Long‐span seek control system for hard disk drive without mode‐switching

In hard disk drives (HDD) there are two control modes: the head positioning control mode and the other is the seek control mode. In the head positioning control mode, a feedback controller is optimally designed to suppress disturbances. In the long‐span seek mode, a velocity feedback control system is applied in order to move the heads fast. Thus, an HDD has multiple control systems, and the head is moved to the target position while changing from one control system to the other. However, changing the control system causes a discontinuous control signal, which activates the resonant mode of an actuator. Past methods can only decrease discontinuous control, and therefore a single control system that can be used for both a seek control mode and a head positioning control mode is necessary for a narrow track pitch. In the proposed method, the feedback controller is decomposed into an integrator and a phase compensator. The VCM model is updated by the output of the phase compensator, and the integrator and the output of the velocity feedback controller control the VCM. The validity of the proposed method was confirmed by numerical and experimental results using a miniature 2.5‐inch hard disk drive. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 171(3): 51–60, 2010; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20935     

A hybrid current controller for dual three‐phase permanent magnet synchronous motors

Control of the current harmonics is a critical issue for dual three‐phase (DTP) permanent magnet synchronous motors (PMSMs). Considering the limitations of conventional synchronous frame proportional‐integral (PI) current regulator, this paper presents a hybrid current controller that combines the PI current regulator with a multiresonant controller. With the proposed hybrid current controller, precise current control can be achieved with only a slight increase in the computational effort. Theoretical analysis and experimental results confirm the effectiveness of proposed current controller. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Robust self‐tuning PI decoupling control of uncertain multivariable systems

In this paper, for a class of multivariable systems with strong couplings, a robust self‐tuning PI decoupling controller is developed by combining a self‐tuning PI controller with a feedforward decoupling compensator and a filter. To determine the gains and other parameters of the PI decoupling controller, we first introduced a reduced order model. The parameters of the reduced order model are identified by using a normalized projection algorithm with dead zone. The gains of the PI controller together with other parameters are tuned online according to the certainty equivalent principle. By resorting to time‐varying operation, we presented the bounded‐input bounded‐output stability conditions and convergence conditions of the closed‐loop system. Simulation results on a synthetic system and a twin‐tank level system show the effectiveness of the proposed method. Copyright © 2011 John Wiley & Sons, Ltd.     

Comments on ‘comparison of architectures and robustness of model reference adaptive controllers and L1‐adaptive controllers’

In a recent paper it is claimed that adding a filter at the plant input to a classical direct model reference adaptive control constitutes a ‘new architecture’ for adaptive control. The purpose of this note is to show that this claim is specious. Towards this end, we bring to the readers attention the some recent results where a rigorous mathematical analysis shows that the resulting control signal always converges to the output of a linear time‐invariant proportional plus integral (PI) controller, whose gains are independent of the plant parameters. Moreover, it is shown that if the PI controller does not stabilize the plant, the proposed controller will not stabilize it either, making unnecessary the addition of the adaptation. Copyright © 2015 John Wiley & Sons, Ltd.     

Null‐space‐based optimal control reallocation for spacecraft stabilization under input saturation

A novel saturated proportional‐derivative control incorporated with null‐space‐based optimal control reallocation is proposed for spacecraft attitude stabilization in the presence of disturbance and input saturation. More specifically, a saturated proportional‐derivative based baseline nonlinear controller is firstly developed to guarantee the globally asymptotic stability under input constraints and external disturbance. This is achieved with inexpensive online computations by dynamically adjusting a single parameter to ensure the desired performance. Then, a novel null‐space‐based optimal control reallocation method is employed to map the specified virtual control command to the redundant actuators. The optimal control solution is obtained by penalizing the control allocation errors at a lower power/energy cost using quadratic programming algorithm. The benefits of the proposed control method are analytically authenticated and also validated via simulation study. Copyright © 2014 John Wiley & Sons, Ltd.     

