One of the main requirements for motion control systems is their robustness. There are several previously introduced control methods possessing the aforementioned requirement. The algorithms designed in acceleration control framework based on disturbance observer (DOB) belong to that group. The DOB introduced in eighties by Ohnishi and his group has been discussed considerably in the literature and applied in numerous applications. However, in majority of them, the control algorithms have been designed in continuous time domain, even though today they are almost always implemented on digital platforms. In addition, a discussion about discrete implementation of the designed algorithms, and influence of the parameters of discrete systems on the control performance, appeared only in several previous works. This paper aims to fill part of that gap, by discussing discrete implementation of the control algorithms which are well developed in continuous domain. The given results will provide an opportunity to give recommendations for engineers employing DOB-based control in practice.

Many effective robot-manipulator control schemes using a disturbance observer have been reported in the literature in the past decades. Besides, the disturbance observer combined with the Kalman filter has attracted the attention of researchers in the field of motion control. The major advantage of a motion control system based on the Kalman filter and disturbance observer is the realization of high robustness against disturbance and parameter variations, effective noise suppression and wideband force sensing. This paper presents a survey of motion control based on the Kalman filter and disturbance observer, which have been previously introduced by the authors. Several control schemes, as well as formulations and applications of the Kalman filter and disturbance observer, are described in the paper. The performance and effectiveness of the control schemes are evaluated to give a useful and comprehensive design of the Kalman filter and disturbance observer in various motion control applications.

This article presents a novel master-slave control configuration that is experimentally demonstrated to improve teleoperation performance under random network delay. This is achieved via the design of a proactive haptic sensing system based on a laser range sensor on the slave side, which in turn allows for the proactive transmission of force control from the master to the slave, thus compensating for Internet-based network delays. The proposed configuration introduces three main contributions to the literature of bilateral control systems: (1) fully decoupled position and force control systems, which allow for the controller gains of each loop to be tuned independently, eliminating the trade-off common to most previous literature; (2) a novel approach that exploits the slow variation nature of the environment parameters, resulting in a lower bandwidth requirement in comparison to previous force control methods; (3) capability to measure the slave environment location and the prediction of the contact force as a result, which provides the human operator with the capability to generate the reaction force proactively on the master side. The conducted experiments demonstrated a significantly improved performance in terms of synchronized forces and positions despite the random network delay between the master and slave systems.

Purpose This paper aims to propose a novel grid current control strategy for grid-connected voltage source converters (VSCs) under unbalanced grid voltage conditions. Design/methodology/approach A grid voltage dynamic model is represented in symmetrical positive and negative sequence reference frames. A proportional controller structure with a first-order low-pass filter disturbance observer (DOB) is designed for power control in unbalanced voltage conditions. This controller is capable of meeting the positive sequence power requirements, and it also eliminates negative sequence power components which cause double-frequency oscillations on power. The symmetrical components are calculated by using the second-order generalized integrator-based observer, which accurately estimates the symmetrical components. Findings Proportional current controllers are sufficient in this study in a wide range of operating conditions, as DOB accurately estimates and feed-forwards nonlinear terms which may be deteriorated by physical and operating conditions. This is the first reported scheme which estimates the VSC disturbances in terms of symmetrical component decomposition and the DOB concept. Originality/value The proposed method does not require any grid parameter to be known, as it estimates nonlinear terms with a first-order low-pass filter DOB. The proposed control system is implemented on a dSPACE ds1103 digital controller by using a three-phase, three-wire VSC.

This paper proposes a novel control method for voltage source converter (VSC) connected to grid under unbalanced voltage conditions. The method is based on utilizing the full control capabilities of the switching converter. The proposed method makes the voltage source inverter (VSI) supply the voltages according to the requirements of the load and/or grid. The method is tested with both the balanced and unbalanced cases of the grid. The grid's average voltage serves as the reference for the average voltage at the converter's output alongside the active and reactive power's set-point requirements. The mathematical formulation of the proposed method is given in detail and simulations are done in MATLAB/Simulink® to validate the effectiveness of the proposed method.

Purpose This paper aims to propose a robust cascaded controller based on proportional-integral (PI) and continuous sliding mode control. Design/methodology/approach Cascaded control structure is an attractive control scheme for DC-DC power converters. It has a two-loop structure where the outer loop contains PI controller and the inner loop uses sliding mode control (SMC). This structure thus combines the merits of both the control schemes. However, there are some issues that have prohibited its adoption in industry, the discontinuous nature of SMC which leads to variable switching frequency operation and is hard to realize practically. This paper attempts to overcome this issue by changing the discontinuous functionality of SMC to continuous by utilizing the concept of equivalent control. Findings The robustness of the controller designed is verified by considering various cases, namely, ideal case with no uncertainties, sudden variation of input supply voltage, load resistance, reference voltage, circuit-parameters and for noise disturbance. The controller effectiveness is validated by simulating the DC-DC boost and Cuk converters in SimPowerSystems toolbox of MATLAB/Simulink. It is shown that the performance of the proposed controller is satisfactory, and both reference output voltage and inductor current are tracked with little or no sensitivity to disturbances. Originality/value The results for various scenarios are interesting and show that the controller works quite satisfactorily for all the simulated uncertainties.

