Development of Novel Compound Controllers to Reduce Chattering of Sliding Mode Control

The robotics and dynamic systems constantly encountered with disturbances such as micro electro mechanical systems (MEMS) gyroscope under disturbances result in mechanical coupling terms between two axes, friction forces in exoskeleton robot joints, and unmodelled dynamics of robot manipulator. Sliding mode control (SMC) is a robust controller. The main drawback of the sliding mode controller is that it produces high-frequency control signals, which leads to chattering. The research objective is to reduce chattering, improve robustness, and increase trajectory tracking of SMC. In this research, we developed controllers for three different dynamic systems: (i) MEMS, (ii) an Exoskeleton type robot, and (iii) a 2 DOF robot manipulator. We proposed three sliding mode control methods such as robust sliding mode control (RSMC), new sliding mode control (NSMC), and fractional sliding mode control (FSMC). These controllers were applied on MEMS gyroscope, Exoskeleton robot, and robot manipulator. The performance of the three proposed sliding mode controllers was compared with conventional sliding mode control (CSMC). The simulation results verified that FSMC exhibits better performance in chattering reduction, faster convergence, finite-time convergence, robustness, and trajectory tracking compared to RSMC, CSMC, and NSFC. Also, the tracking performance of NSMC was compared with CSMC experimentally, which demonstrated better performance of the NSMC controller

Nonlinear control and perturbation compensation in UAV quadrotor

The great interest in the field of flying robotics encouraged a lot of research work to improve its control strategies. This thesis is about modelling and design of controllers and perturbation compensators for a UAV quadrotor. Four approaches are built in this purpose. The first approach is perturbation attenuation system in a UAV quadrotor. Hierarchical Perturbation Compensator (HPC) is built to compensate for system uncertainties, non-modelled dynamics and external disturbances. It comprises three subsystems designed to provide continuous and precise estimation of perturbation. Each subsystem is designed to avoid the drawbacks of the other. This approach has superior proficiency to decrease unknown perturbation either external or internal. The second approach is a Three Loop Uncertainties Compensator (TLUC), designed to estimate unknown time- varying uncertainties and perturbations to reduce their effects and in order to preserve stability. The novelty of this approach is that the TLUC can estimate and compensate for uncertainties and disturbances in three loops made to provide tracking to residual uncertainty in order to achieve a higher level of support to the controller. Exponential reaching law sliding mode controller is proposed and applied. It is integrated based on Lyapunov stability theory to obtain fast response with lowest possible chattering. The performance is verified through analyses, simulations and experiments. The third approach is Feedback Linearization based on Sliding Mode Control (FLSMC). The purpose is to provide nonlinear control that reduces the effect of the highly coupled dynamic behavior and the hard nonlinearity in the quadrotor. The proposed controller uses a Second Order sliding mode Exact Differentiator SOED to estimate the velocity and the acceleration. The fourth approach proposes an improved Non-Singular Terminal Super-Twisting Control for the problem of position and attitude tracking of quadrotor systems. The super-twisting algorithm is an effective control used to provide high precision and less chattering. The proposed method is based on a non-singular terminal sliding surface with new exponent that solves the problem of singularity in terminal sliding mode control. Design procedure and the stability analysis using Lyapunov theory are detailed for the considered approaches. The performance is verified through analyses, simulations and experiments

Design of a fuzzy PID controller for a MEMS tunable capacitor for noise reduction in a voltage reference source

This study presents a conventional Ziegler-Nichols (ZN) Proportional Integral Derivative (PID) controller, having reviewed the mathematical modeling of the Micro Electro Mechanical Systems (MEMS) Tunable Capacitors (TCs), and also proposes a fuzzy PID controller which demonstrates a better tracking performance in the presence of measurement noise, in comparison with conventional ZN-based PID controllers. Referring to importance and impact of this research, the proposed controller takes advantage of fuzzy control properties such as robustness against noise. TCs are responsible for regulating the reference voltage when integrated into Alternating Current (AC) Voltage Reference Sources (VRS). Capacitance regulation for tunable capacitors in VRS is carried out by modulating the distance of a movable plate. A successful modulation depends on maintaining the stability around the pull-in point. This distance regulation can be achieved by the proposed controller which guarantees the tracking performance of the movable plate in moving towards the pull-in point, and remaining in this critical position. The simulation results of the tracking performance and capacitance tuning are very promising, subjected to measurement nois

Decoupled Fractional Super-Twisting Stabilization of Interconnected Mobile Robot Under Harsh Terrain Conditions

