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In the presence of system coupling and dynamic uncertainties, extensive research has been conducted on the precise motion control of industrial manipulators with general reference trajectories. Since repetitive operations are common tasks in industrial applications, it is an essential and practical problem to further improve the control accuracy by taking advantage of the periodicity of the reference trajectory. In this paper, a desired compensation adaptive robust repetitive control is proposed for multi-DoFs industrial manipulators to perform repetitive tasks. Specifically, the link dynamics identified offline is compensated directly to decouple the system and capture the main characteristics of the link effect. Then, the uncertain friction is dealt with through an online adaptation scheme, in which the desired compensation is utilized to avoid measurement noise and chattering at low speed. And periodic disturbances are approximated by Fourier series expansion with unknown Fourier coefficients, which will be learned online. Finally, the robust feedback is designed to guarantee transient control accuracy and robustness against dynamic uncertainties. Comparative experiments on an industrial manipulator show that the proposed controller possesses better transient and steady-state control accuracy and error convergence rate.

Since the observed angle of a phase-locked loop (PLL) is relatively accurate even under distorted grid conditions, the mathematical model of the voltage errors caused by the switching modulation and the dead-time effect are derived as a function of the grid voltage angle in this paper. Based on the model analysis, an adaptive compensation algorithm is proposed to suppress the grid-side current harmonics in three-phase converters. The proposed algorithm fits the unmeasurable voltage errors by a truncated Fourier series expansion, and then takes it as an equivalent disturbance in the current control loop to achieve harmonic compensation. By the feed-forward compensation, the design and tuning of the controller parameters are simplified and separated from the dynamic performance. In addition, the controller can adapt to the grid frequency variation by updating the grid voltage angle with the PLL block. To reduce the computational burden, a simplified version of the proposed method is also presented. Simulation and experiment results show that the proposed methods can suppress the current harmonics and achieve better performance in terms of total harmonic distortion, strong robustness and insensitivity to the grid frequency variations, compared with the traditional PI control or repetitive control strategy.

This paper investigates the issue of fault-tolerant and anti-disturbance attenuation for a two-dimensional modified repetitive control system (2D MRCS) which is described by switched fuzzy systems with multiple disturbances. In particular, the multiple disturbances contain an exogenous disturbance and standard Wiener noise. Specifically, a generalized extended state observer (GESO) is incorporated with the 2D MRCS to estimate both fault and exogenous multiple disturbances so that the disturbances and faults can be attenuated in the control input. Further, the improved 2D MRCS relaxes the stability condition and provides an enhanced tracking performance. Based on the Lyapunov function approach, pole placement technique and average dwell time approach, the stability criteria for the considered system is developed in terms of linear matrix inequality (LMI). Then an algorithm for designing a GESO-based 2D MRC design is developed based on the obtained LMIs. Further, the results developed are validated in the simulation section through three numerical examples.

This paper concerns with the issues of designing an improved-equivalent-input-disturbance (IEID) based robust two dimensional modified repetitive control (2D MRC) for a class of fuzzy systems in the presence of aperiodic disturbances. Specifically, IEID-estimator is implemented to the 2D MRC systems that estimates all types of disturbances and compensates them for assuring robust stability. In particular, the proposed 2D MRC system has two different type of behaviours such as continuous control and discrete learning independently. To obtain gains of the observer and the controller, an adequate set of robust stability conditions is derived in the form of a linear-matrix-inequalities. Finally, simulation results for three numerical examples are provided to depict the efficacy of the proposed control technique.

A robust control scheme with low-voltage ride-through ability is presented for grid-connected photovoltaic converters that operate under harsh conditions such as voltage sags and unknown disturbances and parameters. The proposed strategy allows for flexible active and reactive power injection into the grid during asymmetrical voltage sags without using a phase-locked loop or positive and negative sequence components. In addition, the same controllers are used under both normal operation and voltage sags, thus, lowering the control system's complexity. The scheme is conceived by combining uncertainty-and-disturbance-estimation compensation and repetitive control for the dc voltage and phase currents, respectively. Controller design is carried out systematically and closed-loop stability is proven through Lyapunov's analysis. Several simulation case studies are presented using the SimPowerSystemsTM toolbox of MATLAB/Simulink computing environment to demonstrate the performance of the proposed control system under voltage sags, unknown disturbances, abrupt changes in operating conditions, and parametric uncertainties.

