Manuel R. Arahal

Switching losses make up for a notable portion of all losses in converter-supplied electric drives. Control algorithms such as Finite State Model Predictive Control (FSMPC) have tackled this issue in different ways; in particular incorporating a switching penalty to the cost function. This, however, results in an optimization problem with increased computational load, restricting the attainable sampling frequency for a given computing hardware. Recently, fast algorithms have been developed that reduce the computational load. However they cannot incorporate the switching penalty term. This paper explores a way around this problem for the particular case of stator current control of a five-phase induction motor. The proposal achieves fast computation even if a term for switching frequency reduction is present in the cost function. Experimental results show how stator current tracking performance is affected in both the torque producing plane and the harmonic subspace.

The area of Finite State Model Predictive Control (FSMPC) has seen a rapid development in recent years. In particular, its application to multiphase induction machine drives has received attention due to the specific advantages of such systems. The FSMPC method has been shown to be flexible thanks to the combination of a model and a cost function. However, the selection of the weighting coefficients in the cost function remains an obstacle for practitioners. Existing tuning methods for weighting coefficients require a large dataset obtained by extensive experimentation. In this paper, a cascaded structure providing a means for cost function self tuning is proposed. Tests are conducted with a five-phase induction machine connected to a mechanical load. The results show that, for each speed and load, the cascaded structure yields weighting coefficients with improved results.

This paper presents a comprehensive review and comparative evaluation of Fault Current Limiter (FCL) technologies for enhancing the Low-Voltage Ride-Through (LVRT) capability of Wind Turbine Generation Systems (WTGSs). Among various hardware solutions, FCLs have emerged as a particularly efficient and cost-effective approach to limit high fault currents and ensure grid code compliance. While the application of individual FCL types has been explored in the literature, a comparative analysis encompassing their technologies, inherent trade-offs, and performance insights remains lacking. To address this gap, this work examines the application of key FCL categories, including superconducting FCLs (SFCLs), resonance-type FCLs (RFCLs), and solid-state FCLs (SSFCLs), in both fixed-speed and variable-speed WTGS configurations. The paper synthesizes technological principles, assesses practical trade-offs (e.g., cost, response speed, scalability), and discusses critical insights derived from simulation-based comparisons. The consolidated findings aim to guide the selection, design, and future development of FCL solutions to enhance robust LVRT and provide reliable protection for modern wind power systems.

Recently, different techniques have been proposed for the scheduling and loading problems in cooling plants with chillers in a parallel configuration. Two broad groups can be considered: the online control-based group and the offline optimization-based group. The first group is exemplified by Model Predictive Control, where the selection of control moves provides a solution to both scheduling and loading. The second group includes Optimal Chiller Loading and Optimal Chiller Sequencing algorithms. They usually derive operating plans with some lead time in a batch-like fashion for long horizons. Both groups use forecasts of important factors such as the cooling demand and ambient conditions; hence, they have to deal with inaccuracies in the forecasts. In this paper, a comparison among these two groups is made considering demand uncertainties. The severity of the uncertainty is shown to play a role in the results as well as the controller tuning in the case of the predictive approach. The results are favorable to OCS with respect to overall consumption (up to 15%) but uses more on/off changes in the chiller’s operation (double in some cases).

Modern electric machines are attracting the greatest interest from the research community due to their current increasing number of applications, including electric vehicles and wind power generators. Their use requires the development of complex regulators, where predictive controllers appear as interesting and viable alternatives in recent research works. Although these controllers have an easy formulation and high flexibility to incorporate different control objectives in multidimensional systems, they have limitations that require attention and limit their application: a high computational cost and current harmonic content. This work presents a novel controller that focuses on these limitations, where the additional degree of freedom introduced in the predictive controller through the lead-pursuit guidance law concept is combined with the use of virtual voltage vectors to reduce the harmonic content in a controlled drive. The effectiveness of the proposed controller is explored using a five-phase drive and several figures of merit, such as the root mean square error in current tracking, the total harmonic distortion in the stator currents, and the number of switching commutations per cycle. Different predictive controllers are compared with the proposal in terms of speed regulation, stator current control, and steady-state performance, where the results obtained are analyzed to show the interest, improvements, and limitations of the proposal.

Predictive stator current control (PSCC) is a flexible technique that has been the subject of research in connection with multiphase drives. The flexibility that the cost function (CF) brings finds an obstacle in CF tuning. Intensive trial and error tests are usual in this context. In this article, an adaptive procedure is proposed based on the concept of model reference adaptive control. Unlike previous methods, the proposal provides on-line tuning of PSCC with very little burden. The proposal is motivated by the idea of using optimal weighting factors (WFs) for each operating point. A case study is developed for a six-phase induction machine. The adaptive method includes cross terms and momentum to cope with irregularities in the derivatives with respect to the WF. It is shown that adaptiveness allows crossing the Pareto front of performance indicators. This provides flexibility without optimality loss. The proposal is assessed with real experimentation on a laboratory set-up.

Variable speed drives are often controlled by a double-loop scheme in which a proportional integral controller takes on the speed loop. The tuning of this loop is a complex job. In most cases just mechanical variables are considered for tuning. This paper presents a new Pareto analysis incorporating mechanical and electrical variables. A state of the art finite state model predictive controller is used for stator current control. The analysis is performed using experimental data from a five-phase induction motor and considers considering commonly found performance indicators derived from experimental data. The results show undocumented connections between those performance indicators. The analysis not only helps in PI tuning but, more importantly, prompts for a revision of the methods usually utilized to report performance enhancements of new methods.

Variable-speed electrical drive control typically relies upon a two-loop scheme, one for torque/speed and another for stator current control. In modern drive control methods, the actual mechanical speed is needed for both loops. In practical applications, the speed is often acquired by incremental rotary encoders. The most used method derives speed from an encoder pulse count during a fixed amount of time. It is known that this sensing method produces time delay in the speed feedback loop as well as fluctuations in the speed measurements. Time lags produce phase loss that has potentially negative effects on the overall drive performance. Nevertheless, the pulse counting method is favored in most cases due to its simplicity and existing support for its use in digital signal processors. In this paper, a new speed sensing method is proposed to reduce time lag without incurring increased fluctuations. The proposal uses a novel transient detector to determine the actual operational regime of the drive: transient or stationary. Transient detection is not based on measured speeds but works directly with the train of incoming encoder pulses. The method is designed to work well with established digital signal processor routines. The proposal is assessed through experimentation on a real five-phase induction motor.

The increasing use of unmanned aerial vehicles (UAVs) in the commercial and recreational sectors has led to a heightened demand for effective recovery solutions after a crash, particularly for lightweight drones. This paper presents the development of a long-range and low-cost emergency radio beacon designed specifically for small UAVs. Unlike traditional emergency locator transmitters (ELTs), our proposed beacon addresses the unique needs of UAVs by reducing size, weight, and cost, while maximizing range and power efficiency. The device utilizes a global system for mobile (GSM)-based communication module to transmit location data via short message service (SMS), eliminating the need for specialized receivers and expanding the operational range even in obstacle-rich environments. Additionally, a built-in global navigation satellite system (GNSS) receiver provides precise coordinates, activated only upon impact detection through an accelerometer, thereby saving power during normal operations. Experimental tests confirm the extended range, high precision, and compatibility of the prototype with common mobile networks. Cost-effective and easy to use, this beacon improves UAV recovery efforts by providing reliable localization data to users in real time, thus safeguarding the UAV investment.