Voltage and reactive power control by particle swarm optimization considering control process

This paper presents a new approach to optimal voltage and reactive power control based on a particle swarm optimization (PSO). According to the proposed method, one controller is selected by PSO and the number of control actions to the convergence of the objective function is taken into account. Thus, this method can be used to design a control process. So far, no methods using PSO algorithms for a control process have been proposed. The effectiveness of the proposed method is demonstrated by application to 15‐bus and 118‐bus systems. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 151(1): 9–18, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20055     

Walking planning based on artificial vector field with prediction simulation for biped robot

This paper proposes a method for gait trajectory generation using an artificial vector field for stable walking for a biped robot. The tip of the robot while walking can often deviate from the desired trajectory as a result of the disturbances forced by unexpected outside factors. In our approach, though no prepared trajectory is specified a priori, the tip follows the artificial vectors designed in the workspace. Moreover, the prediction simulation is performed online. The simulator judges the stability under comparison with the present state and the prediction results, and then the gait parameters are adaptively improved in feedforward for the stable walk. The numerical and physical experimental results show the validity of the proposed method in a continuous walk. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 159(4): 54– 61, 2007; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20547     

A multiagent approach to distribution system restoration

This paper proposes a multiagent approach to decentralized power system restoration for a distribution system network. The proposed method consists of several feeder agents (FAGs) and load agents (LAGs). LAG corresponds to the customer load, while a FAG is developed to act as a manager for the decision process. From the simulation results, the proposed multiagent system was able to reach the right solution by making use of only local information. This means that the proposed multiagent restoration system is a promising approach to more large‐scale distribution networks. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 152(3): 21–28, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20065     

A new command governor architecture for transient response shaping

In this paper, we develop a control framework for stabilization and command following of nonlinear uncertain dynamical systems. The proposed methodology consists of a new command governor architecture and an adaptive controller. The command governor is a dynamical system that adjusts the trajectory of a given command to follow an ideal reference system capturing a desired closed‐loop dynamical system behavior in transient time. Specifically, we show that the controlled nonlinear uncertain dynamical system can approach the ideal reference system by choosing the design parameter of the command governor. In addition, an adaptive element is used to asymptotically assure that the error between the controlled nonlinear uncertain dynamical system and the ideal reference system is reduced in long term. Therefore, the proposed methodology not only has closed‐loop transient and steady‐state performance guarantees but can also shape the transient response by adjusting the trajectory of the given command with the command governor. We highlight that there exists a trade‐off between the adaptive controller's learning rate and the command governor's design parameter. This key feature of our framework allows rapid suppression of system uncertainties without resorting to a high learning rate in the adaptive controller. Furthermore, we discuss the robustness properties of the proposed approach with respect to high‐frequency dynamical system content such as measurement noise and ∕ or unmodeled dynamics. A numerical example is provided to demonstrate the efficacy of the proposed architecture. Copyright © 2012 John Wiley & Sons, Ltd.     

Multitrajectory dynamic tunneling algorithm for global optimization

Most of the actual optimization problems are large‐scale, nonlinear, and multipeaked (nonconvex). Furthermore, with the widespread use of high‐speed and large‐capacity computers as the background, it is felt necessary in recent years to derive a global solution for nonlinear and multipeaked optimization problems. It is one of the most important topics in optimization. This paper proposes a new dynamic tunneling algorithm with multitrajectories (Multitrajectory Dynamic Tunneling Algorithm) that is composed of two systems, an optimization system and a tunneling system. The numerical stability of the conventional dynamic tunneling algorithm is theoretically investigated and interaction between each trajectory of the tunneling system is introduced in order to improve search efficiency. The proposed algorithm is applied to 2‐variable and 10‐variable typical multipeaked nonlinear optimization problems. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 154(1): 47–58, 2006; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20171     

A basic study of adaptive particle swarm optimization

This paper points out that meta‐heuristics should have not only robustness and adaptability to problems with different structure but also adjustability of parameters included in their algorithms. Particle swarm optimization (PSO), whose concept began as a simulation of a simplified social milieu, is known as one of the most powerful optimization methods for solving nonconvex continuous optimization problems. Then, in order to improve adjustability, a new parameter is introduced into PSO on the basis of the proximate optimality principle (POP). In this paper, we propose adaptive PSO and the effectiveness and the feasibility of the proposed approach are demonstrated on simulations using some typical nonconvex optimization problems. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 151(3): 41–49, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20077     

Fast and precise positioning using sequential adaptive feedforward compensation for disturbance

This paper presents a performance improvement for trajectory tracking for fast‐response and high‐precision positioning using sequential adaptive compensation for disturbances. A mathematical disturbance model formulated and parametrized by an iterative learning process can estimate the actual disturbance, and the model can be sequentially adapted using the recursive least squares method so that it shows adaptivity to disturbance variations. The proposed positioning control approach involving disturbance modeling and compensation has been verified by experiments using a linear motor‐driven table system. © 2013 Wiley Periodicals, Inc. Electr Eng Jpn, 184(4): 52–63, 2013; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.22280     

