is a fault section identification protection algorithm, implementing protective relay coordination to protect the system from false circuit breaker reclose as well as enabling fast system restart for nonpermanent faults. This restart protection algorithm is implemented without the use of a communications channel between converter stations, introducing novelty and quick restart response. [ABSTRACT FROM PUBLISHER]

A main problem in autonomous vehicles in general, and in unmanned aerial vehicles (UAVs) in particular, is the determination of the attitude angles. A novel method to estimate these angles using off-the-shelf components is presented. This paper introduces an attitude heading reference system (AHRS) based on the unscented Kalman filter (UKF) using the three-axis attitude determination (TRIAD) algorithm as the observation model. The performance of the method is assessed through simulations and compared to an AHRS based on the extended Kalman filter (EKF). The paper presents field experiment results using a real fixed-wing UAV. The results show good real-time performance with low computational cost in a microcontroller. [ABSTRACT FROM PUBLISHER]

In this paper, a flux search controller is proposed to increase the efficiency of a direct torque-controlled induction motor in full load range. The value of the flux reference is determined through a minimization algorithm. The amplitude of stator current is used as the objective function since it is shown that samples of the stator current have better statistical properties than input power. In addition, the stator current has more sensitivity to the flux variation than input power. These two properties allow implementing an adaptive algorithm to determine the proper flux step without waste of time. The minimum allowable value of the flux step has been determined based on this process to prevent the divergence problem. This adaptive algorithm set a large flux step for transient state to speed up the convergence process and a small flux step for steady state to minimize the flux ripple. Simulation and experimental results presented in this paper confirm the fast dynamic of the proposed method. [ABSTRACT FROM AUTHOR]

A microgrid is a promising approach to provide clean, renewable, and reliable electricity by integrating various distributed generations and energy storage systems into power systems. However, highly intermittent renewable generations and various load demands pose new challenges to the optimal resource management in a microgrid. This paper proposes a fully distributed control strategy based on the consensus algorithm for the optimal resource management in an islanded microgrid. The proposed strategy is implemented through a multiagent system framework, which only requires information exchange among neighboring agents through a local network. The objective is achieved through a two-level control strategy. The upper control level is a consensus-based optimization algorithm that discovers the reference of optimal power generation or demand while maintaining the supply–demand balance. The lower control level is responsible for reference tracking of the associated component. Simulation results in the IEEE 14- and 162-bus systems are presented to demonstrate the effectiveness of the proposed control strategy. [ABSTRACT FROM PUBLISHER]

In this paper, a Takagi–Sugeno–Kang (TSK)-type-based self-evolving compensatory interval type-2 fuzzy neural network (FNN) (TSCIT2FNN) is proposed for system modeling and noise cancellation problems. A TSCIT2FNN uses type-2 fuzzy sets in an FNN in order to handle the uncertainties associated with information or data in the knowledge base. The antecedent part of each compensatory fuzzy rule is an interval type-2 fuzzy set in the TSCIT2FNN, where compensatory-based fuzzy reasoning uses adaptive fuzzy operation of a neural fuzzy system to make the fuzzy logic system effective and adaptive, and the consequent part is of the TSK type. The TSK-type consequent part is a linear combination of exogenous input variables. Initially, the rule base in the TSCIT2FNN is empty. All rules are derived according to online type-2 fuzzy clustering. For parameter learning, the consequent part parameters are tuned by a variable-expansive Kalman filter algorithm to the reinforce parameter learning ability. The antecedent type-2 fuzzy sets and compensatory weights are learned by a gradient descent algorithm to improve the learning performance. The performance of TSCIT2FNN for the identification is validated and compared with several type-1 and type-2 FNNs. Simulation results show that our approach produces smaller root-mean-square errors and converges more quickly. [ABSTRACT FROM PUBLISHER]

This paper presents the dynamic behavior of multiport power electronic interface (MPEI) under load/source disturbances. A cascaded topology for MPEI is considered. This system is capable of power management for local generations, loads, and storage systems. Large-signal and small-signal models for MPEI are developed. These models are combined with corresponding control algorithms. Simulated and experimental transient responses to disturbances on each port are presented. The behavior of MPEI in response to each disturbance is analyzed. Simulation and experimental results are compared in order to verify the model. [ABSTRACT FROM PUBLISHER]

