Control de sistemas usando aprendizaje de máquina

Systems control using machine learning

Jesús Martín Miguel Martínez (2023, [Tesis de maestría])

El aprendizaje por refuerzo es un paradigma del aprendizaje de máquina con un amplio desarrollo y una creciente demanda en aplicaciones que involucran toma de decisiones y control. Es un paradigma que permite el diseño de controladores que no dependen directamente del modelo que describe la dinámica del sistema. Esto es importante ya que en aplicaciones reales es frecuente que no se disponga de dichos modelos de manera precisa. Esta tesis tiene como objetivo implementar un controlador óptimo en tiempo discreto libre de modelo. La metodología elegida se basa en algoritmos de aprendizaje por refuerzo, enfocados en sistemas con espacios de estado y acción continuos a través de modelos discretos. Se utiliza el concepto de función de valor (Q-función y función V ) y la ecuación de Bellman para resolver el problema del regulador cuadrático lineal para un sistema mecánico masa-resorte-amortiguador, en casos donde se tiene conocimiento parcial y desconocimiento total del modelo. Para ambos casos las funciones de valor son definidas explícitamente por la estructura de un aproximador paramétrico, donde el vector de pesos del aproximador es sintonizado a través de un proceso iterativo de estimación de parámetros. Cuando se tiene conocimiento parcial de la dinámica se usa el método de aprendizaje por diferencias temporales en un entrenamiento episódico, que utiliza el esquema de mínimos cuadrados con mínimos cuadrados recursivos en la sintonización del crítico y descenso del gradiente en la sintonización del actor, el mejor resultado para este esquema es usando el algoritmo de iteración de valor para la solución de la ecuación de Bellman, con un resultado significativo en términos de precisión en comparación a los valores óptimos (función DLQR). Cuando se tiene desconocimiento de la dinámica se usa el algoritmo Q-learning en entrenamiento continuo, con el esquema de mínimos cuadrados con mínimos cuadrados recursivos y el esquema de mínimos cuadrados con descenso del gradiente. Ambos esquemas usan el algoritmo de iteración de política para la solución de la ecuación de Bellman, y se obtienen resultados de aproximadamente 0.001 en la medición del error cuadrático medio. Se realiza una prueba de adaptabilidad considerando variaciones que puedan suceder en los parámetros de la planta, siendo el esquema de mínimos cuadrados con mínimos cuadrados recursivos el que tiene los mejores resultados, reduciendo significativamente ...

Reinforcement learning is a machine learning paradigm with extensive development and growing demand in decision-making and control applications. This technique allows the design of controllers that do not directly depend on the model describing the system dynamics. It is useful in real-world applications, where accurate models are often unavailable. The objective of this work is to implement a modelfree discrete-time optimal controller. Through discrete models, we implemented reinforcement learning algorithms focused on systems with continuous state and action spaces. The concepts of value-function, Q-function, V -function, and the Bellman equation are employed to solve the linear quadratic regulator problem for a mass-spring-damper system in a partially known and utterly unknown model. For both cases, the value functions are explicitly defined by a parametric approximator’s structure, where the weight vector is tuned through an iterative parameter estimation process. When partial knowledge of the dynamics is available, the temporal difference learning method is used under episodic training, utilizing the least squares with a recursive least squares scheme for tuning the critic and gradient descent for the actor´s tuning. The best result for this scheme is achieved using the value iteration algorithm for solving the Bellman equation, yielding significant improvements in approximating the optimal values (DLQR function). When the dynamics are entirely unknown, the Q-learning algorithm is employed in continuous training, employing the least squares with recursive least squares and the gradient descent schemes. Both schemes use the policy iteration algorithm to solve the Bellman equation, and the system’s response using the obtained values was compared to the one using the theoretical optimal values, yielding approximately zero mean squared error between them. An adaptability test is conducted considering variations that may occur in plant parameters, with the least squares with recursive least squares scheme yielding the best results, significantly reducing the number of iterations required for convergence to optimal values.

aprendizaje por refuerzo, control óptimo, control adaptativo, sistemas mecánicos, libre de modelo, dinámica totalmente desconocida, aproximación paramétrica, Q-learning, iteración de política reinforcement learning, optimal control, adaptive control, mechanical systems, modelfree, utterly unknown dynamics, parametric approximation, Q-learning, policy iteration INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS TECNOLOGÍA DE LOS ORDENADORES INTELIGENCIA ARTIFICIAL INTELIGENCIA ARTIFICIAL