Anti‐windup synthesis for a model predictive control system

In this paper, an anti‐windup design problem for a model predictive control system is studied. The plant is assumed to be stable. First, we propose the structure of an output feedback model predictive controller with an anti‐windup compensator. Then we show a design method of the anti‐windup compensator that guarantees closed‐loop stability and improves the transient response. The design problem of the anti‐windup compensator is reduced to a linear matrix inequality (LMI) optimization problem. Further, it is shown that there always exists an anti‐windup compensator that ensures global asymptotic stability. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Model‐based feedforward compensation for disturbance during inching and reciprocating motions

This paper presents a feedforward compensation approach for nonlinear disturbances in ball‐screw‐driven table positioning systems. The compensator design is focused on minimizing the effects of nonlinear disturbances on positioning performance. This is achieved through the use of a mathematical model of precise micrometer disturbance characteristics produced by nonlinear spring behaviors during inching and reciprocating motions. Based on this model, feedforward disturbance compensation is applied in order to improve the disturbance suppression capability. The effectiveness of the proposed positioning control approach has been verified by experiments using a table drive system on a machine stand. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 174(3): 34–44, 2011; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21054     

Robust backstepping controller for grid‐side converter of DFIG‐based wind energy conversion systems

A robust backstepping controller with nonlinear damping is designed for the grid‐side converter (GSC) of a grid‐connected doubly fed induction generator (DFIG) in wind energy conversion systems (WECSs). The designed controller achieves the exponential ultimate boundedness of both the DC‐link voltage and GSC current errors with an arbitrarily fast decay rate and an arbitrarily small bound in the presence of both model uncertainties and time‐varying external disturbances. A desirable feature that distinguishes the proposed controller from other existing controllers is that the control input of GSC is constructed only by the static feedback of the measurable states. As a result, the control input becomes smooth and easy to implement without requiring differentiation or switching operations. The exponential boundedness and performance of the designed controller are demonstrated by simulation using a 1.5‐MW DFIG‐based WECS model built in MATLAB/SimPowerSystems and compared with a standard proportional‐integral controller. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Finite‐model adaptive control using an LS‐like algorithm

Adaptive control problem of a class of discrete‐time nonlinear uncertain systems, of which the internal uncertainty can be characterized by a finite set of functions, is formulated and studied by using an least squares (LS)‐like algorithm to design the feedback control law. For the finite‐model adaptive control problem, this algorithm is proposed as an extension of counterpart of traditional LS algorithm. Stability in sense of pth mean for the closed‐loop system is proved under a so‐called linear growth assumption, which is shown to be necessary in general by a counter‐example constructed in this paper. The main results have been also applied to parametric cases, which demonstrate how to bridge the non‐parametric case and parametric case. Copyright © 2006 John Wiley & Sons, Ltd.     

Self‐tuning PID control of a brushless DC motor by adaptive interaction

In this paper, a self‐tuning algorithm for proportional integral derivative (PID) control based on the adaptive interaction (AI) approach theory efficiently used in artificial neural networks (ANNs) is proposed. In this approach, a system is decomposed into interconnected subsystems, and adaptation occurs in the interaction weights among these subsystems. The principle behind the adaptation algorithm is mathematically equivalent to a gradient descent algorithm. The same adaptation as the well‐known backpropagation algorithm (BPA) can be achieved without the need of a feedback network, which would propagate the errors, by applying adaptive interaction. Thereby, the ANN controller can be adapted directly without wasting calculation time in order to increase the frequency response of the controller. The velocity control of a brushless DC motor (BLDCM) under slowly and rapidly changing load conditions is simulated to demonstrate the effectiveness of the algorithm. The AI tuning algorithm was used to tune up the PID gains, and the simulation results with PID adaptation process are presented by comparing the obtained results with the adaptive PID controller based on BPNN and a conventional PID controller. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Global adaptive regulation control for a class of nonlinear systems with unknown control coefficients

This paper is concerned with the global asymptotic regulation control problem for a class of nonlinear uncertain systems with unknown control coefficients. The allowed class of uncertainties include unmeasured input‐to‐state stable (ISS) and/or weaker integral ISS (iISS) inverse dynamics, parametric uncertainties, and uncertain nonlinearities. By using the Nussbaum‐type gain technique and changing the ISS/integral ISS inverse dynamics supply rates, we design a dynamic output feedback controller which could guarantee that the system states are asymptotically regulated to the origin from any initial conditions, and the other signals are bounded in closed‐loop systems. The numerical example of a simple pendulum with all unknown parameters and without velocity measurement illustrates our theoretical results. The simulation results demonstrate its efficacy. Copyright © 2015 John Wiley & Sons, Ltd.     

