Multiple characteristic model‐based golden‐section adaptive control: Stability and optimization

The characteristic model‐based golden‐section adaptive control (CM‐GSAC) law has been developed for over 20 years in China with a broad range of applications in various fields. However, quite a few theoretical problems remain open despite its satisfying performance in practice. This paper revisits the stability of the CM‐GSAC from its very beginning and explores the underlying implications of the so‐called golden‐section parameter l₂≈0.618. The closed‐loop system, which consists of the CM and the GSAC, is a discrete time‐varying system, and its stability is discussed from three perspectives. First, attentions have been paid to select the optimal controller coefficients such that the closed‐loop system exhibits the best transient performance in the worst case. Second, efforts are made to improve the robustness in the presence of parameter estimation errors, which provide another choice when designing the adaptive controller. Finally, by measuring the slowly time‐varying nature in an explicit inequality form, a bridge is built between the instantaneous stability and the time‐varying stability. In order to relax the constraints on the parameter bounds of the CM, the GSAC is further extended to multiple CMs, which shows more satisfying tracking performance than that of the traditional multiple model adaptive control method. Copyright © 2014 John Wiley & Sons, Ltd.     

Finite‐time prescribed performance adaptive fuzzy fault‐tolerant control for nonstrict‐feedback nonlinear systems

This paper focuses on a finite‐time adaptive fuzzy control problem for nonstrict‐feedback nonlinear systems with actuator faults and prescribed performance. Compared with existing results, the finite‐time prescribed performance adaptive fuzzy output feedback control is under study for the first time. By designing performance function, the transient performance of the corresponding controlled variable is maintained in a prescribed area. Combining the finite‐time stability criterion with backstepping technique, a feasible adaptive fault‐tolerant control scheme is proposed to guarantee that the system output converges to a small neighborhood of the origin in finite time, and the closed‐loop signals are bounded. Finally, simulation results are shown to illustrate the effectiveness of the presented control method.     

Formation control of multiple nonholonomic mobile robots

Tracking control problem of multiple mobile robots is considered. Our system is composed of a reference and follower robots of unicycle type. The robots are assumed to satisfy pure rolling and nonslipping conditions, which lead to nonholonomic constraints. The purpose is to control the followers so that the reference is tracked with arbitrary desired clearance and also to avoid interrobot collisions. To accomplish this goal, we first introduced a virtual robot (VR) tracking control to establish and maintain the formation when no collision is detected. VR is an ideal robot fixed with each follower and helps in simplifying the control, as the tracking error becomes zero in the final stage. During the process, if the possibility of collision is detected, a collision avoidance technique (l?ψ or l?l control) will be applied to the lower priority robot. The result of this control gives a monotonic convergence in an internal shape of distance variables, which enables us to predict the movement of the robots during this control and leads to collision‐free movement. These processes are repeated until the desired motion is accomplished. Simulation results prove the efficiency of our control techniques. © 2006 Wiley Periodicals, Inc. Electr Eng Jpn, 157(3): 81–88, 2006; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20192 Copyright © 2006 Wiley Periodicals, Inc.     

Accommodation of unknown actuator faults using output feedback‐based adaptive robust control

In this paper, we solve the problem of output tracking for linear uncertain systems in the presence of unknown actuator failures using discontinuous projection‐based output feedback adaptive robust control (ARC). The faulty actuators are characterized as unknown inputs stuck at unknown values experiencing bounded disturbance and actuators losing effectiveness at unknown instants of time. Many existing techniques to solve this problem use model reference adaptive control (MRAC), which may not be well suited for handling various disturbances and modeling errors inherent to any realistic system model. Robust control‐based fault‐tolerant schemes have guaranteed transient performance and are capable of dealing with modeling errors to certain degrees. But, the steady‐state tracking accuracy of robust controllers, e.g. sliding mode controller, is limited. In comparison, the backstepping‐based output feedback adaptive robust fault‐tolerant control (ARFTC) strategy presented here can effectively deal with such uncertainties and overcome the drawbacks of individual adaptive and robust controls. Comparative simulation studies are performed on a linearized Boeing 747 model, which shows the effectiveness of the proposed scheme. Copyright © 2011 John Wiley & Sons, Ltd.     

