Zero Average Dynamics (ZAD) strategy has been reported in the last decade as an alternative control technique for power converters, and a lot of work has been devoted to analyze it. From a theoretical point of view, this technique has the advantage that it guarantees fixed switching frequency, low output error and robustness, however, no high correspondence between numerical and experimental results has been obtained. These differences are basically due to model assumptions; in particular, all elements in the circuit were modeled as ideal elements and simulations and conclusions about steady state stability and transitions to chaos have been carried out with this ideal model. Regarding the practical point of view and the digital implementation, we include in this paper internal resistances, quantization effects and 1-period delay to the model. This paper shows in an experimental and numerical way the effects of these elements to the model and their incidence in the results. Now, experimental and numerical analyses fully agree.

The motor speed of a buck power converter and DC motor coupled system is controlled by means of a quasi-sliding scheme. The fixed point inducting control technique and the zero average dynamics strategy are used in the controller design. To estimate the load and friction torques an online estimator, computed by the least mean squares method, is used. The control scheme is tested in a rapid control prototyping system which is based on digital signal processing for a dSPACE platform. The closed loop system exhibits adequate performance, and experimental and simulation results match.

There is an increased industry demand for efficient and safe methods to select the best-quality coffee beans for a demanding market. Color, morphology, shape and size are important factors that help identify the best quality beans; however, conventional techniques based on visual and/or mechanical inspection are not sufficient to meet the requirements. Therefore, this paper presents an image processing and machine learning technique integrated with an Arduino Mega board, to evaluate those four important factors when selecting best-quality green coffee beans. For this purpose, the k-nearest neighbor algorithm is used to determine the quality of coffee beans and their corresponding defect types. The system consists of logical processes, image processing and the supervised learning algorithms that were programmed with MATLAB and then burned into the Arduino board. The results showed this method has a high effectiveness in classifying each single green coffee bean by identifying its main visual characteristics, and the system can handle several coffee beans present in a single image. Statistical analysis shows the process can identify defects and quality with high accuracy. The artificial vision method was helpful for the selection of quality coffee beans and may be useful to increase production, reduce production time and improve quality control.

In this paper, the output voltage of a buck power converter is controlled by means of a quasi-sliding scheme. The Fixed Point Inducting Control (FPIC) technique is used for the control design, based on the Zero Average Dynamics (ZAD) strategy, including load estimation by means of the Least Mean Squares (LMS) method. The control scheme is tested in a Rapid Control Prototyping (RCP) system based on Digital Signal Processing (DSP) for dSPACE platform. The closed loop system shows adequate performance. The experimental and simulation results match. The main contribution of this paper is to introduce the load estimator by means of LMS, to make ZAD and FPIC control feasible in load variation conditions. In addition, comparison results for controlled buck converter with SMC, PID and ZAD–FPIC control techniques are shown.

This work describes a method to characterize a three-phase linear induction motor in order to determine the various parameters used in its per-phase equivalent circuit by a DSP-based electric-drives system. In LIM (Linear Induction Motor), the air gap is very large compared with the RIMs (Rotary Induction Motors). Further, the secondary part normally does not have slotted structure. It is just made of aluminum and steel plates. Therefore, the effective air gap is larger than the physical air gap. High air gap makes a larger leakage inductance. It leads to lower efficiency and lower power factor. DC resistance test will be done to determine the value of Rs. The primary Inductance Ls will be calculated by running the LIM at synchronous speed. The secondary parameters i.e. Llr and Rr′ will be calculated by blocked-mover test. The experiment for no load test is shown and include a DC motor coupled to the LIM under test. Two methods to calculate the secondary parameters are described.

This paper presents the experimental implementation of a buck converter with quasi-sliding mode control combined with a loss estimator function. An online loss estimator is developed to estimate, in real time, the parasitic resistances of the converter and variations of the resistance in the load. The estimated loss resistance and the resistance of the load are embedded, in real time, into the model equations of the controller using Zero Average Dynamics and Fixed Point Induction Control techniques (ZAD-FPIC) to improve the control robustness to resistive parameter variations. Details of the experimental setup are presented to show developed electrical and electronic circuits, and experimental techniques are described to ensure the successful digital implementation of closed-loop control of the buck power converter. The proper shielding of electrical wiring in power electronics allows improvement to the quality of the measures by removing noise induced by electromagnetic interference. A trigger signal is used to implement the Pulse-Width Modulation (PWM) with centered pulse and to synchronize the sampling of analogical signals from the buck converter. Such synchronization allows the use of a lower sampling frequency and ensures the measurements at the right instant in time. Experimental results are in good agreement with numerical simulations, showing the effectiveness of the control approach.

This paper presents the dynamic analysis of a permanent magnet DC motor using a buck converter controlled by zero average dynamics (ZADs) and fixed-point inducting control (FPIC). Initially, the steady-state behavior of the closed-loop system was observed and then transient behavior analyzed while maintaining a fixed ZAD control parameter and changing the FPIC parameter. Other behaviors were studied when the value of the ZAD control parameter changed and the FPIC parameter was maintained at the initial value. Besides, bifurcation diagrams were built with one and two delay periods by changing the control parameter of the FPIC and maintaining fixed ZAD parameters while some disturbances were carried out in the electric source. The results show that the ZAD-FPIC controller allowed good regulation of the speed for different reference values. The ZAD-FPIC control technique is effective for controlling the buck converter with the motor, even with two delay periods. The robustness of the system was checked by changing the voltage of the source. It was shown that the system used a fixed switching frequency because the duty cycle was not saturated for certain ranges of the control parameters shown in the research. This technique can be used for higher order systems with experimental phenomena such as quantization effects, time delays, and variations in the input signal.

This paper presents a methodology based on two interrelated rapid prototyping processes in order to find the best correspondence between theoretical, simulated, and experimental results of a power converter controlled by a digital PWM. The method supplements rapid control prototyping (RCP) with effective math tools to quickly select and validate models of a controlled system. We show stability analysis of the classical and two modified buck converter models controlled by zero average dynamics (ZAD) and fixed-point induction control (FPIC). The methodology consists of obtaining the mathematical representation of power converters with the controllers and the Lyapunov Exponents (LEs). Besides, the theoretical results are compared with the simulated and experimental results by means of one- and two-parameter bifurcation diagrams. The responses of the three models are compared by changing the parameter K_s of the ZAD and the parameter N of the FPIC. The results show that the stability zones, periodic orbits, periodic bands, and chaos are obtained for the three models, finding more similarities between theoretical, simulated, and experimental tests with the third model of the buck converter with ZAD and FPIC as it considers more parameters related to the losses in different elements of the system. Additionally, the intervals of the chaos are obtained by using the LEs and validated by numerical and experimental tests