Modeling the growth, yield and N dynamics of wheat for decoding the tillage and nitrogen nexus in 8-years long-term conservation agriculture based maize-wheat system

C.M. Parihar Dipaka Ranjan Sena Prakash Chand Ghasal Shankar Lal Jat Yashpal Singh Saharawat Mahesh Gathala Upendra Singh Hari Sankar Nayak (2024, [Artículo])

Context: Agricultural field experiments are costly and time-consuming, and their site-specific nature limits their ability to capture spatial and temporal variability. This hinders the transfer of crop management information across different locations, impeding effective agricultural decision-making. Further, accurate estimates of the benefits and risks of alternative crop and nutrient management options are crucial for effective decision-making in agriculture. Objective: The objective of this study was to utilize the Crop Environment Resource Synthesis CERES-Wheat model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based wheat system. The study aimed to calibrate the model using data from a field experiment conducted during the 2019-20-2020-21 growing seasons and evaluation it with independent data from the year 2021–22. Method: Crop simulation models, such as the Crop Environment Resource Synthesis CERES-Wheat (DSSAT v 4.8), may provide valuable insights into crop growth and nitrogen dynamics, enabling decision makers to understand and manage production risk more effectively. Therefore, the present study employed the CERES-Wheat (DSSAT v 4.8) model and calibrated it using field data, including plant phenological phases, leaf area index, aboveground biomass, and grain yield from the 2019-20-2020-21 growing seasons. An independent dataset from the year 2021–22 was used for model evaluation. The model was used to investigate the relationship between growing degree days (GDD), temperature, nitrate and ammonical concentration in soil, and nitrogen uptake by the crop. Additionally, the study explored the impact of contrasting tillage practices and fertilizer nitrogen management options on wheat yields. The experimental site is situated at ICAR-Indian Agricultural Research Institute (IARI), New Delhi, representing Indian Trans-Gangetic Plains Zone (28o 40’N latitude, 77o 11’E longitude and an altitude of 228 m above sea level). The treatments consist of four nitrogen management options, viz., N0 (zero nitrogen), N150 (150 kg N ha−1 through urea), GS (Green seeker based urea application) and USG (urea super granules @150 kg N ha−1) in two contrasting tillage systems, i.e., CA-based zero tillage (ZT) and conventional tillage (CT). Result: The outcomes exhibited favorable agreement between the model’s simulations and the observed data for crop phenology (With less than 2 days variation in 50% onset of flowering), grain and biomass yield (Root mean square error; RMSE 336 kg ha−1 and 649 kg ha−1, respectively), and leaf area index (LAI) (RMSE 0.28 & normalized RMSE; nRMSE 6.69%). The model effectively captured the nitrate-N (NO3−-N) dynamics in the soil profile, exhibiting a remarkable concordance with observed data, as evident from its low RMSE = 12.39 kg ha−1 and nRMSE = 13.69%. Moreover, as it successfully simulated the N balance in the production system, the nitrate leaching and ammonia volatilization pattern as described by the model are highly useful to understand these critical phenomena under both conventional tillage (CT) and CA-based Zero Tillage (ZT) treatments. Conclusion: The study concludes that the DSSAT-CERES-Wheat model has significant potential to assess the impacts of tillage and nitrogen management practices on crop growth, yield, and soil nitrogen dynamics in the western Indo-Gangetic Plains (IGP) region. By providing reliable forecasts within the growing season, this modeling approach can facilitate better planning and more efficient resource management. Future implications: The successful implementation of the DSSAT-CERES-Wheat model in this study highlights its applicability in assessing crop performance and soil dynamics. Future research should focus on expanding the model’s capabilities by reducing its sensitivity to initial soil nitrogen levels to refine its predictions further. Moreover, the model’s integration with decision support systems and real-time data can enhance its usefulness in aiding agricultural decision-making and supporting sustainable crop management practices.