In this paper, a three-phase, two stage, bidirectional off board plug-in Electric Vehicle (PEV) charger controller has been designed and implemented in real time. The proposed PEV charger is able to work in all four quadrants in active–reactivepower plane. Generally, power electronics converters are controlled by PI regulators in d-q reference frame, where the signals to be regulated are inherently DC in nature. These controllers are implemented in two loops i.e., Slow (outer) control loop and fast (inner) control loop. Setting the gains of outer loops are little bit easier in comparison to fast acting inner loops besides the involvement of decoupling terms to have independent operation of active and reactive current components. Therefore, a repetitive controller (RC) is designed to regulate the inner sinusoidal reference current having both active–reactive​ components as per the control requirement without involving any decoupling terms. The RC is well known for their ability to track periodic signal and inherently based on internal model control theory. However, the major problem with RC is its sensitivity due to which it provides high gains at all frequencies levels. Therefore, in proposed controller the sensitivity of RC is modified by squaring it. This results the deep notches at higher frequency levels This approach is found to be very much suitable for the compensation of reactive power and load current harmonics. This also helps to exclude unwanted frequencies which results reduction in THD level. Therefore, the main contribution of this paper is adapting such robust EV charger controller for harmonic compensation. Moreover, from the implementation, it is found that the conventional RC is capable to compensate load current harmonic to some extent but it takes around 140 μ s computational time. However, the proposed RC takes around 100 μ s computational time, this results the grid current purely sinusoidal. The MATLAB/Simulink environment has been used to simulate proposed PEV charger controller, further it has been verified on scaled down experimental prototype.

In this paper, the synchronized output regulation (SOR) problem of leader-following heterogeneous linear networked systems aiming at tracking periodical signals is investigated. Only the output information of each agent is delivered throughout the communication network. For tracking a general periodic signal consisting many sinusoid functions, the dimension of the internal model compensator embedded in each agent will be too high to be implemented in practice. To cope with this difficulty, a distributed repetitive control method is proposed in this paper. A stability condition is developed, as well as the bound of error size. Then it is shown that the controller always exists for any given bound of tracking error. At last, the efficacy of analytic results is illustrated by simulation examples.

It can be challenging to design and implement Model Predictive Control (MPC) schemes in systems with fast dynamics. As MPCs often introduce high computational loads, it can be hard to assure real-time properties required by the dynamic system. An understanding of the system’s behavior, to exploit system properties that can benefit real-time implementation is imperative. Moreover, MPC implementations on embedded local devices rarely allows flexibility to changes in model and control philosophy, due to increased complexity and computational loads. A change in control philosophy (run-time) can be quite relevant in power systems that can change from an integrated to a segregated state. This paper proposes a distributed control hierarchy with a real-time MPC implementation, designed as a higher-level control unit, to feed a lower-level control device with references. The higher-level control unit’s objective in this paper is to generate the control reference of an Active Power Filter for system-level harmonic mitigation. In particular, a novel system architecture, which incorporates the higher-level MPC control and handles distribution of control action to low-level controllers, as well as receiving measurements used by the MPC, is proposed to obtain the application’s real-time properties and control flexibility. The higher-level MPC control, which is designed as a distributed control node, can be swapped with another controller (or control philosophy) if the control objective or the dynamic system changes. A standard optimization framework and standard software and hardware technology is used, and the MPC is designed on the basis of repetitive and distributed control, which allows the use of relatively low control update rate. A simulator architecture is implemented with the aim of mimicking a Hardware-In-Loop (HIL) simulator test to evaluate the application’s real-time properties, as well as the application’s resource usage. The results demonstrates that the implementation of the harmonic mitigation application exhibits the real-time requirements of the application with acceptable resource usage.

Conventional repetitive control has proven to be an effective strategy to reject/track periodic signals with constant frequency; however, it shows poor performance in varying frequency applications. This paper proposes an active disturbance rejection methodology applied to a large class of uncertain flat systems for the tracking and rejection of periodic signals, in which the possibilities of the generalized proportional integral (GPI) observer-based control to address repetitive control problems are studied. In the proposed scheme, model uncertainties and external disturbances are lumped together in a general additive disturbance input that is estimated and rejected on-line. An illustrative case study of mechatronic nature is considered. Experimental results show that the proposed GPI observer-based control successfully rejects periodic disturbances even under varying speed conditions.

