Modern Electrical Drives: Trends, Problems, and Challenges

Modern electrical drives possess many advantages. Electrical energy, compared to other sources, is easy to transport and can be environmentally friendly (if it comes from renewable sources). Electrical drives convert energy with high efficiency and have flexible control characteristics. They offer a wide range of speed, torque, and power operations. Furthermore, in general, they can serve as electrical generators

Artificial Neural Network-Based Gain-Scheduled State Feedback Speed Controller for Synchronous Reluctance Motor

This paper focuses on designing a gain-scheduled (G-S) state feedback controller (SFC) for synchronous reluctance motor (SynRM) speed control with non-linear inductance characteristics. The augmented model of the drive with additional state variables is introduced to assure precise control of selected state variables (i.e. angular speed and d-axis current). Optimal, non-constant coefficients of the controller are calculated using a linear-quadratic optimisation method. Non-constant coefficients are approximated using an artificial neural network (ANN) to assure superior accuracy and relatively low usage of resources during implementation. To the best of our knowledge, this is the first time when ANN-based gain-scheduled state feedback controller (G-S SFC) is applied for speed control of SynRM. Based on numerous simulation tests, including a comparison with a signum-based SFC, it is shown that the proposed solution assures good dynamical behaviour of SynRM drive and robustness against q-axis inductance, the moment of inertia and viscous friction fluctuations

Efficient Local Path Planning Algorithm Using Artificial Potential Field Supported by Augmented Reality

Mobile robots in industry are commonly used in warehouses and factories. To achieve the highest production rate, requirements for path planning algorithms have caused researchers to pay significant attention to this problem. The artificial potential field algorithm, which is a local path planning algorithm, has been previously modified to obtain higher smoothness of path, to solve the stagnation problem and to jump off the local minimum. The last itemized problem is taken into account in this paper—local minimum avoidance. Most of the modifications of artificial potential field algorithms focus on a mechanism to jump off a local minimum when robots stagnate. From the efficiency point of view, the mobile robot should bypass the local minimum instead of jumping off it. This paper proposes a novel artificial potential field supported by augmented reality to bypass the upcoming local minimum. The algorithm predicts the upcoming local minimum, and then the mobile robot’s perception is augmented to bypass it. The proposed method allows the generation of shorter paths compared with jumping-off techniques, due to lack of stagnation in a local minimum. This method was experimentally verified using a Husarion ROSbot 2.0 PRO mobile robot and Robot Operating System in a laboratory environment

Auto-Tuning Process of State Feedback Speed Controller Applied for Two-Mass System

The state feedback controller is increasingly applied in electrical drive systems due to robustness and good disturbance compensation, however its main drawback is related to complex and time consuming tuning process. It is particularly troublesome for designer, if the plant is compound, nonlinear elements are taken into account, measurement noise is considered, etc. In this paper the application of nature-inspired optimization algorithm to automatic tuning of state feedback speed controller (SFC) for two-mass system (TMS) is proposed. In order to obtain optimal coefficients of SFC, the Artificial Bee Colony algorithm (ABC) is used. The objective function is described and discussed in details. Comparison with analytical tuning method of SFC is also included. Additionally, the stability analysis for the control system, optimized using the ABC algorithm, is presented. Synthesis procedure of the controller is utilized in Matlab/Simulink from MathWorks. Next, obtained coefficients of the controller are examined on the laboratory stand, also with variable moment of inertia values, to indicate robustness of the controller with optimal coefficients

Parallel computing applied to auto-tuning of state feedback speed controller for PMSM drive

Nowadays the simulation is inseparable part of researcher's work. Its computation time may significantly exceed the experiment time. On the other hand, multi-core processors can be used to reduce computation time by using parallel computing. The parallel computing can be employed to decrease the overall simulation time. In this paper the parallel computing is used to speed-up the auto-tuning process of state feedback speed controller for PMSM drive

PMSM Servo-Drive Fed by SiC MOSFETs Based VSI

The article presents modern PMSM servo-drive with SiC MOSFETs power devices and microprocessor with ARM Cortex core. The high switching frequency is obtained due to the application of high efficient power switching components and powerful microprocessor. It allows to achieve good dynamical properties of current control loop, proper disturbance compensation and silent operation of servo-drive. Experimental tests results obtained for two different control schemes (i.e., cascade control structure and state feedback position control) are presented

Improved Fixed-Frequency SOGI Based Single-Phase PLL

In this paper, an improved single-phase second order generalized integrator (SOGI) fixed-frequency phase-locked loop (FFPLL) is presented. The proposed improvement comprises the modification of the PLL input signal estimated phase angle correction factor, which is in this paper calculated and implemented with the exactly accurate value, while in the existing literature the approximated correction value is employed. Also, in this paper, the FFPLL with DC offset is presented, together with the corresponding estimated angle correction technique. Furthermore, the PLL with the positive sequence separation is outlined, based on the new FFPLL structure. The proposed technique is analyzed and verified by simulation and experimental runs, which proved the accuracy and efficiency of the proposed PLL technique. Furthermore, a corresponding PLL parameter values tuning procedure is presented that illustrates the dynamic performance improvements that SOGI based FFPLL introduces when compared with SOGI based PLL. Consequently, FFPLL combined with the proposed new estimated angle correction factor represents a significant improvement when compared to the conventional SOGI based PLL

State Feedback Speed Control with Periodic Disturbances Attenuation for PMSM Drive

This paper proposes an auto-tuned constrained state-feedback controller (SFC) to attenuate periodic disturbances present in permanent magnet synchronous (PMSM) motor drives. An online auto-tuning process of SFC has been made using a powerful nature-inspired optimization algorithm—artificial bee colony (ABC)—to achieve high-performance operation of the drive. A novel performance index is proposed to minimize the impact of pulsating torque and obtain smooth-velocity of the drive. The proposed approach is a practical application of classic control theory with novel engineering-tools for improving the operational quality of a PMSM drive system. The obtained results are compared with a classical cascade control structure (CCS) based on proportional-integral (PI) regulators and disturbance observer-based control (DOBC). A detailed time- and frequency-domain analysis has been conducted in respect to periodic disturbances present in a PMSM drive system. Moreover, the robustness of SFC against parameter variations of inductance and resistance has been tested

Improved Fixed-Frequency SOGI Based Single-Phase PLL

In this paper, an improved single-phase second order generalized integrator (SOGI) fixed-frequency phase-locked loop (FFPLL) is presented. The proposed improvement comprises the modification of the PLL input signal estimated phase angle correction factor, which is in this paper calculated and implemented with the exactly accurate value, while in the existing literature the approximated correction value is employed. Also, in this paper, the FFPLL with DC offset is presented, together with the corresponding estimated angle correction technique. Furthermore, the PLL with the positive sequence separation is outlined, based on the new FFPLL structure. The proposed technique is analyzed and verified by simulation and experimental runs, which proved the accuracy and efficiency of the proposed PLL technique. Furthermore, a corresponding PLL parameter values tuning procedure is presented that illustrates the dynamic performance improvements that SOGI based FFPLL introduces when compared with SOGI based PLL. Consequently, FFPLL combined with the proposed new estimated angle correction factor represents a significant improvement when compared to the conventional SOGI based PLL