This paper focuses on the problem of moving target tracking with a group of mobile robots. Each robot in the group has a pan/tilt camera to detect the target and has limited communication capability to communicate with neighbor robots. The problem is solved by separating it into two parts. One part is the estimation of target position and another is the flocking control of multiple robots moving toward the estimated position. In the target estimation part, we propose to use a novel distributed Kalman filter to estimate the target position. The distributed Kalman filter is deduced based on a standard Kalman filter by modeling the neighbor's information as one of measurements. In the motion control part, a distributed flocking algorithm is developed. It is used to track the estimated target and avoid collision. In both parts, only local communication between neighbor robots is required. Finally, the tracking algorithms are simulated with 2-D and 3-D robots to verify their performance. The simulation results provide a firm conclusion that the proposed algorithms are able to track a moving target. A group of real ground mobile robots is used to test the proposed algorithm. The experiment results show that multiple robots are able to cooperate to track the target under the proposed algorithms and the tracking result outperforms the result produced by individual robots without cooperation. [ABSTRACT FROM PUBLISHER]

This paper presents a novel two-level scheme for adaptive active visual servoing of a mobile robot equipped with a pan camera. In the lower level, the pan platform carrying an onboard camera is controlled to keep the reference points lying around the center of the image plane. On the higher level, a switched controller is utilized to drive the mobile robot to reach the desired configuration through image feature feedback. The designed active visual servoing system presents such advantages as follows: 1) a satisfactory solution for the field-of-view problem; 2) global high servoing efficiency; and 3) free of any complex pose estimation algorithm usually required for visual servoing systems. The performance of the active visual servoing system is proven by rigorous mathematical analysis. Both simulation and experimental results are provided to validate the effectiveness of the proposed active visual servoing method. [ABSTRACT FROM AUTHOR]

This paper presents a pulsewidth modulation (PWM) algorithm for a three-phase ac–dc rectifier, where the third and fifth harmonics are indicated in the input phase voltages. A mathematical analysis, which includes this voltage harmonic's components, shows that the unity input displacement factor (IDF) can be reached by appropriate evaluation of duty-cycle functions. A PWM algorithm is proposed based on this developed theoretical achievement. This approach enables current sensorless unity IDF rectification. The PWM algorithm is investigated theoretically and verified by simulations and experiment. [ABSTRACT FROM PUBLISHER]

Digital ecosystems (DEs) are based on a large amount of distributed data, and these data are gathered from physical devices, particularly from wireless sensor networks (WSNs). Due to the inherent stringent bandwidth and energy constraints, energy-efficient mechanisms of performance measurement are the key to the proper operation of WSNs and thereby important for the data reliability of DEs. This paper presents a novel algorithm, i.e., Loss Inference based on Passive Measurement (LIPM), to infer WSN link loss performance. The LIPM algorithm passively monitors the application traffic between sensor nodes and the sink (base station), and then uses network tomography technology to infer the network internal performance. Furthermore, contour maps, the well-known representation of data, are first taken into account in WSN loss performance inference, which can help the LIPM algorithm identify lossy areas rapidly. Finally, the algorithm is validated through simulations and exhibits good performance and scalability. [ABSTRACT FROM AUTHOR]

This paper focuses on the benefits of adaptive control for permanent-magnet synchronous machines; a novel method of online parameter estimation for such machines has been developed. Two recursive least square algorithm segments, a fast and a slow one, are uniquely combined in real time with rich enough data from the machine to estimate all four machine parameters instead of a subset of these. Simulation and experimental results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Multiphase (more than three phases) drives exhibit interesting advantages over conventional three-phase drives. Over the last years, topics related to the extension of control schemes to these specific drives have been covered in depth in the literature. Direct torque control and predictive current control are normally used in conventional ac drives when fast electrical dynamic performance is required. In this paper, a one-step modulation predictive current control technique is proposed for asymmetrical dual threephase ac drives. Based on the use of a predictive model including the motor and the inverter, the control algorithm determines the switching state which minimizes errors between predicted and reference state variables. The period of application of the selected switching state is then obtained, resulting in a sub-modulation method. The proposed predictive current control algorithm uses a prediction horizon of one sampling period; however, two switching states are applied during the sampling period. The switching states are the selected optimum active vector and a null voltage combination. Simulation and experimental results are provided to examine the features of the control method. Performances, advantages, and limitations are also discussed. [ABSTRACT FROM AUTHOR]

Abstract-This paper presents a modulation technique based on the generalized pulsewidth-modulation strategy for matrix converters. The proposed technique uses a discontinuous modulation to clamp each output leg of the converter during 1200 of the output voltage period, achieving a reduced number of switchings compared with the traditional modulation techniques. Aside from that, the major attraction of the proposed technique is an additional algorithm that lags the clamping of each output leg of the converter to synchronize it with the peak of the corresponding output current (load current), avoiding high switching losses (switching at high currents). Therefore, this technique reduces the number of switchings as well as guarantees only medium and low current switchings. Simulation and experimental results show the efficiency of the proposed technique. [ABSTRACT FROM AUTHOR]