Adaptive control strategy‐based reference model for spacecraft motion trajectory

In aerospace field, the economic realization of a spacecraft is one of the main objectives that should be accomplished by conceiving the optimal propulsion system and the best control algorithms. This paper focuses on the development of a viable adaptive control approach (ACA) for spacecraft motion trajectory (SMT). The proposed strategy involves the nonlinear mathematical model of SMT expressed in the central field, which is linearized by the Taylor expansion, and the second Lyapunov method to offer a high rate and unfailing performance in the functioning. The adaptive control system is composed of the cascade of adaptation loop and feedback control loop. When the spacecraft deviates from its reference trajectory model, the ACA acts on the control system to correct this deviation and follow the optimal reference trajectory. Therefore, when the states of the adjustable model are different from its reference values, then the error signal is provided as an input to the adaptation law, which contains the adaptation algorithm. The output will be the state variable feedback control matrix, which will be used to calculate the new control law vector. The efficiencies of the linearization procedure and the control approach are theoretically investigated through some realistic simulations and tests under MATLAB. The steady‐state errors of control between the reference model and the adjustable model of SMT converge to zero. Copyright © 2014 John Wiley & Sons, Ltd.     

State of circuit components in the behavioral framework

A general, rigorous but reasonably simple, and meaningful approach to the concept of state for circuit components is proposed in the behavioral framework. First, some basic notions of the behavioral setting (e.g., trajectory, event, universum of trajectories, admissible trajectory, and behavior) are recalled. Then, using the notion of trajectory concatenation, the forwards and backwards concatenation sets of an admissible trajectory are introduced, and the class of components with well‐ordered behavior is defined. Finally, for these components, the concept of state is established as the parametrization that rules the time‐dependent partition of the component behavior whose sets are closed under trajectory concatenation. To provide a clear and significant illustration of the theory, the state investigation of the class of the two‐terminal components whose behavior is generated by means of an ordinary differential relation of any order, linear, and with constant coefficients, is carried out in all details. This class includes, in particular, all compound one‐ports of the Classical Circuit Theory, that is, those made of customary resistors, capacitors, and inductors, coupled or not. Copyright © 2016 John Wiley & Sons, Ltd.     

Hebbian learning rule restraining catastrophic forgetting in pulse neural network

In this paper, a Hebbian learning rule restraining “catastrophic forgetting” is proposed on a pulsed neural network (PNN) with leaky integrate‐and‐fire neurons. The strong point of this learning rule is that a learning of new pattern does not destroy past ones, and that an efficient use of synapses is enabled. First, in order to consider the function of the learning rule, a fundamental experiment is carried out. Next, to compare the performance between the proposed learning rule and conventional ones on the application, simulation experiments are examined using autonomous behavior robots which are forced to learn concurrently two different environments. The results of the experiments show that the proposed learning rule clearly restrains “catastrophic forgetting” and enables working of more efficient than conventional PNN learning. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 151(3): 50–60, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10343     

An egg‐shaped diagram and its discrepancies in switched reluctance machines

Recently, switched reluctance motors have attracted attention from industries. It is a common practice to develop several test machines for performance evaluation. One way to make a comparison among several test machines is to draw an efficiency map in a speed and torque plane, but this is rather complicated. For an easy comparison, a machine parameter measurement with an egg‐shaped diagram has been proposed by the authors. In this method, it is possible to measure an inductance ratio, which indicates the saliency of switched reluctance machines. In this paper, a calculation of tolerance between theoretical egg‐shaped curves and measured powers is proposed. It is found that the tolerances are within 4% as a result of several test machines. Although discrepancies in instantaneous current waveforms and voltage phase angles are seen, the obtained machine parameters indicate an exact relation between input power and required apparent power. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 152(1): 61–71, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10286     

Estimation of output voltage for high‐speed,surface permanent magnet generator with large air gap length

This paper presents a method to estimate the output voltage of a high‐speed, surface permanent magnet generator with large air gap length at design stage. The output voltage is estimated by the induced electromotive force and the synchronous inductance obtained from the analytical results of the flux linkage using FEM. Also, a method to classify the synchronous inductance per causative factor is proposed. The air gap leakage inductance is not negligible in a large‐air‐gap machine like this generator. The validity of the proposed method has been proved by the measured values of a generator designed by this method, and the measured values also show that the output voltage of the generator is within the permissible range. The method proposed in this paper will be an effective tool to design a high‐speed, surface permanent magnet generator with large air gap length. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 153(2): 52–60, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20228     