Neural‐hybrid control of systems with sandwiched dead‐zones

The control of systems that have sandwiched nonsmooth nonlinearities, such as a dead‐zone sandwiched between two dynamic blocks, is addressed. An adaptive inverse control scheme using a hybrid controller structure and a neural network based inverse compensator, is proposed for such systems with unknown sandwiched dead‐zone. This neural‐hybrid controller consists of an inner loop discrete‐time feedback structure incorporated with an adaptive inverse using a neural network for the unknown dead‐zone, and an outer‐loop continuous‐time feedback control law for achieving desired output tracking. The dead‐zone compensator consists of two neural networks, one used as an estimator of the sandwiched dead‐zone function and the other for the compensation itself. The compensator neural network has neurons that can approximate jump functions such as a dead‐zone inverse. The weights of the two neural networks are tuned using a modified gradient algorithm. Simulation results are given to illustrate the performance of the proposed neural‐hybrid controller. Copyright © 2002 John Wiley & Sons, Ltd.     

Decentralized model predictive‐based load‐frequency control in an interconnected power system concerning wind turbines

This paper presents a load‐frequency control (LFC) design using the model predictive control (MPC) technique in a multi‐area power system in the presence of wind turbines (WTs). In the studied system, the controller of each local area is designed independently such that the stability of the overall closed‐loop system is guaranteed. A frequency response model of the multi‐area power system including WTs is introduced, and physical constraints of the governors and turbines are considered. The model was employed in the MPC structures. Digital simulations for a two‐area power system are provided to validate the effectiveness of the proposed scheme. The results show that with the proposed MPC technique the overall closed‐loop system performance shows robustness in the face of uncertainties due to governor and turbine parameter variation and load disturbances. A performance comparison between the proposed controller with WTs and MPC without WTs and a classical integral control scheme is carried out, confirming the superiority of the proposed MPC technique with WTs. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Application of a sinusoidal internal model to current control of three‐phase utility interface converters

Three‐phase voltage‐source converters are used as a utility interface. In such a case, the converter line currents are required to track sinusoidal references synchronized with the utility grid without steady‐state error. In this paper a current control method based on a sinusoidal internal model is employed. The method uses a sine transfer function with a specified resonant frequency, which is called an S compensator. The combination of a conventional PI compensator and an S compensator is called a PIS compensator. The PIS compensator ensures that the steady‐state error in response to any step changes in a reference signal at the resonant frequency and zero hertz reduces to zero. An experiment was carried out using a 1‐kVA prototype of three utility interface converters, a voltage‐source rectifier, an active power filter, and STATCOM. Almost perfect current tracking performance can be observed. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 150(3): 54–61, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20064     

Improved static and dynamic performances of a two‐cell DC–DC buck converter using a digital dynamic time‐delayed control

Multi‐cell converters have been developed to overcome shortcomings in usual switching devices. The control system in these circuits is twofold: first, to balance voltages of the switches and second to regulate the load current to a desired value. However, with a purely proportional controller, the system presents a static error. With a PI controller the static error is annihilated, but at the expense of shortening the stability region and increasing settling time. In this work, a zero static error dynamic controller for a two‐cell DC–DC buck converter is designed. To achieve zero current error, we propose a generalized scheme of a dynamic controller. Then, using nonlinear analysis and Lyapunov stability theory and bifurcation prediction tools, we prove that zero static error is achieved. The proposed controller outperforms the PI controller in terms of settling time in the presence of saturating effect during the start‐up transients. Numerical simulations in the form of time domain waveforms and bifurcation diagrams from switched circuit‐based model are presented to confirm our theoretical results. Copyright © 2010 John Wiley & Sons, Ltd.     