The control of a biped humanoid is a challenging task due to the hard-to-stabilize dynamics. Walking reference trajectory generation is a key problem. Linear Inverted Pendulum Model (LIPM) and Zero Moment Point (ZMP) Criterion-based approaches in stable walking reference generation are reported. In these methods, generally, the ZMP reference during a stepping motion is kept fixed in the middle of the supporting foot sole. This kind of reference generation lacks naturalness, in that the ZMP in the human walk does not stay fixed, but it moves forward under the supporting foot. This paper proposes a reference generation algorithm based on the LIPM and moving support foot ZMP references. The application of Fourier series approximation simplifies the solution, and it generates a smooth ZMP reference. A simple inverse kinematics-based joint space controller is used for the tests of the developed reference trajectory through full-dynamics 3-D simulation. A 12-DOF biped robot model is used in the simulations. Simulation studies suggest that the moving ZMP references are more energy efficient than the ones with fixed ZMP under the supporting foot. The results are promising for implementations. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new robust congestion- control strategy for a differentiated-services (DiffServ) network. A sliding-mode-based variable structure control technique is utilized to design a congestion controller on the basis of a fluid flow model. The performance of our proposed scheme is then demonstrated on a DiffServ network. Our proposed algorithm is developed for an interconnected network as a hop-by-hop distributed-control approach. A formal analysis of the controlled network is conducted, where it is shown that the error dynamics of the overall time-delay-dependent system is ℒ∞ stable. Numerical simulations are provided to demonstrate the capabilities of our proposed methodology. [ABSTRACT FROM AUTHOR]

This paper presents a model-based fault detection (FD) and isolation scheme for rigid manipulators. A single fault acting on a specific actuator or on a specific sensor of the manipulator is detected (and, if possible, the exact location of the fault), and an estimation of the fault signal is performed. Input-signal estimator and output observers are considered in order to make the FD procedure possible. By using the suboptimal second-order sliding-mode (SOSM) algorithm to design the input laws of the observers, satisfactory stability properties of the observation error are established. The proposed algorithm is verified in simulation and experimentally on a COMAU SMART3-S2 robot manipulator. [ABSTRACT FROM AUTHOR]

The aim of this paper is to spread the sliding-mode control design technique on the new class of the ac drives: an induction motor fed by a three-level voltage-source inverter (3LVSI). A comprehensive investigation of possible drive "variable structures" was carried out. Based on this analysis, an original two-step design procedure allows the use of the "classical" result of sliding-mode theory for the real variable structure system with more than 2m variable structures (m is the control space order). Based on this design procedure, the original control algorithm that includes a choice condition for 3LVSI input dc voltage and a switch table for the 3LVSI semiconductor switches are designed. The performance of the considered control structure has been examined by simulation. [ABSTRACT FROM AUTHOR]

This paper presents system modeling, analysis, and simulation of an electric vehicle (EV) with two independent rear wheel drives. The traction control system is designed to guarantee the EV dynamics and stability when there are no differential gears. Using two in-wheel electric motors makes it possible to have torque and speed control in each wheel. This control level improves EV stability and safety. The proposed traction control system uses the vehicle speed, which is different from wheel speed characterized by a slip in the driving mode, as an input. In this case, a generalized neural network algorithm is proposed to estimate the vehicle speed. The analysis and simulations lead to the conclusion that the proposed system is feasible. Simulation results on a test vehicle propelled by two 37-kW induction motors showed that the proposed control approach operates satisfactorily. [ABSTRACT FROM AUTHOR]

This paper studies the probability distribution functions of the parameters to be learned and optimized in biped gait generation. By formulating the gait pattern generation into a multiobjective optimization problem with consideration of geometric and state constraints, dynamically stable and low energy cost biped gaits are generated and optimized by the proposed method, namely Spline-based Estimation of Distribution Algorithm (EDA) with Q-learning updating rule (EDA̱S̱Q). Instead of assuming variables as independent ones, the relationship between them is exploited by formulating the corresponding probability models with the Catmull-Rom cubic spline function. Such kind of function is proved to be a suboptimal and adaptive realization of the cubic spline function and is capable of providing high- precision description. Moreover, the probability models are up- dated autonomously by Q-learning method, which is model-free and adaptive. Thus, EDA̱S̱Q can deal with complex probability distribution functions without a prior knowledge about the distribution. The biped gait generated by EDA̱S̱Q has been verified using the simulation model of a humanoid soccer robot Robo-Erectus. It also shows that EDA̱S̱Q can generate the desired biped gaits autonomously in short learning epochs. An interpretation of the transition probability distribution achieved by EDA̱S̱Q provides us easy understanding for biped locomotion and better control in humanoid robots. [ABSTRACT FROM AUTHOR]