Purpose The purpose of this paper is to propose successive-over-relaxation (SOR) based recursive Bayesian approach (RBA) for the configuration identification of a Power System. Moreover, to present a comparison between the proposed method and existing RBA approaches regarding convergence speed and robustness. Design/methodology/approach Swift power network configuration identification is important for adopting the smart grid features like power system automation. In this work, a new SOR-based numerical approach is adopted to increase the convergence speed of the existing RBA algorithm and at the same time maintaining robustness against noise. Existing RBA and SOR-RBA are tested on IEEE 6 bus, IEEE 14 bus networks and 48 bus Danish Medium Voltage distribution network in the MATLAB R2014b environment and a comparative analysis is presented. Findings The comparison of existing RBA and proposed SOR-RBA is performed, which reveals that the latter has good convergence speed compared to the former RBA algorithms. Moreover, it is robust against bad data and noise. Originality value Existing RBA techniques have slow convergence and are also prone to measurement noise. Their convergence speed is effected by noisy measurements. In this paper, an attempt has been made to enhance convergence speed of the new identification algorithm while keeping its numerical stability and robustness during noisy measurement conditions. This work is novel and has drastic improvement in the convergence speed and robustness of the former RBA algorithms.

Purpose To propose an improved algorithm for the state estimation of distribution networks based on the unscented Kalman filter (IUKF). The performance comparison of unscented Kalman filter (UKF) and newly developed algorithm, termed Inproved unscented Kalman Filter (IUKF) for IEEE-30, 33 and 69-bus radial distribution networks for load variations and bad data for two measurement noise scenarios, i.e. 30% and 50% are shown. Design/methodology/approach State estimation (SE) plays an instrumental role in realizing smart grid features like distribution automation (DA), enhanced distribution generation (DG) penetration and demand response (DR). Implementation of DA requires robust, accurate and computationally efficient dynamic SE techniques that can capture the fast changing dynamics of distribution systems more effectively. In this paper, the UKF is improved by changing the way the state covariance matrix is calculated, to enhance its robustness and accuracy under noisy measurement conditions. UKF and propo...

This paper proposes a new approach on the novel current control strategy for grid-tied voltage-source inverters (VSIs) with circumstances of asymmetrical voltage conditions. A standard grid-connected inverter (GCI) allows the degree of freedom to integrate the renewable energy system to enhance the penetration of total utility power. However, restrictive grid codes require that renewable sources connected to the grid must support stability of the grid under grid faults. Conventional synchronously rotating frame dq current controllers are insufficient under grid faults due to the low bandwidth of proportional-integral (PI) controllers. Hence, this work proposes a proportional current controller with a first-order low-pass filter disturbance observer (DOb). The proposed controller establishes independent control on positive, as well as negative, sequence current components under asymmetrical grid voltage conditions. The approach is independent of parametric component values, as it estimates nonlinear feed-forward terms with the low-pass filter DOb. A numerical simulation model of the overall power system was implemented in a MATLAB/Simulink (2014B, MathWorks, Natick, MA, USA). Further, particular results show that double-frequency active power oscillations are suppressed by injecting appropriate negative-sequence currents. Moreover, a set of simulation results provided in the article matches the developed theoretical background for its feasibility.

Penetration of grid connected inverters (GCI) has arisen in power systems due to increasing integration of renewable sources. However, restrictive grid codes require that renewable sources connected to the grid with power electronic systems must be properly connected and appropriate currents must be injected to support stability of the grid under grid faults. Simultaneous injection of symmetrical positive and negative sequence currents is mandatory to support stabilization of grid at the instant of grid faults. Conventional synchronously rotating frame dq current controllers are insufficient under grid faults due to low bandwidth of PI controllers. This paper proposes a new grid current control strategy for grid connected voltage source inverters under unbalanced grid voltage conditions. A proportional current controller with a first order low pass filter disturbance observer (DOb) is proposed which establishes positive sequence power requirements and independently control negative sequence current components under unbalanced voltage conditions. The method does not need any parameter, since it estimates nonlinear terms with low pass filter DOb. Simulations are implemented in Matlab/Simulink platform demonstrating the effectiveness of proposed method.

Abstract State estimation is an integral component of energy management systems used for the monitoring and control of operation of transmission networks worldwide. However, it has so far not yet been widely adopted in the distribution networks due to their passive nature with no active generation. But this scenario is challenged by the integration of distributed generators (DGs) at this level. Various static and dynamic state estimators have been researched for the transmission systems. These cannot be directly applied to the distribution systems due to their different philosophy of operation. Thus the performance of these estimators need to be re-evaluated for the distribution systems. This paper presents a computational and statistical performance of famous static estimator such as weighted least squares (WLS) and dynamic state estimators such as extended Kalman filter (EKF) and unscented Kalman filter (UKF) for electric distribution system. Additionally, an improved-UKF (IUKF) is also proposed which enhances the robustness and numerical stability of the existing UKF algorithm. All the estimators are tested for load variation and bad data for IEEE-30, 33 and 69 bus radial distribution networks using statistical performance metrics such as Maximum Absolute Deviation (MAD), Maximum Absolute Percent Error (MAPE), Root Mean Square Error (RMSE) and Overall Performance index (J). Based on these metrics, IUKF outperforms other estimators under the simulated noisy measurement conditions.

1 Department of Electrical and Electronics Engineering, University of Johannesburg, Auckland Park, South Africa; eemreozsoy@yahoo.co.uk 2 Department of Industrial Engineering, University of Salerno, Salerno 84084, Italy; psiano@unisa.it (P.S.); fiazahmad@sabanciuniv.edu (F.A.) 3 Mechatronics Engineering, Faculty of Engineering and Natural Sciences, Sabancı University, Istanbul 34956, Turkey; akhtar@sabanciuniv.edu (R.A.); asif@sabanciuniv.edu (A.S.) 4 Department of Management & Innovation Systems, University of Salerno, Salerno 84084, Italy; loia@unisa.it * Correspondence: sanjeevi_12@yahoo.co.in, Tel.: +27-79-219-9845, psiano@unisa.it, Tel.: +39-08-996-4294