Variable Structure-Based Control for Dynamic Temperature Setpoint Regulation in Hospital Extreme Healthcare Zones

In critical healthcare units, such as operation theaters and intensive care units, healthcare workers require specific temperature environments at different stages of an operation, which depends upon the condition of the patient and the requirements of the surgical procedures. Therefore, the need for a dynamically controlled temperature environment and the availability of the required heating/cooling electric power is relatively more necessary for the provision of a better healthcare environment as compared to other commercial and residential buildings, where only comfortable room temperature is required. In order to establish a dynamic temperature zone, a setpoint regulator is required that can control the zone temperature with a fast dynamic response, little overshoot, and a low settling time. Thus, two zone temperature regulators have been proposed in this article, including double integral sliding mode control (DISMC) and integral terminal sliding mode control (ITSMC). A realistic scenario of a hospital operation theater is considered for evaluating their responses and performance to desired temperature setpoints. The performance analysis and superiority of the proposed controllers have been established by comparison with an already installed Johnson temperature controller (JTC) for various time spans and specific environmental conditions that require setpoints based on doctors’ and patients’ desires. The proposed controllers showed minimal overshoot and a fast settling response, making them ideal controllers for operation theater (OT) zone temperature control

Closed-loop elastic demand control under dynamic pricing program in smart microgrid using super twisting sliding mode controller

Electricity demand is rising due to industrialisation, population growth and economic development. To meet this rising electricity demand, towns are renovated by smart cities, where the internet of things enabled devices, communication technologies, dynamic pricing servers and renewable energy sources are integrated. Internet of things (IoT) refers to scenarios where network connectivity and computing capability is extended to objects, sensors and other items not normally considered computers. IoT allows these devices to generate, exchange and consume data without or with minimum human intervention. This integrated environment of smart cities maintains a balance between demand and supply. In this work, we proposed a closed-loop super twisting sliding mode controller (STSMC) to handle the uncertain and fluctuating load to maintain the balance between demand and supply persistently. Demand-side load management (DSLM) consists of agents-based demand response (DR) programs that are designed to control, change and shift the load usage pattern according to the price of the energy of a smart grid community. In smart grids, evolved DR programs are implemented which facilitate controlling of consumer demand by effective regulation services. The DSLM under price-based DR programs perform load shifting, peak clipping and valley filling to maintain the balance between demand and supply. We demonstrate a theoretical control approach for persistent demand control by dynamic price-based closed-loop STSMC. A renewable energy integrated microgrid scenario is discussed numerically to show that the demand of consumers can be controlled through STSMC, which regulates the electricity price to the DSLM agents of the smart grid community. The overall demand elasticity of the current study is represented by a first-order dynamic price generation model having a piece-wise linear price-based DR program. The simulation environment for this whole scenario is developed in MATLAB/Simulink. The simulations validate that the closed-loop price-based elastic demand control technique can trace down the generation of a renewable energy integrated microgrid

A new fuzzy design for switching gain adaptation of sliding mode controller for a wind energy conversion system using a doubly fed induction generator

The paper proposes a newrobust fuzzy gain adaptation of the sliding mode (SMC) power control strategy for the wind energy conversion system (WECS), based on a doubly fed induction generator (DFIG), to maximize the power extracted from the wind turbine (WT). The sliding mode controller can deal with any wind speed, ingrained nonlinearities in the system, external disturbances and model uncertainties, yet the chattering phenomenon that characterizes classical SMC can be destructive. This problem is suitably lessened by adopting adaptive fuzzy-SMC. For this proposed approach, the adaptive switching gains are adjusted by a supervisory fuzzy logic system, so the chattering impact is avoided. Moreover, the vector control of the DFIG as well as the presented one have been used to achieve the control of reactive and active power of the WECS to make the wind turbine adaptable to diverse constraints. Several numerical simulations are performed to assess the performance of the proposed control scheme. The results show robustness against parameter variations, excellent response characteristics with a reduced chattering phenomenon as compared with classical SMC

