This paper presents a robust nonlinear control strategy for a laser scanner’s actuator operating under stochastic mechanical disturbances. External perturbations are represented as bounded stochastic torque inputs, capturing the aggregate effect of structural imbalance, impacts, or system degradation. Experimental observations of vibration-induced angular fluctuations motivate this modeling choice, highlighting the need for control strategies tolerant to bounded stochastic disturbances resulting from unpredictable mechanical faults. A smooth hyperbolic-based control law is proposed to achieve robust velocity tracking under these uncertain conditions. Global asymptotic stability is formally established through Lyapunov analysis, and simulation results confirm that the proposed method effectively maintains convergence and bounded control effort in the presence of estimated disturbance torque. The formulation is suitable for fault-tolerant control of precision actuators where physical irregularities are difficult to isolate or diagnose in real time.

This study presents a robust control strategy to mitigate the effects of friction and mechanical vibrations in a 1-DOF electromechanical actuator for laser scanning systems. Using hyperbolic tangent functions ensures bounded control signals, preventing actuator saturation. Real-time vibration measurements with MPU6050 modules were conducted to characterize the system’s mechanical behavior. The stability of the system is ana-lyzed using the direct Lyapunov method and Barbalat’s lemma, ensuring global asymptotic stability. Simulations demonstrated the control strategy’s effectiveness in improving stability and accuracy. Future work will focus on implementing this control in a physical prototype for validation.

This work presents improvements to a patented 3D laser scanning system with a friction-compensated laser positioning mechanism. By employing a dynamic friction model, the system accurately identifies angular positioning errors through a combination of manual and automatic measurements with different control inputs. The study conducts experiments involving multiple friction cycles and SEM micrograph analysis to compare the microscopic irregularities of steel surfaces before and after friction-based positioning. Parameters of the friction system are derived or estimated from processed input-output test data. A nonlinear control is proposed to compensate for friction effects, resulting in improved positioning accuracy. Experimental implementation using an STM32 board demonstrates a remarkable reduction in the uncertainty of 3D coordinates measured by applying friction-compensated laser positioning. The findings highlight the effectiveness of the proposed friction compensation method, making the 3D laser scanning system more precise and reliable for diverse applications.

Laser Scanners used for Structural Health Monitoring applications such as Pipelines Structural Inspections normally needs Point Clouds from a large quantity of individual measurements that should be adjusted or post-processed to decrease overall point-cloud errors depending on scanner's characteristics. The posterior adjustment is commonly addressed by different mathematical methods or computational algorithms. According to application requirements methods such as machine learning, signal filtering, or RANSAC algorithms are used. This paper shows the application of an adapted/modify RANSAC algorithm especially suited for the pipeline inspection task. Aiming to increase the percentage of useful data per capture.

Frequency measurement is one of the most important tasks in modern electrical metrology. In particular, for highly sensitive sensors with a frequency output, the resolution and sensitivity depends of the frequency measurement method used. The principle of rational approximations is a technique for frequency measurement, and its use has been proposed for application in sensors. In this work, a device which implements the principle of rational approximations is presented, and its characteristics are analyzed. Particularly, the system is used to measure the signal generated by a quartz crystal microbalance, and the relationship between the measured frequency, temperature and measurement time are evaluated.

Inertial navigation systems (INS) provide information about position and acceleration of a unmanned aerial vehicle (UAV) or airplanes. There are many types of INS, but most of them share the same principle of operation. We provide in this paper basic information in regard of accelerometers and gyroscopes; then, we demonstrate the effectiveness of our method based on computational experiments to measure the information from the INS. Finally we introduce a method for frequency shift detection and measurement based on pulse coincidence.

A new approach to position the Technical Vision System (TVS) laser ray, which determines the 3D coordinates of any object under observation in the TVS Field-of-View (FOV), using the Digital Controller LM629 is proposed. This approach reduces significantly the angular position error by at least 82.97 per cent, compared to the previous implementation of a proportional algorithm in closed-loop configuration, using directly a single microcontroller. Present paper identifies the behavior of the DC motor shaft, which represents the main actuator of the TVS Positioning Laser (PL), adjusting an internal trapezoidal velocity profile, generated as the control signal for the DC motor. The reference value for the DC motor actual angular position is computed, using the Digital Controller LM629, which also tracks this actual angular position. The methodology of the new approach is developed in accordance with theoretical concepts. In addition, experimental results show the comparison between the previous implementation and this new approach.