The four-wheel omnidirectional mobile robot usually suffers disturbed or unstable lateral motion under harsh terrain conditions (such as uneven or oiled ground). Generally for such a challenging situation, the lumped disturbances and interconnected states render available coupling solutions difficult to achieve demand-satisfied performance. This paper proposes a novel decoupled fractional super-twisting sliding mode control (FST-SMC) method by (i) constructing an inverse system-based decoupling to form a pseudolinear composition system; (ii) presenting an enhanced nominal sliding law for chattering mitigation and (iii) designing an unbiased multi-layer fuzzy estimator with gain-learning capacity to compensate for the lumped disturbances actively. Given that the identified disturbances can be directly reflected in the FST-SMC law, this method guarantees an accurate and robust control without causing gain overestimation. Theoretical analysis is offered to verify the asymptotic stability. Under harsh terrain conditions, experimental results validate the effectiveness of the proposed FST-SMC method

Design of a fuzzy PID controller for a MEMS tunable capacitor for noise reduction in a voltage reference source

This study presents a conventional Ziegler-Nichols (ZN) Proportional Integral Derivative (PID) controller, having reviewed the mathematical modeling of the Micro Electro Mechanical Systems (MEMS) Tunable Capacitors (TCs), and also proposes a fuzzy PID controller which demonstrates a better tracking performance in the presence of measurement noise, in comparison with conventional ZN-based PID controllers. Referring to importance and impact of this research, the proposed controller takes advantage of fuzzy control properties such as robustness against noise. TCs are responsible for regulating the reference voltage when integrated into Alternating Current (AC) Voltage Reference Sources (VRS). Capacitance regulation for tunable capacitors in VRS is carried out by modulating the distance of a movable plate. A successful modulation depends on maintaining the stability around the pull-in point. This distance regulation can be achieved by the proposed controller which guarantees the tracking performance of the movable plate in moving towards the pull-in point, and remaining in this critical position. The simulation results of the tracking performance and capacitance tuning are very promising, subjected to measurement noise. Article Highlights This article deals with MEMS tunable capacitor dynamics and modeling, considering measurement noise. It designs and applies fuzzy PID control system for regulating MEMS voltage reference output. This paper contributes to robustness increase in pull-in performance of the tunable capacitor

Modeling and Robust Control of Flying Robots Using Intelligent Approaches Modélisation et commande robuste des robots volants en utilisant des approches intelligentes

This thesis aims to modeling and robust controlling of a flying robot of quadrotor type. Where we focused in this thesis on quadrotor unmanned Aerial Vehicle (QUAV). Intelligent nonlinear controllers and intelligent fractional-order nonlinear controllers are designed to control. The QUAV system is considered as MIMO large-scale system that can be divided on six interconnected single-input–single-output (SISO) subsystems, which define one DOF, i.e., three-angle subsystems with three position subsystems. In addition, nonlinear models is considered and assumed to suffer from the incidence of parameter uncertainty. Every parameters such as mass, inertia of the system are assumed completely unknown and change over time without prior information. Next, basing on nonlinear, Fractional-Order nonlinear and the intelligent adaptive approximate techniques a control law is established for all subsystems. The stability is performed by Lyapunov method and getting the desired output with respect to the desired input. The modeling and control is done using MATLAB/Simulink. At the end, the simulation tests are performed to that, the designed controller is able to maintain best performance of the QUAV even in the presence of unknown dynamics, parametric uncertainties and external disturbance

Soft computing techniques applied to modelling and control of unmanned aerial vehicles

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, leída el 18-06-2019El uso de UAVs (vehículos autónomos aéreos), y en concreto, de cuatrirrotores o drones, está creciendo de día en día, y se espera que se usen en multitud de aplicaciones: rescate, seguridad,lucha contra incendios, agricultura, inspección de estructuras, logística, … En la mayoría de estas tareas los cuatrirrotores deben actuar de una forma totalmente autónoma. Estas aplicaciones y las que están por llegar requieren el diseño de modelos y controladores eficientes y robustos para esos vehículos no pilotados. Sin embargo, esta no es una tarea sencilla debido, entre otras causas, a la aleatoriedad de los flujos de aire, la dinámica altamente no lineal del UAV, el acoplamiento entre sus variables internas, etc. Estos factores hacen que las técnicas de Soft Somputing (computación suave, una rama de la Inteligencia Artificial), y entre ellas concretamente las redes neuronales artificiales y la lógica fuzzy, sean un enfoque prometedor para la identificación y el control de estos sistemas...The use of UAVs (unmanned aerial vehicles), and specially quadrotors, is growing day by day, they are planned to be used in multitude of valuable applications: rescue, security, firefighting, agriculture, structure inspection, logistics, … In most of those tasks, the quadrotorsare expected to be fully autonomous. All these applications and those to come, demand the design of efficient and robust models and controllers for those autonomous vehicles. However, this is not an easy task due to, among others: the randomness of the airstreams, the high nonlinearity dynamics, the coupling between the internal variables, etc. These factors make the Soft Computing techniques (a field of the Artificial Intelligence), and among them specially the artificial neural networks and the fuzzy logic, a promising approach for the identification and control of these systems...Fac. de InformáticaTRUEunpu

Multi-sensor activity recognition of an elderly person.