Maximum Power Point Tracking Techniques for Photovoltaic Panel: A Review and Experimental Applications

This article contains a review of essential control techniques for maximum power point tracking (MPPT) to be applied in photovoltaic (PV) panel systems. These devices are distinguished by their capability to transform solar energy into electricity without emissions. Nevertheless, the efficiency can be enhanced provided that a suitable MPPT algorithm is well designed to obtain the maximum performance. From the analyzed MPPT algorithms, four different types were chosen for an experimental evaluation over a commercial PV system linked to a boost converter. As the reference that corresponds to the maximum power is depended on the irradiation and temperature, an artificial neural network (ANN) was used as a reference generator where a high accuracy was achieved based on real data. This was used as a tool for the implementation of sliding mode controller (SMC), fuzzy logic controller (FLC) and model predictive control (MPC). The outcomes allowed different conclusions where each controller has different advantages and disadvantages depending on the various factors related to hardware and software.This research was funded by the Basque Government through the project EKOHEGAZ (ELKARTEK KK-2021/00092), by the Diputación Foral de Álava (DFA), through the project CONAVANTER, and by the UPV/EHU, through the project GIU20/063

Optimal energy-efficient predictive controllers in automotive air-conditioning/refrigeration systems

The final publication is available at Elsevier via: http://dx.doi.org/10.1016/j.apenergy.2016.09.086 © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/This paper presents several robust model predictive controllers that improve the temperature performance and minimize energy consumption in an automotive air-conditioning/refrigeration (A/C-R) system with a three-speed and continuously-varying compressor. First, a simplified control-oriented model of the A/C-R system is briefly introduced. Accordingly, a discrete Model Predictive Controller (MPC) is designed based on the proposed model for an A/C-R system with a three-speed compressor. A proper terminal weight is chosen to guarantee its robustness under both regular and frost conditions. A case study is conducted under various heating load conditions. Two hybrid controllers are made, which combine the advantages of both the on/off controller and discrete MPC such that they will be more efficient under any ambient heating condition. In addition, a continuous MPC is developed for systems with continuous variable components. Finally, the experimental and simulation results of the new controllers and the conventional on/off controller are provided and compared to show that the proposed controllers can save up to 23% more energy.Automotive Partnership Canada (APC) || Cool-it Grou

