Fuzzy logic applied to system control to enhance commercial appliance performance

The purpose of this research is to determine the usefulness of fuzzy logic and fuzzy control when applied to a commercial appliance. Fuzzy logic is a structured, model-free estimator that approximates a function through linguistic input/output associations. Fuzzy rule-based systems apply these methods to solve many types of real-world problems, especially where a system is difficult to model, is controlled by a human operator or expert, or where ambiguity or vagueness is common. This dissertation presents fuzzy sets, fuzzy systems, and fuzzy control, with an example conveying the use of fuzzy control of a consumer product and an overview of fuzzy logic in the field of artificial intelligence. Ultimately, it demonstrates that the use of fuzzy systems makes a viable addition to the field of artificial intelligence and, perhaps, more generally to the application of other consumer products to reduce energy consumption and increase the ease of operation. Topics such as classical logic, set theory, fuzzy set theory, and fuzzy mathematics are developed in this research to provide a foundation in fuzzy logic. Fuzzy logic is an excellent development of a basic home appliance to provide a powerful and user-friendly device. Fuzzy logic allows an engineer without a great knowledge of control systems and mathematical modeling a viable alternative in product creation. The fuzzy logic toolbox of the program MATLAB\sp{\rm TM} developed by The Mathworks Corporation is used to build and test the fuzzy logic systems explored by this dissertation. Again, in this dissertation the concept of fuzzy logic shall be explored in detail. Background and theoretical information shall be derived to provide a good base for applications. Classical logic, crisp sets, fuzzy sets, and operations on fuzzy sets are explained in order to cover a wide spectrum of applications. The focus or cumulating point will be to apply the fuzzy logic principle to any type of consumer appliance (such as a washing machine). The use of fuzzy logic will allow many household goods to be manufactured more quickly and with more options, and be energy efficient, user friendly, and cost effective

Nonlinear H-infinity control for switched reluctance machines

AbstractThe article proposes a nonlinear H-infinity control method for switched reluctance machines. The dynamic model of the switched reluctance machine undergoes approximate linearization round local operating points which are redefined at each iteration of the control algorithm. These temporary equilibria consist of the last value of the reluctance machine's state vector and of the last value of the control signal that was exerted on it. For the approximate linearization of the reluctance machine's dynamics, Taylor series expansion is performed through the computation of the associated Jacobian matrices. The modelling errors are compensated by the robustness of the control algorithm. Next, for the linearized equivalent model of the reluctance machine an H-infinity feedback controller is designed. This requires the solution of an algebraic Riccati equation at each time-step of the control method. It is shown that the control scheme achieves H-infinity tracking performance, which implies maximum robustness to modelling errors and external perturbations. The stability of the control loop is proven through Lyapunov analysis

A decision support model for process planning in remanufacturing using fuzzy set theory and genetic algorithm

The environmental awareness and resources preservation has boosted the use of remanufacturing processes. Many important studies have been made in this area, but there are still pitfalls and opportunities that have not been explored yet. Specifically, the cleaning processes play a critical role in remanufacturing. It is among the top of most costly processes and it plays a key step in remanufacturing because delivers a free of contaminant product ready for reprocessing. Understanding and selecting the best processes to meet the need and goals of remanufacturers are important for effective and efficient remanufacturing. Due to variables and high uncertainty associated with cleaning processes, there is a need of both knowledge and application of remanufacturing process planning. Aiming on this need, a decision making tool based on fuzzy sets and genetic algorithm for process planning is proposed. It helps the remanufacturer to select the best cleaning processes to achieve its objective

Neural Network Based Torque Control of Switched Reluctance Motor for Hybrid Vehicle Propulsion

Considering the extensive non-linearities in the switched reluctance motor (SRM) drive, variation in the DC bus voltage and specific requirements of the hybrid electric vehicles (HEVs) traction application, a feed-forward back propagation neural network (BPNN) based torque controller is proposed. By using proposed controller, the torque ripple has been effectively reduced at low speeds while the power efficiency has been optimized at high speeds range. The problem of multi-valuedness related with the neural network based direct inverse control has been targeted by designing a bank of two-hidden-layer neural network controllers. And the problem of torque oscillation due to the change of control mode and step change of firing angle has been solved by using dead-band filtering and nearly continuous changing of firing angle and phase currents. Computed results are presented to demonstrate the effectiveness of the proposed control scheme

Advanced Power Loss Modeling and Model-Based Control of Three-Phase Induction Motor Drive Systems

Three-phase induction motor (IM) drive systems are the most important workhorses of many industries worldwide. This dissertation addresses improved modeling of three-phase IM drives and model-based control algorithms for the purpose of designing better IM drive systems. Enhancements of efficiency, availability, as well as performance of IMs, such as maximum torque-per-ampere capability, power density, and torque rating, are of major interest. An advanced power loss model of three-phase IM drives is proposed and comprehensively validated at different speed, load torque, flux and input voltage conditions. This model includes a core-loss model of three-phase IMs, a model of machine mechanical and stray losses, and a model of power electronic losses in inverters. The drive loss model shows more than 90% accuracy and is used to design system-level loss minimization control of a motor drive system, which is integrated with the conventional volts-per-hertz control and indirect field-oriented control as case studies. The designed loss minimization control leads to more than 13% loss reduction than using rated flux for the testing motor drive under certain conditions. The proposed core-loss model is also used to design an improved model-based maximum torque-per-ampere control of IMs by considering core losses. Significant increase of torque-per-ampere capability could be possible for high-speed IMs. A simple model-based time-domain fault diagnosis method of four major IM faults is provided; it is nonintrusive, fast, and has excellent fault sensitivity and robustness to noise and harmonics. A fault-tolerant control scheme for sensor failures in closed-loop IM drives is also studied, where a multi-controller drive is proposed and uses different controllers with minimum hand-off transients when switching between controllers. A finite element analysis model of medium-voltage IMs is explored, where electromagnetic and thermal analyses are co-simulated. The torque rating and power density of the simulated machine could be increased by 14% with proper change of stator winding insulation material. The outcome of this dissertation is an advanced three-phase IM drive that is enhanced using model-based loss minimization control, fault detection and diagnosis of machine faults, fault-tolerant control under sensor failures, and performance-enhancement suggestions