Precise disturbance modeling for improvement of positioning performance

This paper presents a modeling methodology for unknown disturbances in mechatronics systems, based on disturbance estimation using an iterative learning process. In disturbance modeling, nonlinear frictions are specially handled as disturbances in the mechanisms, which mainly degrade trajectory control performance. Friction can be mathematically modeled by using learned estimation data as a function of the displacement, velocity. acceleration, and jerk of the actuator. This model has the distinctive feature that friction compensation can be achieved with a generalization capability for different conditions. The proposed positioning control approach with disturbance modeling and compensation has been verified by experiments using a table drive system on a machine stand. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 171(2): 31–39, 2010; Published online in Wiley InterScience ( www. interscience.wiley.com ). DOI 10.1002/eej.20928     

Adaptive trajectory tracking control of wheeled mobile robots with disturbance observer

In this paper, the trajectory tracking problem for a wheeled mobile robot in the presence of kinematic and dynamic uncertainties has been addressed. Uncertainties are modeled as lumped disturbances. A kinematic controller based on feedback linearization approach and a dynamic controller based on model reference adaptive control are designed in the presence of disturbances. In order to ensure both robustness and implementability of the controllers, the disturbances are estimated by a generalized linear matrix inequality‐based disturbance observer. Simulation results show the effectiveness of the proposed method. Copyright © 2013 John Wiley & Sons, Ltd.     

The design of TSK‐type fuzzy controllers using a new hybrid learning approach

In this paper, the TSK‐type fuzzy controllers with a novel hybrid learning approach (TFC‐HLA) are proposed. The proposed hybrid learning approach consists of the self‐clustering algorithm (SCA) and the dynamic‐form symbiotic evolution (DSE). First, the proposed SCA is used to identify a parsimonious internal structure. Secondly, the proposed DSE uses the sequential‐search‐based dynamic evolution method. Better combinations of the chromosomes will be initially generated while better mutation points will be determined to perform dynamic mutation. The advantages of the proposed learning algorithm are that, first, it converges quickly and the obtained fuzzy rules are more precise. Second, the proposed TFC‐HLA controller only requires a few population sizes. Third, the DSE constructs only four fuzzy controllers every generation. The performance of the TFC‐HLA controller compares excellently with other existing models in our control simulations. Copyright © 2005 John Wiley & Sons, Ltd.     

Synchronization of identical neural networks and other systems with an adaptive coupling strength

In this paper, a new scheme to synchronize linearly or nonlinearly coupled identical circuit systems, which include neural networks and other systems, with an adaptive coupling strength is proposed. Unlike other adaptive schemes that synchronize coupled circuit systems to a specified trajectory (or an equilibrium point) of the uncoupled node by adding negative feedbacks adaptively, here the new adaptive scheme for the coupling strength is used to synchronize coupled systems without knowing the final synchronization trajectory. Moreover, the adaptive scheme is applicable when the coupling matrix is unknown or time‐varying. The validity of the new adaptive scheme is also proved rigorously. Finally, several numerical simulations to synchronize coupled neural networks, Chua's circuits and Lorenz systems, are also given to show the effectiveness of the theory. Copyright © 2009 John Wiley & Sons, Ltd.     

Model and experience‐based initial input construction for iterative learning control

The initial choice of input in iterative learning control (ILC) generally has a significant effect on the error incurred over subsequent trials. In this paper, techniques are developed that use experimental data gathered over previous applications of ILC in order to generate an initial input signal for the tracking of a new reference trajectory. A model‐based approach is then incorporated to overcome the limitation of insufficient previous experimental data, and a robust design procedure is developed. Experimental evaluation results are obtained using a gantry robot facility. Copyright © 2010 John Wiley & Sons, Ltd.     

An active‐passive capacitor‐commutated converter for HVDC systems with a three‐phase voltage‐source PWM converter

This paper introduces a new approach to the capacitor‐commutated converters (CCCs) for HVDC systems. A small‐rated three‐phase voltage‐source PWM converter is connected between a series commutation capacitor and thyristor converter through matching transformers. The PWM converter acts as auxiliary commutation‐capacitor for the thyristor converter while the series passive capacitor acts as the main commutation capacitor. The capacitance, which is the sum of the small‐rated active and series passive capacitors, is variable, so that stable commutation is obtained. In CCCs, commutation failure occurs when the AC bus voltage is recovered whereas the proposed combined commutation‐capacitor can achieve successful commutation for both rapidly decreasing and increasing AC bus voltages. The basic principle of the proposed active–passive capacitor‐commutated converter is discussed in detail. Then, constant margin angle control with a constant firing angle of the thyristor converter is proposed using a function generator block. Digital simulation demonstrates the novelty and effectiveness of the proposed active–passive capacitor‐commutated converter. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 151(1): 66–75, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20030     

CNN‐based architecture for real‐time object‐oriented video coding applications

This paper presents a new CNN‐based architecture for real‐time video coding applications. The proposed approach, by exploiting object‐oriented CNN algorithms and MPEG encoding capabilities, enables low bit‐rate encoder/decoder to be designed. Simulation results using Claire video sequence show the effectiveness of the proposed scheme. Copyright © 2005 John Wiley & Sons, Ltd.