Nitrogen Dynamics Mechanistic Crop Growth Models Crop Simulation CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA NITROGEN CONSERVATION AGRICULTURE WHEAT MAIZE CROP GROWTH RATE SIMULATION MODELS

DEPRESSIVE SYMPTOMS (DS) AND CITIES: A SOCIOECONOMIC PERSPECTIVE FOR THE MEXICAN CASE

Jorge López Martínez Déborah Féber González (2023, [Artículo, Artículo])

This article presents an analysis of the proportion of the population that lives in the 20 top cities of Mexico. Population that suffers from moderate to severe Depressive Symptoms (DS) in relation to urban and socioeconomic factors typical of urban territories and comparing them with people living in rural or non-urban environments that suffers DS. To check this, we generated the Complex Index of Socioeconomic and Urban Conditions (CISUC), based on the Mind the GAPS framework, a model that relates the susceptibility or prevention of mental illness in cities based on urban factors, we also used socioeconomic indicators that exist in Mexican cities. For the construction of the ICCSU database, we used data from the National Health and Nutrition Survey in the years 2006, 2012 and 2018-19 and the data of the Mexican Institute for Competitiveness, A.C. and National Institute of Statistics and Geography in the same years. The results obtained from CISUC were reinforced with the use of a panel data model. The findings that we obtained reveal that there is a more important correlation between cities and people who suffer from moderate to severe DS than in rural areas, a condition that intensifies with the socioeconomic conditions of the population, for example, their socioeconomic stratum, their gender, and present urban marginalization. This allows to generate future discussions about other types of diseases such as anxiety, depression, stress, loneliness, and schizophrenia for large population groups. The panel model yields a lower goodness of adjustment, due to the lack of more time points, however, it points out that improvements in socioeconomic and urban conditions slightly reduce depressive symptoms.

mental health depressive symptoms (DS) urban marginalization socioeconomic factors cities salud mental sintomatología depresiva (SD) ciudades marginación urbana factores socioeconómicos CIENCIAS SOCIALESCIENCIAS SOCIALES CIENCIAS SOCIALES

Sistemas de producción sostenibles y redes de innovación

Jelle Van Loon (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA PRODUCTION SYSTEMS INNOVATION PRODUCTION SYSTEMS AGRIFOOD SYSTEMS

Last mile seed delivery approaches in Sudan and beyond: an annotated bibliography

Hugo De Groote Paswel Marenya (2023, [Libro])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SEED SYSTEMS SEED INDUSTRY BIBLIOGRAPHIES

Impact of automation on enhancing energy quality in grid-connected photovoltaic systems

Virgilio Alfonso Murillo Rodríguez NOE VILLA VILLASEÑOR José Manuel Robles Solís OA Guirette-Barbosa (2023, [Artículo])

Rapid growth in the integration of new consumers into the electricity sector, particularly in the industrial sector, has necessitated better control of the electricity supply and of the users’ op-erating conditions to guarantee an adequate quality of service as well as the unregulated dis-turbances that have been generated in the electrical network that can cause significant failures, breakdowns and interruptions, causing considerable expenses and economic losses. This research examines the characteristics of electrical variations in equipment within a company in the industrial sector, analyzes the impact generated within the electrical system according to the need for operation in manufacturing systems, and proposes a new solution through automation of the regulation elements to maintain an optimal system quality and prevent damage and equipment failures while offering a cost-effective model. The proposed solution is evaluated through a reliable simulation in ETAP (Energy Systems Modeling, Analysis and Optimization) software, which emulates the interaction of control elements and simulates the design of electric flow equipment operation. The results demonstrate an improvement in system performance in the presence of disturbances when two automation schemes are applied as well as the exclusive operation of the capacitor bank, which improves the total system current fluctuations and improves the power factor from 85.83% to 93.42%. Such a scheme also improves the waveform in the main power system; another improvement result is when simultaneously operating the voltage and current filter together with the PV system, further improving the current fluctuations, improving the power factor from 85.83% to 94.81%, achieving better stability and improving the quality of the waveform in the main power grid.

This article belongs to Special Issue Advances and Optimization of Electric Energy System.