Fault detection and fault tolerant control in wind turbines

Renewable energy is an important sustainable energy in the world. Up to now, as an essential part of low emissions energy in a lot of countries, renewable energy has been important to the national energy security, and played a significant role in reducing carbon emissions. It comes from natural resources, such as wind, solar, rain, tides, biomass, and geothermal heat. Among them, wind energy is rapidly emerging as a low carbon, resource efficient, cost effective sustainable technology in the world. Due to the demand of higher power production installations with less environmental impacts, the continuous increase in size of wind turbines and the recently developed offshore (floating) technologies have led to new challenges in the wind turbine systems.Wind turbines (WTs) are complex systems with large flexible structures that work under very turbulent and unpredictable environmental conditions for a variable electrical grid. The maximization of wind energy conversion systems, load reduction strategies, mechanical fatigue minimization problems, costs per kilowatt hour reduction strategies, reliability matters, stability problems, and availability (sustainability) aspects demand the use of advanced (multivariable and multiobjective) cooperative control systems to regulate variables such as pitch, torque, power, rotor speed, power factors of every wind turbine, etc. Meanwhile, with increasing demands for efficiency and product quality and progressing integration of automatic control systems in high-cost and safety-critical processes, the fields of fault detection and isolation (FDI) and fault tolerant control (FTC) play an important role. This thesis covers the theoretical development and also the implementation of different FDI and FTC techniques in WTs. The purpose of wind turbine FDI systems is to detect and locate degradations and failures in the operation of WT components as early as possible, so that maintenance operations can be performed in due time (e.g., during time periods with low wind speed). Therefore, the number of costly corrective maintenance actions can be reduced and consequently the loss of wind power production due to maintenance operations is minimized. The objective of FTC is to design appropriate controllers such that the resulting closed-loop system can tolerate abnormal operations of specific control components and retain overall system stability with acceptable system performance. Different FDI and FTC contributions are presented in this thesis and published in different JCR-indexed journals and international conference proceedings. These contributions embrace a wide range of realistic WTs faults as well as different WTs types (onshore, fixed offshore, and floating). In the first main contribution, the normalized gradient method is used to estimate the pitch actuator parameters to be able to detect faults in it. In this case, an onshore WT is used for the simulations. Second contribution involves not only to detect faults but also to isolate them in the pitch actuator system. To achieve this, a discrete-time domain disturbance compensator with a controller to detect and isolate pitch actuator faults is designed. Third main contribution designs a super-twisting controller by using feedback of the fore-aft and side-to-side acceleration signals of the WT tower to provide fault tolerance capabilities to the WT and improve the overall performance of the system. In this instance, a fixed-jacket offshore WT is used. Throughout the aforementioned research, it was observed that some faults induce to saturation of the control signal leading to system instability. To preclude that problem, the fourth contribution of this thesis designs a dynamic reference trajectory based on hysteresis. Finally, the fifth and last contribution is related to floating-barge WTs and the challenges that this WTs face. The performance of the proposed contributions are tested in simulations with the aero-elastic code FAST.La energía renovable es una energía sustentable importante en el mundo. Hasta ahora, como parte esencial de la energía de bajas emisiones en muchos países, la energía renovable ha sido importante para la seguridad energética nacional, y jugó un papel importante en la reducción de las emisiones de carbono. Proviene de recursos naturales, como el viento, la energía solar, la lluvia, las mareas, la biomasa y el calor geotérmico. Entre ellos, la energía eólica está emergiendo rápidamente como una tecnología sostenible de bajo carbono, eficiente en el uso de los recursos y rentable en el mundo. Debido a la demanda de instalaciones de producción de mayor potencia con menos impactos ambientales, el aumento continuo en el tamaño de las turbinas eólicas y las tecnologías offshore (flotantes) recientemente desarrolladas han llevado a nuevos desafíos en los sistemas de turbinas eólicas. Las turbinas eólicas son sistemas complejos con grandes estructuras flexibles que funcionan en condiciones ambientales muy turbulentas e impredecibles para una red eléctrica variable. La maximización de los sistemas de conversión de energía eólica, los problemas de minimización de la fatiga mecánica, los costos por kilovatios-hora de estrategias de reducción, cuestiones de confiabilidad, problemas de estabilidad y disponibilidad (sostenibilidad) exigen el uso de sistemas avanzados de control cooperativo (multivariable y multiobjetivo) para regular variables tales como paso, par, potencia, velocidad del rotor, factores de potencia de cada aerogenerador, etc. Mientras tanto, con las crecientes demandas de eficiencia y calidad del producto y la progresiva integración de los sistemas de control automático en los procesos de alto costo y de seguridad crítica, los campos de detección y aislamiento de fallos (FDI) y control tolerante a fallos (FTC) juegan un papel importante. Esta tesis cubre el desarrollo teórico y también la implementación de diferentes técnicas de FDI y FTC en turbinas eólicas. El propósito de los sistemas FDI es detectar y ubicar las degradaciones y fallos en la operación de los componentes tan pronto como sea posible, de modo que las operaciones de mantenimiento puedan realizarse a su debido tiempo (por ejemplo, durante periodos con baja velocidad del viento). Por lo tanto, se puede reducir el número de costosas acciones de mantenimiento correctivo y, en consecuencia, se reduce al mínimo la pérdida de producción de energía eólica debido a las operaciones de mantenimiento. El objetivo de la FTC es diseñar controladores apropiados de modo que el sistema de bucle cerrado resultante pueda tolerar operaciones anormales de componentes de control específicos y retener la estabilidad general del sistema con un rendimiento aceptable del sistema. Diferentes contribuciones de FDI y FTC se presentan en esta tesis y se publican en diferentes revistas indexadas a JCR y en congresos internacionales. Estas contribuciones abarcan una amplia gama de fallos WTs realistas, así como diferentes tipos de turbinas (en tierra, en alta mar ancladas al fondo del mar y flotantes). El rendimiento de las contribuciones propuestas se prueba en simulaciones con el código aeroelástico FAST.Postprint (published version