In this paper, the five main formulations of the instantaneous reactive power theory have been chosen to study nonlinear load compensation. They are p - q original theory, d - q transformation, modified or cross-product formulation, p - q - r reference frame, and vectorial theory. The obtention of the compensation current according to each formulation has been established. Next, the behavior of an active power filter (APF) that is implemented with those different control algorithms has been studied. On one hand, a simulation platform with control, APF, and load has been built to test them. Results obtained in an unbalanced and nonsinusoidal three-phase four-wire system have been compared by means of the most adequate indexes. On the other hand, the APF control strategies have been implemented in an experimental platform constituted by a 20-kVA power inverter and a 400-MHz digital signal processing controller board. The final analysis shows that, in general, the five theories present a different behavior, which depends on supply voltage, with respect to distortion. However, all of them widely decrease the waveform distortion. Moreover, a more general compensation objective is possible. It obtains balanced and sinusoidal source current in any conditions of the supply voltage. [ABSTRACT FROM AUTHOR]

Multilevel inverters have emerged as attractive high-power medium-voltage power-conversion systems. They are mainly controlled with high-frequency pulsewidth-modulation methods. This is not suitable for very high-power application due to significant switching losses. This paper presents an adaptive duty-cycle modulation algorithm that reduces the switching frequency to a minimum necessary to fulfill the dynamic requirements of the system. Switching losses are, therefore, strongly reduced. This is achieved by using the slope of the voltage reference to adapt the modulation period to ensure that only one-step change between two voltage levels. Simulation and experimental results are presented for a nine-level cascaded inverter. Voltage waveforms obtained for variable frequencies and amplitudes show similar switching patterns, with a reduced and near-constant number of commutations per cycle, regardless of the reference frequency and amplitude. [ABSTRACT FROM AUTHOR]

This paper aims to achieve good performance for both the dc boost and the ac output voltage control of the Z-source inverter (ZSI). The algorithm to control linearly the capacitor voltage is suggested in order to improve the transient response for dc boost control of the ZSI. The peak value of the ac output voltage is used to control exactly the ac output voltage to its desired level. A modified space vector pulsewidth modulation scheme is applied to control the shoot-through time for boosting dc voltage. The proposed algorithms are verified with simulation and experiment with a 32-bit digital signal processor. [ABSTRACT FROM AUTHOR]

This paper presents a new approach in realizing various carrier-based pulsewidth-modulation techniques by a generalized control algorithm, which is referred to as the universal control algorithm and is obtained via unequal sharing of null states. The flexibility of such an approach allows one to easily and quickly control two-level inverters. Furthermore, this approach may be also extended with few changes to the control of multi- level inverters. The algorithm that is presented here for two-level voltage-source inverters (VSIs) also obtains efficient detection and management of both the linear and overmodulation ranges. In the overmodulation range, which is treated by using the α-β components of the reference-voltage space vector, the algorithm shows the advantage of lower calculation time, thus allowing one, if required, to increase the switching frequency. Several simulation runs have been performed, aiming to test the proposed procedure for both two-level and multilevel VSIs. Finally, the new algorithm was experimentally validated in the case of two-level inverters by using it in a VSI workbench that can carry out several experimental tests. [ABSTRACT FROM AUTHOR]

This paper presents a new model reference adaptive system (MRAS) speed observer for high-performance field-oriented control induction motor drives based on adaptive linear neural networks. It is an evolution and an improvement of an MRAS observer presented in the literature. This new MRAS speed observer uses the current model as an adaptive model discretized with the modified Euler integration method. A linear neural network has been then designed and trained online by means of an ordinary least-squares (OLS) algorithm, differently from that in the literature which employs a nonlinear backpropagation network (BPN) algorithm. Moreover, the neural adaptive model is employed here in prediction mode, and not in simulation mode, as is usually the case in the literature, with a consequent quicker convergence of the speed estimation, no need of filtering the estimated speed, higher bandwidth of the speed loop, lower estimation errors both in transient and steady-state operation, belier behavior in zero-speed operation at no load, and stable behavior in field weakening. A theoretical analysis of some stability issues of the proposed observer has also been developed. The OLS MRAS observer has been verified in numerical simulation and experimentally, and in comparison with the BPN MRAS one presented in the literature. [ABSTRACT FROM AUTHOR]