Power quality Capacitor bank Voltage and current filter Photovoltaic system INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS OTRAS ESPECIALIDADES TECNOLÓGICAS OTRAS OTRAS

Diseño y desarrollo de dispositivo de sujeción hidráulica para el proceso de brochado

Design and development of hydraulic clamping device for broaching process

Jorge Morales Carlos Álvarez Raúl Pérez Bustamante (2023, [Artículo])

Se desarrollo un dispositivo de sujeción hidráulica para el proceso de brochado de Brackets usados en los sistemas de frenado de automóviles, que permite reducir la variación del proceso de corte al mejorar el sistema de sujeción y con ello limitar la deformación de la pieza luego de haber sido procesada. Con este concepto de dispositivo es posible mejorar las condiciones del proceso de producción, como lo son: velocidad de corte, reducción de tiempo ciclo, rendimiento de la operación, reducción de costo de scrap, y reducción de tiempo muerto por sobre ajuste de proceso y cambio de modelo. Adicional, se hizo el desarrollo de un sistema de detección de pieza presente que permite captar cuando una pieza no es colocada correctamente en el dispositivo antes de iniciar el ciclo de corte, con esto es posible detectar fallas en el proceso que representen un riesgo para la operación. Durante la etapa de diseño se realizó una simulación del proceso de maquinado en condiciones extremas y condiciones ideales para medir la deformación de la pieza y con esto obtener los parámetros adecuados de corte para la puesta en marcha del dispositivo de sujeción. Para la validación del modelo, se realizó un estudio de habilidad de proceso Cpk y Ppk (acorde a los requerimientos de cliente) para evaluar que el nuevo proceso es eficiente y se encuentra bajo control.

A hydraulic clamping device was developed for the broaching process of Brackets used in automotivebraking systems, which allows reducing the variation of the cutting process by improving the clamping system andthereby limiting the deformation of the piece after having been processed. With this concept of device, it is possibleto improve the conditions of the production process such as: cutting speed, cycle time reduction, operationperformance, scrap cost reduction, and downtime reduction due to process over-adjustment and change over.Additionally, the development of a part detection system was made that allows capturing when a part is not correctlyplaced in the device before starting the cutting cycle, with this it is possible to detect failures in the process thatrepresent a risk to the operation. During the design stage, a simulation of the machining process was carried outin extreme conditions and ideal conditions to measure the deformation of the part and with this obtain theappropriate cutting parameters for the implementation of the clamping device. For the validation of the model, aCpk and Ppk process ability study was carried out (according to customer requirements) to assess that the newprocess is efficient and is under control.

Agradecemos al Centro de Investigación y Asistencia Técnica del Estado de Querétaro, A.C. (CIATEQ) y a la empresa donde fue desarrollado el proyecto por todas las facilidades otorgadas para la realización de dicho proyecto, de igual manera, agradecer por el apoyo brindado a todas las personas involucradas directa o indirectamente en el desarrollo de este trabajo.

Agradecimientos de autoría: Jorge Alberto Morales Martínez: Conceptualización; Metodología; Software; Análisis formal; Investigación; Adquisición de fondos; Recursos; Análisis de datos; Borrador original; Administración de proyecto, Revisión y edición. Carlos Marín: Conceptualización; Ideas; Análisis de datos; Software; Análisis formal y Supervisión. Raúl Pérez Bustamante: Revisión y edición.

Dispositivo de sujeción Proceso de brochado Bracket Sistema de frenado Parámetros de corte Cpk Ppk Clamping device Broaching process Brake system Cutting parameters INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS OTRAS ESPECIALIDADES TECNOLÓGICAS OTRAS OTRAS

Core partners kick-off meeting─Ukama Ustawi (UU): Diversification for Resilient Agrifood systems in East and Southern Africa (ESA)

Evan Girvetz Christian Thierfelder Iddo Dror (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURE FOOD SYSTEMS DIVERSIFICATION RESILIENCE

MLN disease diagnostics, MLN disease-free seed production and MLN disease management

Suresh L.M. (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DISEASES DISEASE MANAGEMENT SEED PRODUCTION MAIZE NECROSIS YIELD LOSSES ECONOMIC IMPACT SURVEILLANCE SYSTEMS TRAINING

Redesigning crop varieties to win the race between climate change and food security

Kevin Pixley Jill Cairns Santiago Lopez-Ridaura Chris Ojiewo Baloua Nébié Godfrey Asea Biswanath Das Benoit Joseph Batieno Clare Mukankusi Sarah Hearne Kanwarpal Dhugga Sieglinde Snapp Ernesto Adair Zepeda Villarreal (2023, [Artículo])

Crop Breeding Expert Survey CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE CROPPING SYSTEMS FOOD SECURITY CROPS