High performance disturbance observer based control system design for permanent magnet synchronous AC machine applications

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonAn electrical machine is one of the main workforces in different industries and serves them in various applications. Machine drive control design involves many technical issues for efficient and robust exploitation. Over several decades, Permanent Magnet Synchronous Motor (PMSM) is getting preferred for industrial applications over its counterpart Squirrel Cage Induction Motor (SCIM) drive, because of their higher efficiency, power density, and higher torque to inertia ratio. In the prospective that PMSM drives are considered the drives of the future, there are still technical challenges and issues related to PMSM control. Many studies have been devoted to PMSM control in the past, but there are still some open research areas that bring worldwide researchers’ interests back to PMSM drive control. One of the approaches that may facilitate better performance, higher efficiency, and robust and reliable work of the control system is the disturbance observer-based control (DOBC) with linear and nonlinear output feedback control for PM synchronous machine applications. DOBC is adopted due to its ability to reject external and internal disturbances with improving tracking performance in the variable speed wind energy conversion system (WECS) to maximize power extraction. The high order disturbance observer (HODO) is utilized to estimate the aerodynamic torque-based wind speed without the use of a traditional anemometer, which reduces the overall cost and improves the reliability of the whole system. Also, this method has been designed to improve the angular shaft speed tracking of the PMSM system under load torque disturbance and speed variations. The model-based linear and nonlinear feedback control are used in the proposed control systems. The sliding mode control (SMC) with switching output feedback control law and integral SMC with linear feedback and state-dependent Riccati equation (SDRE) based approaches have been designed for the systems. The SDRE control accounts for the nonlinear multivariable structure of the WECS and is approximated with Taylor series expansion terms. The chattering inherited from SMC is eliminated by the continuous approximation technique. The sliding mode is guaranteed by eliminating the reaching mode in the proposed integral SMC. The model-free cascaded linear feedback control system based on the proportional-integral (PI) controllers use a back-calculation algorithm anti-windup scheme. The proposed speed controllers are synthesized with HODO to compensate for the external disturbance, model uncertainty, noise, and modelling errors. Moreover, servomechanism-based SDRE control, a near-optimal control system is designed to suppress the model uncertainty and noise without the use of disturbance observers. The proposed control systems for PMSM speed regulation have demonstrated a significant improvement in the angular shaft speed-tracking performance at the transients. Their performances have been tested under speed, load torque variations, and model uncertainty. For example, HODO-based SMC with switching output feedback control law (SOFCL) has demonstrated improvement by more than 78% than the PI-PI control system of the PMSM. The performance of the HODOs-based Integral SMC with SDRE nonlinear feedback is improved by 80.5% under external disturbance, model uncertainty, and noise than Integral SMC with linear feedback in the WECS. The HODO-based SDRE control with servomechanism has shown an 80.2% improvement of mean absolute percentage error under disturbances than Integral SMC with linear feedback in the WECS. The PMSM speed tracking performance of the proposed HODO-based discrete-time PI-PI control system with back-calculation algorithm anti-windup scheme is improved by 87.29% and 90.2% in the speed commands and load torque disturbance variations scenarios respectively. The simulations for testing the proposed control system of the PMSM system and WECS have been implemented in Matlab/Simulink environment. The PMSM speed control experimental results have been obtained with Lucas-Nuelle DSP-based rapid control prototyping kit.Center for International Program “Bolashak” of the Ministry of Education and Science Republic of Kazakhsta