Development of a large‐current high‐precision pulse power supply

JAEA and KEK are jointly constructing a high‐intensity proton accelerator project J‐PARC. Its main accelerator is a 3‐GeV synchrotron. Its injection bump magnets, especially horizontal paint bump magnets, are excited by large pulse currents. Their rated currents are over 10 kA and pulse widths are about 1 ms. Tracking errors are required to be less than 1%. Multiple connected two‐quadrant IGBT choppers are adopted for their power supplies. Their output currents are controlled by feedback control with minor loop voltage control (m‐AVR). When output current of a chopper intermits at small current, its output voltage rises and current control becomes difficult. In this paper, response of m‐AVR and output voltage characteristics at current intermittent region are studied and an improved control scheme is proposed. The performance is confirmed by a test. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 166(3): 62– 72, 2009; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20783     

Neural‐network‐based finite‐time H∞ control for extended Markov jump nonlinear systems

This paper presents a neural‐network‐based finite‐time H_∞ control design technique for a class of extended Markov jump nonlinear systems. The considered stochastic character is described by a Markov process, but with only partially known transition jump rates. The sufficient conditions for the existence of the desired controller are derived in terms of linear matrix inequalities such that the closed‐loop system trajectory stays within a prescribed bound in a fixed time interval and has a guaranteed H_∞ noise attenuation performance for all admissible uncertainties and approximation errors of the neural networks. A numerical example is used to illustrate the effectiveness of the developed theoretic results. Copyright © 2009 John Wiley & Sons, Ltd.     

Optimal model‐free control for a generic MIMO nonlinear system with application to autonomous mobile robots

In this paper, the design procedure for optimal model‐free control algorithm is presented for the tracking problem of completely unknown nonlinear dynamic systems operating under unknown disturbances. The procedure includes a new structure in the context of model‐free control and data‐driven control algorithms. In the new structure, the unknown nonlinear functions are segmented into 1 unknown linear‐in‐states part and another unknown nonlinear part. The adaptive laws proposed for estimating the unknown system dynamics are regressor‐free estimation methods in which there is no need for regressor parameters and, consequently, the persistent excitation condition is not required anymore. Moreover, the main controller gains are updated online, incorporating the adapted values of linear terms in the system dynamics. A comparative study is presented to show that the proposed optimal model‐free control outperforms the state‐of‐the‐art model‐free control algorithms. In addition, the simulation results for the application of the algorithm on autonomous mobile robots are provided.     

Neural adaptive robust output feedback control of wheeled mobile robots with saturating actuators

This paper addresses the output feedback tracking control problem of electrically driven wheeled mobile robots subjected to actuator constraints. The main drawback of previously proposed controllers is the actuator saturation problem, which degrades the transient performance of the closed‐loop control system. In order to alleviate this problem, a saturated tracking controller has been proposed using the hyperbolic tangent function. A new nonlinear observer is introduced in order to leave out the velocity sensors in the robot system to decrease the cost and weight of the system for practical applications. A dynamic surface control strategy is effectively used to reduce the design complexity when considering actuator dynamics. In addition, neural network approximation capabilities and adaptive robust techniques are also adopted to improve the tracking performance in the presence of uncertain nonlinearities and unknown parameters. Semi‐global stability of the closed‐loop system is presented using direct Lyapunov method. Simulation results are provided to illustrate the effectiveness of the proposed control system for a differential drive mobile robot in practice. Copyright © 2014 John Wiley & Sons, Ltd.     

High‐speed and high‐precision position control using a sliding mode compensator

To achieve high‐speed, high‐precision position control for semiconductor product machines and industrial robots, full‐closed feedback control is applied. Many control methods have been proposed for such a system. In general, proportional position control and proportional plus integral velocity control or integral plus proportional velocity control (P,PI/I‐P), which is a type of proportional plus integral plus differential control (PID), is applied in many industrial applications. However, in the case of changing mechanical characteristics of the control target, the parameters of P,PI/I‐PI control must also change in order to maintain good motion performance. In this paper, we propose a new P,PI/I‐P control method that includes a nonlinear compensator. The algorithm of the nonlinear compensator is based on sliding mode control with chattering compensation. The effectiveness of the proposed control method is evaluated using a full‐closed single‐axis slider system via point‐to‐point control and contour control in the case of changing load. The experimental results indicate that the proposed control method is robust in the case of changing acceleration/deceleration of control reference, changing load, and low‐velocity contour motion. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 174(2): 65–71, 2011; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21011     