Previous research have shown the advantages of a novel Technical Vision System (TVS), developed at the Autonomous University of Baja California (UABC), which uses triangulation to determine spatial coordinates on any object under observation. Present paper proposes a new application for the TVS use on drones with remote laser scanner in agriculture to determine a vegetation index of scanned crops. Thereby the needed algorithm to position the laser ray in the TVS field-of-view are proposed, implemented using microcontroller and tested using various experimental factors. Experimentation results shows the advantages and disadvantages of every algorithm comparing the positioning errors after control.

In agricultural tasks, monitoring of large fields is required. In the last years automatic/autonomous monitoring has been researched; where unmanned aerial vehicles (UAV)-commonly known as drones-are used. For these systems, constrains related with autonomy during flight arise. In order to control properly the UAVs during flight, they require to measure physical variables, in a fast and accurate way. Also, the weight of instruments must be reduced for improving autonomy. In general, aerial vehicles obtain parameters like position, velocity and acceleration using inertial navigation systems. Regarding to this concern, in this work application of a novel technique for measurements onboard UAVs-particularly inertial measurement unit or IMU-is proposed. There are accelerometers inside the IMU. These accelerometers have a frequency domain output. The speed and position are calculated by the INS from acceleration. The acceleration is obtained from frequency measurements of the accelerometers output. For this reason an accurate and fast frequency measurement method is required. In this work, for this particular application, frequency measurement using principle of rational approximations is proposed. This technique allows to measure frequency in short time and with high accuracy, using a few electronic components. Due this properties, it perfectly fits requirements for UAVs.

A 3D spatial measurement system has been enhanced by computational intelligence. The measurement system is based in opto-electronic scanning instrumentation for industrial task, robot navigation, medical scanning, and structural health monitoring applications. This paper presents new research performed in the data processing of a vision sensing database. Multivariate outlier analysis has been implemented by Mahalanobis distance in order to improve Support Vector Machine (SVM) regression algorithm results. Measurement error regression data has been used for spatial 3D measurements error correction. Demonstrating that optical systems for measurements that present non-linear behavior could be positive impacted by computational intelligence.

Frequency domain sensors (FDS) are important elements in control, data acquisition and monitoring systems. Such sensors have some outstanding characteristics like output of quasi-digital signals, high sensitivity, high resolution, wide dynamic range, anti-interference capacity and good stability. A FDS converts a physical variable (measurand) into a frequency domain ouput. When the measurand changes, the output has a proportional frequency shift. In systems that use FDS, measuring the frequency shift is desirable. Accuracy of most frequency measurement techniques is limited by measurement time, and if more precision is required, longer times for measuring are needed. In this work, a novel approach using the rational approximations principle for measuring frequency shift in the output of a FDS is introduced. Also algorithms for simulating the mathematical model of frequency measurement process are proposed, and resolution of measurement is improved by analyzing the data obtained.

The presented paper is a follow up work and improvement of a previously published research of a 3D Vision System for mobile robot navigation application. Sensor fusion and redundancy are integrated to the system in order to increase the overall robustness as well as the accuracy of the system measurements by finding the energetic center of the laser signal used by the vision system. New experimental results are presented to demonstrate the increase of system accuracy.

As a consequence of the aging of the world population, society and governments must face major challenges regarding people's health. In recent years, researches have been interested in investigating how the technology can be used to improve the healthcare and assistance of patients with dementia, as the Alzheimer's disease. In this paper, we propose a nonintrusive pervasive model to assist patients with dementia, based on the use of a wireless sensor network. Using high availability and low cost binary sensors, the proposed model is able to determine in real-time the location of a patient, and to emit alerts if one leaves a safe place without supervision.