The rapid increase in the number of ageing population brings major issues to health care including a rise in care cost, high demand in long- term care, burden to caregivers, and insufficient and ineffective care. Activity recognition can be used as the key part of the intelligent sys- tems to allow elderly people to live independently at homes, reduce care cost and burden to the caregivers, provide assurance for the fam- ilies, and promote better care. However, current activity recognition systems mainly focus on the technical aspect i.e. systems accuracy and neglects the practical aspects such as acceptance, usability, cost and privacy. The practicality of the system is the vital indication whether the system will be adopted. This research aims to develop the activity recognition system which considers both practical and technical aspects using multiple wrist-worn sensors. An extensive literature review in wearable sensor based activity recog- nition and its applications in healthcare have been carried out. Novel multi-sensor activity recognition utilising multiple low-cost, non-intrusive, non-visual wearable sensors is proposed. The sensor fusion is per- formed at feature and classi er levels using the proposed feature se- lection and classi er combination techniques. The multi-sensor ac- tivity recognition data sets have been collected. The rst data set contains data from accelerometer collected from seven young adults. The second data set contains data from accelerometer, altimeter, and temperature sensor collected from 12 elderly people in home environ- ment performing 10 activities. The third data set contains sensor data from accelerometer, gyroscope, temperature sensor, altimeter, barometer, and light sensor worn on the users wrist and a heart rate monitor worn over the users chest. The data set is collected from 12 elderly persons in a real home environment performing 13 activities. This research proposes two feature selection methods, Feature Com- bination (FC) and Maximal Relevancy and Maximal Complementary (MRMC), based on the relationship between feature and classes as well as the relationship between a group of features and classes. The experimental studies show that the proposed techniques can select an optimum set of features from irrelevant, overlapped, and partly over- lapped features. The studies also show that FC and MRMC obtain higher classi cation performances than popular techniques including MRMR, NMIFS, and Clamping. Two classi er combination tech- niques based on Genetic Algorithm (GA) are proposed. The rst technique called GA based Fusion Weight (GAFW), uses GA nd the optimum fusion weights. The results indicate that 99% of classi er fusion using GAFW achieves equal or higher accuracy than using only the best classi er. While other fusion weight techniques cannot guar- antee accuracy improvement, GAFW is a more suitable method for determining fusion weight regardless which fusion techniques are used. Another algorithm called GA based Combination Model (GACM) is proposed to nd the optimal combination between classi er, weight function, and classi er combiners. The algorithm does not only nd the model which has the minimum classi cation error but also select the one that is simpler. Other criteria e.g. select the classi er with low computation can also be easily added to the algorithm. The re- sults show that in general GACM can nd the optimum combinations automatically. The comparison against manually selection revealed that there is no statistical signi cant in the performances. Applications of the proposed work in home care and decision support system are discussed The results of this research will have a signi cant impact on the future health care where people can be health monitored from their homes to promote healthy living, detect any changes in behaviour, and improve quality of care

Applications of Mathematical Models in Engineering

The most influential research topic in the twenty-first century seems to be mathematics, as it generates innovation in a wide range of research fields. It supports all engineering fields, but also areas such as medicine, healthcare, business, etc. Therefore, the intention of this Special Issue is to deal with mathematical works related to engineering and multidisciplinary problems. Modern developments in theoretical and applied science have widely depended our knowledge of the derivatives and integrals of the fractional order appearing in engineering practices. Therefore, one goal of this Special Issue is to focus on recent achievements and future challenges in the theory and applications of fractional calculus in engineering sciences. The special issue included some original research articles that address significant issues and contribute towards the development of new concepts, methodologies, applications, trends and knowledge in mathematics. Potential topics include, but are not limited to, the following: Fractional mathematical models; Computational methods for the fractional PDEs in engineering; New mathematical approaches, innovations and challenges in biotechnologies and biomedicine; Applied mathematics; Engineering research based on advanced mathematical tools