Adaptive robust output‐feedback motion control of hydraulic actuators

Most previous advanced motion control of hydraulic actuators used full‐state feedback control techniques. However, in many cases, only position feedback is available, and thus, there are imperious demands for output‐feedback control for hydraulic systems. This paper firstly transforms a hydraulic model into an output feedback–dependent form. Thus, the K‐filter can be employed, which provides exponentially convergent estimates of the unmeasured states. Furthermore, this observer has an extended filter structure so that online parameter adaptation can be utilized. In addition, it is a well‐known fact that any realistic model of a hydraulic system suffers from significant extent of uncertain nonlinearities and parametric uncertainties. This paper constructs an adaptive robust controller with backstepping techniques, which is able to take into account not only the effect of parameter variations coming from various hydraulic parameters but also the effect of hard‐to‐model nonlinearities such as uncompensated friction forces, modeling errors, and external disturbances. Moreover, estimation errors that come from initial state estimates and uncompensated disturbances are dealt with via certain robust feedback at each step of the adaptive robust backstepping design. After that, a detailed stability analysis for the output‐feedback closed‐loop system is scrupulously checked, which shows that all states are bounded and that the controller achieves a guaranteed transient performance and final tracking accuracy in general and asymptotic output tracking in the presence of parametric uncertainties only. Extensive experimental results are obtained for a hydraulic actuator system and verify the high‐performance nature of the proposed output‐feedback control strategy.     

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.     

Decentralized adaptive multi‐dimensional Taylor network tracking control for a class of large‐scale stochastic nonlinear systems

This paper investigates the problem of adaptive multi‐dimensional Taylor network (MTN) decentralized tracking control for large‐scale stochastic nonlinear systems. Minimizing the influence of randomness and complex nonlinearity, which increases computational complexity, and improving the controller's real‐time performance for the stochastic nonlinear system are of great significance. With combining adaptive backstepping with dynamic surface control, a decentralized adaptive MTN tracking control approach is developed. In the controller design, MTNs are used to approximate nonlinearities, the backstepping technique is employed to construct the decentralized adaptive MTN controller, and the dynamic surface control technique is adopted to avoid the “explosion of computational complexity” in the backstepping design. It is proven that all the signals in the closed‐loop system remain bounded in probability, and the tracking errors converge to a small residual set around the origin in the sense of a mean quartic value. As the MTN contains only addition and multiplication, the proposed control method is more simplified and of good real‐time performance, compared with the existing control methods for large‐scale stochastic nonlinear systems. Finally, a numerical example is presented to illustrate the effectiveness of the proposed design approach, and simulation results demonstrate that the method presented in this paper has good real‐time performance and control quality, and the dynamic performance of the closed‐loop system is satisfactory.     

A novel quasi‐Z‐source indirect matrix converter

A new type of three‐phase quasi‐Z‐source indirect matrix converter (QZS‐IMC) is proposed in this paper. It uses a unique impedance network for achieving voltage‐boost capability and making the input current in continuous conduction mode (CCM) to eliminate the input filter. The complete modulation strategy is proposed to operate the QZS‐IMC. Meanwhile, a closed‐loop DC‐link peak voltage control strategy is proposed, and the DC‐link peak voltage is estimated by measuring both the input and capacitor voltages. With this proposed technique, a high‐performance output voltage control can be achieved with an excellent transient performance even if there are input voltage and load current variations. The controller is designed by using the small‐signal model. Vector control scheme of the induction motor is combined with the QZS‐IMC to achieve the motor drive. A QZS‐IMC prototype is built in laboratory, and experimental results verify the operating principle and theoretical analysis of the proposed converter. The simulation tests of QZS‐IMC based inductor motor drive are carried out to validate the proposed converter's application in motor drive. Copyright © 2013 John Wiley & Sons, Ltd.     

Transient performance improvement of model reference adaptive control: LMI‐based resetting

In this paper, a resetting mechanism is proposed to enhance the transient performance of model reference adaptive control. While the suggested method has a simple structure, it is capable of taking into account both the desired steady‐state behavior and the transient response, simultaneously. Whenever the transient specification is not satisfying, there is a jump in the controller parameters. This jump is determined by designing an optimal reset law. At the reset times, the after‐reset values of parameters are calculated based on a minimization problem. The considered cost function is a mixed H₂/H_∞ criterion, which minimizes the tracking error. The optimization problem is converted to an LMI formulation, and the reset law is designed by solving this LMI at certain reset times. To verify the effectiveness of the proposed approach, simulation results are presented.     