Adaptive B‐spline neural network‐based vector control for a grid side converter in wind turbine‐DFIG systems

This paper presents a novel control system design for the grid‐side converter of doubly fed induction generator wind power generation systems. The control method proposed in this work is a vector control based on adaptive B‐spline neural network by using a simple fixed‐gain stabilizing control topology. The adaptive control is designed both for inner current loops and an outer DC‐link voltage loop of the grid side converter control system. To guarantee the control stability, the weights updating rule for the B‐spline neural network is synthesized by utilizing Lyapunov's direct method. To verify the effectiveness of the proposed control system, extensive simulations are performed using MATLAB/Simulink. Based on the simulation results, it is concluded that the proposed controller has improved performance compared to an optimum proportional integral control system. It is also relatively robust against external disturbances and variations of the control parameters. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Optimal control of a single‐phase H‐bridge DC–AC inverter

The control of switched power converters has been mostly accomplished using pulse width modulation (PWM). Under this type of control, it has been shown in literature that DC–AC current mode single‐phase inverter may exhibit chaotic behavior if the proportional controller of the PWM modulator is badly tuned. In this work, we present a novel method to control the inverter using an optimal control approach. Our method consists in defining the switching instances in order to achieve the reference current with minimum error. To illustrate the efficiency of our proposed method, numerical simulations and comparison with the proportional and integral controller as well as to the proportional and resonant controller are presented. Copyright © 2015 John Wiley & Sons, Ltd.     

MIMO multi‐periodic repetitive control system: universal adaptive control schemes

This paper presents a simple adaptive multi‐periodic repetitive control scheme when the MIMO LTI plant is not necessarily positive real (PR), however it is strictly minimum‐phase, the spectrum of high‐frequency gain matrix CB is symmetric and lies in the open right/left half complex plane(sign/spectrum definite). The non‐identifier‐based direct adaptive control technique, which does not need plant parameter information, is used to construct adaptive schemes and the system stability is analysed by Lyapunov second method. The extension to plant under certain non‐linear perturbations and an exponential stability scheme are also discussed. Finally, an adaptive proportional plus multi‐periodic repetitive control scheme is proposed. The theoretical findings are supported with simulations. Copyright © 2006 John Wiley & Sons, Ltd.     

Online data‐driven composite adaptive backstepping control with exact differentiators

This paper presents an online data‐driven composite adaptive backstepping control for a class of parametric strict‐feedback nonlinear systems with mismatched uncertainties, where both tracking errors and prediction errors are utilized to update parametric estimates. Hybrid exact differentiators are applied to obtain the derivatives of virtual control inputs such that the complexity problem of integrator backstepping can be avoided. Closed‐loop tracking error equations are integrated in a moving‐time window to generate prediction errors such that online recorded data can be utilized to improve parameter adaptation. Semiglobal asymptotic stability of the closed‐loop system is rigorously established by the time‐scales separation and Lyapunov synthesis. The proposed composite adaptation can not only avoid the application of identification models and linear filters resulting in a simpler control structure, but also suppress parametric uncertainties and external perturbations via the time‐interval integral. Simulation results have demonstrated that the proposed approach possesses superior control performances under both noise‐free and noisy‐measurement environments. Copyright © 2015 John Wiley & Sons, Ltd.     

Robust adaptive output‐feedback control for a class of nonlinear systems with time‐varying actuator faults

A robust adaptive output‐feedback control scheme is proposed for a class of nonlinear systems with unknown time‐varying actuator faults. Additional unmodelled terms in the actuator fault model are considered. A new linearly parameterized model is proposed. The boundedness of all the closed‐loop signals is established. The desired control performance of the closed‐loop system is guaranteed by appropriately choosing the design parameters. The properties of the proposed control algorithm are demonstrated by two simulation examples. Copyright © 2010 John Wiley & Sons, Ltd.