Power Converter of Electric Machines, Renewable Energy Systems, and Transportation

Power converters and electric machines represent essential components in all fields of electrical engineering. In fact, we are heading towards a future where energy will be more and more electrical: electrical vehicles, electrical motors, renewables, storage systems are now widespread. The ongoing energy transition poses new challenges for interfacing and integrating different power systems. The constraints of space, weight, reliability, performance, and autonomy for the electric system have increased the attention of scientific research in order to find more and more appropriate technological solutions. In this context, power converters and electric machines assume a key role in enabling higher performance of electrical power conversion. Consequently, the design and control of power converters and electric machines shall be developed accordingly to the requirements of the specific application, thus leading to more specialized solutions, with the aim of enhancing the reliability, fault tolerance, and flexibility of the next generation power systems

Control techniques for mechatronic assisted surgery

The treatment response for traumatic head injured patients can be improved by using an autonomous robotic system to perform basic, time-critical emergency neurosurgery, reducing costs and saving lives. In this thesis, a concept for a neurosurgical robotic system is proposed to perform three specific emergency neurosurgical procedures; they are the placement of an intracranial pressure monitor, external ventricular drainage, and the evacuation of chronic subdural haematoma. The control methods for this system are investigated following a curiosity led approach. Individual problems are interpreted in the widest sense and solutions posed that are general in nature. Three main contributions result from this approach: 1) a clinical evidence based review of surgical robotics and a methodology to assist in their evaluation, 2) a new controller for soft-grasping of objects, and 3) new propositions and theorems for chatter suppression sliding mode controllers. These contributions directly assist in the design of the control system of the neurosurgical robot and, more broadly, impact other areas outside the narrow con nes of the target application. A methodology for applied research in surgical robotics is proposed. The methodology sets out a hierarchy of criteria consisting of three tiers, with the most important being the bottom tier and the least being the top tier. It is argued that a robotic system must adhere to these criteria in order to achieve acceptability. Recent commercial systems are reviewed against these criteria, and are found to conform up to at least the bottom and intermediate tiers. However, the lack of conformity to the criteria in the top tier, combined with the inability to conclusively prove increased clinical benefit, particularly symptomatic benefit, is shown to be hampering the potential of surgical robotics in gaining wide establishment. A control scheme for soft-grasping objects is presented. Grasping a soft or fragile object requires the use of minimum contact force to prevent damage or deformation. Without precise knowledge of object parameters, real-time feedback control must be used to regulate the contact force and prevent slip. Moreover, the controller must be designed to have good performance characteristics to rapidly modulate the fingertip contact force in response to a slip event. A fuzzy sliding mode controller combined with a disturbance observer is proposed for contact force control and slip prevention. The robustness of the controller is evaluated through both simulation and experiment. The control scheme was found to be effective and robust to parameter uncertainty. When tested on a real system, however, chattering phenomena, well known to sliding mode research, was induced by the unmodelled suboptimal components of the system (filtering, backlash, and time delays). This reduced the controller performance. The problem of chattering and potential solutions are explored. Real systems using sliding mode controllers, such as the control scheme for soft-grasping, have a tendency to chatter at high frequencies. This is caused by the sliding mode controller interacting with un-modelled parasitic dynamics at the actuator-input and sensor-output of the plant. As a result, new chatter-suppression sliding mode controllers have been developed, which introduce new parameters into the system. However, the effect any particular choice of parameters has on system performance is unclear, and this can make tuning the parameters to meet a set of performance criteria di cult. In this thesis, common chatter-suppression sliding mode control strategies are surveyed and simple design and estimation methods are proposed. The estimation methods predict convergence, chattering amplitude, settling time, and maximum output bounds (overshoot) using harmonic linearizations and invariant ellipsoid sets

Biopolymers in Drug Delivery and Regenerative Medicine

Biopolymers including natural (e.g., polysaccharides, proteins, gums, natural rubbers, bacterial polymers), synthetic (e.g., aliphatic polyesters and polyphosphoester), and biocomposites are of paramount interest in regenerative medicine, due to their availability, processability, and low toxicity. Moreover, the structuration of biopolymer-based materials at the nano- and microscale along with their chemical properties are crucial in the engineering of advanced carriers for drug products. Finally, combination products including or based on biopolymers for controlled drug release offer a powerful solution to improve the tissue integration and biological response of these materials. Understanding the drug delivery mechanisms, efficiency, and toxicity of such systems may be useful for regenerative medicine and pharmaceutical technology. The main aim of the Special Issue on “Biopolymers in Drug Delivery and Regenerative Medicine” is to gather recent findings and current advances on biopolymer research for biomedical applications, particularly in regenerative medicine, wound healing, and drug delivery. Contributions to this issue can be as original research or review articles and may cover all aspects of biopolymer research, ranging from the chemical synthesis and characterization of modified biopolymers, their processing in different morphologies and hierarchical structures, as well as their assessment for biomedical uses