Online trained support vector machines‐based generalized predictive control of non‐linear systems

In this work, an online support vector machines (SVM) training method (Neural Comput. 2003; 15 : 2683–2703), referred to as the accurate online support vector regression (AOSVR) algorithm, is embedded in the previously proposed support vector machines‐based generalized predictive control (SVM‐Based GPC) architecture (Support vector machines based generalized predictive control, under review), thereby obtaining a powerful scheme for controlling non‐linear systems adaptively. Starting with an initially empty SVM model of the unknown plant, the proposed online SVM‐based GPC method performs the modelling and control tasks simultaneously. At each iteration, if the SVM model is not accurate enough to represent the plant dynamics at the current operating point, it is updated with the training data formed by persistently exciting random input signal applied to the plant, otherwise, if the model is accepted as accurate, a generalized predictive control signal based on the obtained SVM model is applied to the plant. After a short transient time, the model can satisfactorily reflect the behaviour of the plant in the whole phase space or operation region. The incremental algorithm of AOSVR enables the SVM model to learn the new training data pair, while the decremental algorithm allows the SVM model to forget the oldest training point. Thus, the SVM model can adapt the changes in the plant and also in the operating conditions. The simulation results on non‐linear systems have revealed that the proposed method provides an excellent control quality. Furthermore, it maintains its performance when a measurement noise is added to the output of the underlying system. Copyright © 2006 John Wiley & Sons, Ltd.     

Force‐based disturbance observer for dynamic force control and a position/force hybrid controller

In this paper, a force‐based disturbance observer (DOB) and a force control system using the DOB are proposed to obtain dynamic force control under disturbances. A DOB can reduce the effect of disturbances and modeling errors on robots. In a conventional DOB, an acceleration response is fed back to a reference, enabling highly precise position control. In other words, the effect of disturbances is decreased by emphasizing the effect of inertial forces. When a force controller is implemented, however, inertial forces are regarded as disturbances respect to a force response. Because inertial forces increase according to the acceleration, conventional DOBs are not suitable for dynamic force control. In the proposed DOB, a force response is fed back instead of an acceleration response. The effect of inertial forces is thus eliminated, thereby improving the tracking performance of force controllers. The proposed method's validity is verified analytically and experimentally. A position/force hybrid controller and a DOB for the controller are proposed as an extension of the proposed DOB. A bilateral controller is given as an example of the proposed hybrid controller, and its tracking performance is demonstrated experimentally. © 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

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.     

Adaptive motion/force tracking control of holonomic constrained mechanical systems: a unified viewpoint

This paper proposes a robust adaptive motion/force tracking controller for holonomic constrained mechanical systems with parametric uncertainties and disturbances. First, two types of well‐known holonomic systems are reformulated as a unified control model. Based on the unified control model, an adaptive scheme is then developed in the presence of pure parametric uncertainty. The proposed controller guarantees asymptotic motion and force tracking without the need of extra conditions. Next, when considering external disturbances, control gains are designed by solving a linear matrix inequality (LMI) problem to achieve prescribed robust performance criterion. Indeed, arbitrary disturbance/parametric error attenuation with respect to both motion and force errors along with control input penalty are ensured in the L₂‐gain sense. Finally, applications are carried out on a two‐link constrained robot and two planar robots transporting a common object. Numerical simulation results show the expected performances. Copyright © 2006 John Wiley & Sons, Ltd.     

Transient performance improvement in indirect model reference adaptive control using perturbation‐based extremum seeking identifier

One of the main drawbacks of model reference adaptive control (MRAC) is the weakness of its transient performance. The key reason of this imperfection is parameter's estimation error convergence. For many cases in the closed‐loop control, the plant input signal cannot satisfy the persistence of excitation (PE) condition which yields poor parameters estimation error convergence. In this paper, we use a fast perturbation‐based extremum seeking (PES) scheme without steady‐state oscillation as the parameter identifier in indirect MRAC. The estimated parameters through the PES identifier contain the additive sinusoidal signals with distinct frequencies in the transient, which satisfy the PE condition of the plant input. Therefore, convergence of the parameters estimation error to zero will be guaranteed that results in improvement of transient performance for indirect MRAC. Also, the contrary effects on the steady‐state behaviour is eliminated since the sinusoidal excitation signals amplitude exponentially converge to zero and reinitiate with every change in the unknown parameters. Simulation results for a second order example have been presented to illustrate the effectiveness of the proposed scheme.     

Multiple‐model adaptive robust dynamic surface control with estimator resetting

A multiple‐model adaptive robust dynamic surface control with estimator resetting is investigated for a class of semi‐strict feedback nonlinear systems in this paper. The transient performance is mainly considered. The multiple models are composed of fixed models, one adaptive model, and one identification model that can be obtained when the persistent exciting condition is satisfied. The transient performance of the final tracking system can be improved significantly by designing proper switching mechanism during the parameter tuning procedure. The semi‐globally uniformly ultimately bounded stability of the closed‐loop system can be easily achieved because of the framework of adaptive robust dynamic surface control. Numerical examples are provided to demonstrate the effectiveness of the proposed multiple‐model controller. Copyright © 2014 John Wiley & Sons, Ltd.