Grid-connected inverters with LCL filters need high steady-state control accuracy, fast dynamic response performance, and strong robustness to guarantee the power quality. However, there are many problems in traditional control strategies that restrict improvements to control system performance, such as poor dynamic performance of traditional single-repetitive control, large ripples, low steady-state accuracy of inverter current feedback based repetitive dual-loop control or grid-current feedback based single-loop proportional-integral control. In this paper, a novel dual closed-loop repetitive control strategy based on grid current feedback is proposed for single-phase grid-connected inverters with LCL filters. The proportional-integral inner loop is stabilized by using an inherent one-beat delay achieved by digital controller. Based on the inner loop system, a detailed design scheme of a repetitive controller is presented, through which direct control of the grid current is realized, the reference is tracked perfectly to a zero phase shift, and high-attenuation gain is achieved in the high frequency range. In particular, the gird-voltage feed forward control and current reference feedforward control are adopted to suppress grid-voltage disturbance and increase dynamic tracking performance. Finally, the simulation and experimental results show that the proposed method has the advantages of high steady-state accuracy, fast dynamic response, and anti-disturbance ability.

This paper presents a frequency identification and disturbance rejection scheme for open loop stable time delay systems with disturbance containing a constant signal and a single sinusoidal signal. Astrom's modified Smith predictor is employed to maintain good setpoint tracking performance. Disturbance rejection controller is designed via internal model control principle and functions as a finite dimensional repetitive controller. Extended Kalman filter is designed to track the frequency of unknown periodic disturbance. The simulation results demonstrate the successful performance of the proposed disturbance rejection method for controlling a linear system with time delays, subjected to both step and sinusoidal disturbances.

In an optical disk drive servo system, to attenuate the external periodic disturbances induced by inevitable disk eccentricity, repetitive control has been used successfully. The performance of a repetitive controller greatly depends on the bandwidth of the low-pass filter included in the repetitive controller. However, owing to the plant uncertainty and system stability, it is difficult to maximize the bandwidth of the low-pass filter. In this paper, we propose an optimality based repetitive controller design method for the track-following servo system with norm-bounded uncertainties. By embedding a lead compensator in the repetitive controller, both the system gain at periodic signal's harmonics and the bandwidth of the low-pass filter are greatly increased. The optimal values of the repetitive controller's parameters are obtained by solving two optimization problems. Simulation and experimental results are provided to illustrate the effectiveness of the proposed method.

This paper proposes a sliding-mode repetitive learning control (SMRLC) scheme with an integral sliding-mode perturbation observer (ISMPO) for repetitive tracking control tasks. The three control strategies which are synthesized to yield excellent tracking performance are: (1) the pole-placement feedback control to specify the desired error dynamics; (2) ISMPO-based feedback compensation as the robust part; and (3) a feedforward learning component that refines the control to improve system performance through repetitive trials. The ISMPO-based feedback compensation ensures that there is only small tracking error during initial learning trials and enhances system insensitivity to exceptional and aperiodic disturbances. The feedforward learning compensation is updated according to a certain switching signal that is equivalent to the compensation error of the feedforward control, yielding fast convergence of the learning process from trial to trial. Experimental results demonstrate the feasibility of the proposed scheme.

This paper proposes a new method for automatic tuning of the Smith predictor controller based on a Repetitive Control (RC) approach. The method requires the input of a periodic reference signal which can be derived from a relay feedback experiment. A modified repetitive control scheme repetitively changes the control signal to achieve tracking error convergence. Once a satisfactory performance is achieved through the learning control, the parameters of the Smith predictor controller can be computed from the signals using a nonlinear least squares algorithm. The same relay feedback experiment can provide an initial parameter vector for an efficient implementation of the parameter estimation. Simulations and experimental results will be furnished to illustrate the effectiveness of the proposed tuning method.

This paper concerns the design of a robust observer-based modified repetitive-control system for a class of strictly proper plants with periodic time-varying uncertainties. It exploits the inherent structure characteristics of repetitive control to convert the design problem to a robust stabilization problem for a continuous-discrete two-dimensional system. The singular-value decomposition and Lyapunov stability theory are used to derive a linear-matrix-inequality-based design algorithm for the parameters of control and state-observer gains. Two tuning parameters are introduced to perform the preferential adjustment of control and learning. A numerical example illustrates the adjusting procedure and demonstrates the validity of the method.