Fuzzy logic based efficiency optimization of IPM synchronous motor drive

Interior permanent magnet synchronous motor (IPMSM) is highly appreciated by researchers in variable speed drive applications due to some of its advantageous features such as small size, high power density, simple maintenance, high output torque, high power factor, low noise and robustness as compared to the conventional IM and other ac motors. Although these motor drives are well known for their relatively high efficiency, improvement margins still exist in their operating efficiency. Particularly, the reduction of power loss for IPMSM still remains a challenge for researchers. Improvement of motor drives efficiency is important not only from the viewpoints of energy loss and hence cost saving, but also from the perspective of environmental pollution. The thesis presents development of a fuzzy logic based efficiency and speed control system of an IPMSM drive. In order to maximize the efficiency in steady state operation while meeting the speed and load torque demands a search based fuzzy efficiency controller is designed to minimize the drive power losses to achieve higher efficiency by reducing the flux. The air gap flux level can be reduced by controlling the d-axis armature current as it is supplied by rotor permanent magnet. In order for the drive to track the reference speed in transient operation another fuzzy logic based controller is designed to increase the flux depending on the speed error and its derivative. The torque component of stator current (q-axis component of stator current) is generated by fuzzy logic based speed controller for different dynamic operation depending on speed error and its derivative. In this work a torque compensation algorithm is also introduced to reduce the torque and speed fluctuations

Fuzzy sliding mode control of a multi-DOF parallel robot in rehabilitation environment

Multi-degrees of freedom (DOF) parallel robot, due to its compact structure and high operation accuracy, is a promising candidate for medical rehabilitation devices. However, its controllability relating to the nonlinear characteristics challenges its interaction with human subjects during the rehabilitation process. In this paper, we investigated the control of a parallel robot system using fuzzy sliding mode control (FSMC) for constructing a simple controller in practical rehabilitation, where a fuzzy logic system was used as the additional compensator to the sliding mode controller (SMC) for performance enhancement and chattering elimination. The system stability is guaranteed by the Lyapunov stability theorem. Experiments were conducted on a lower limb rehabilitation robot, which was built based on kinematics and dynamics analysis of the 6-DOF Stewart platform. The experimental results showed that the position tracking precision of the proposed FSMC is sufficient in practical applications, while the velocity chattering had been effectively reduced in comparison with the conventional FSMC with parameters tuned by fuzzy systems

Control of switched reluctance machines

This thesis is concerned with the control of switched reluctance machines for both motoring and generating applications. There are different control objectives in each case. For motoring operation, there are two possible control objectives. If the SRM is being employed in a servo-type application, the desire is for a constant output torque. However, for low performance applications where some amount of torque ripple is acceptable, the aim is to achieve efficient and accurate speed regulation. When the SRM is employed for generating purposes, the goal is to maintain the dc bus voltage at the required value while achieving maximum efficiency. Preliminary investigative work on switched reluctance machine control in both motoring and generating modes is performed. This includes the implementation and testing through simulation of two control strategies described in the literature. In addition, an experimental system is built for the development and testing of new control strategies. The inherent nonlinearity of the switched reluctance machine results in ripple in the torque profile. This adversely affects motoring performance for servo-type applications. Hence, three neuro-fuzzy control strategies for torque ripple minimisation in switched reluctance motors are developed. For all three control strategies, the training of a neurofuzzy compensator and the incorporation of the trained compensator into the overall switched reluctance drive are described. The performance of the control strategies in reducing the torque ripple is examined with simulations and through experimental testing. While the torque ripple is troublesome for servo-type applications, there are some applications where a certain amount of torque ripple is acceptable. Therefore, four simple motor control strategies for torque ripple-tolerant applications are described and tested experimentally. Three of the control strategies are for low speed motoring operation while the fourth is aimed at high speed motoring operation. Finally, three closed-loop generator control strategies aimed at high speed operation in single pulse mode are developed. The three control strategies are examined by testing on the experimental system. A comparison of the performance of the control strategies in terms of efficiency and peak current produced by each is presented

A new supervisory energy managmement control strategy of a modified D-STATCOM configuration and dual DC source in distribution grids.

A microgrid is a state-of-the-art, next generation of electric distribution grid that provides a fundamental paradigm shift from passive grid networks to active networks. Power electronic technologies play a vital role in enabling microgrids to meet their system level requirements of power quality, reliability and demand response capability. A conventional distribution static compensator (D-STATCOM) is a power electronic converter which acts as a reactive power compensator and voltage controller at the point of common coupling in a grid system. However, these devices have limited ability to mitigate voltage fluctuations caused by active power disturbances. By integrating energy storage into the DC link of a D-STATCOM, controllable active power from the storage device can result in enhanced voltage compensating capability. The active and reactive power control between the D-STATCOM and AC power point is achieved by suitable tuning of the phase and magnitude of the output voltage of the D-STATCOM’s converter. Recent advances and innovations in energy storage systems such as super-capacitors and batteries allow the combination of battery-supercapacitor hybrid energy storage systems to act as an effective solution for energy management in smart grid operation. However, the concept and control of the hybridisation of energy storage are relatively new, and there are great challenges to the development of control management systems, for example, reduce battery current stresses. This study presents a novel approach in applying a fuzzy-PI controller to a D-STATCOM based energy storage unit to provide enhanced power quality and voltage stability in distribution grids. Full information is provided concerning the implementation of the system, and the dynamic controls devised during the research programme. A second novel approach is the use of sugeno fuzzy logic controller based decision making for power management of the D-STATCOM based HESS to achieve a robust and superior performance for voltage regulation. Recent developments in this field have tended to converge on intelligent control as the best approach to achieve an effective strategy for power sharing with HESSs by using a high-power storage unit (supercapacitor) and high energy storage unit (battery) in combination with the D-STATCOM to avoid the drawbacks of a single storage unit. This development is considered one of the main ways to upgrade energy storage technology, with gains of faster voltage regulation and decreased battery current peak value. Verification of the control designs has been achieved through simulation using MATLAB/SIMULINK based on the derived analytical model in state-space form. Comprehensive simulation results show that the proposed fuzzy controller demonstrates significant improvements over conventional controllers in supporting voltage stability in distribution networksPhD in Energy and Powe

Doubly-fed induction generator used in wind energy

Wound-rotor induction generator has numerous advantages in wind power generation over other generators. One scheme for wound-rotor induction generator is realized when a converter cascade is used between the slip-ring terminals and the utility grid to control the rotor power. This configuration is called the doubly-fed induction generator (DFIG). In this work, a novel induction machine model is developed. This model includes the saturation in the main and leakage flux paths. It shows that the model which considers the saturation effects gives more realistic results. A new technique, which was developed for synchronous machines, was applied to experimentally measure the stator and rotor leakage inductance saturation characteristics on the induction machine. A vector control scheme is developed to control the rotor side voltage-source converter. Vector control allows decoupled or independent control of both active and reactive power of DFIG. These techniques are based on the theory of controlling the B- and q- axes components of voltage or current in different reference frames. In this work, the stator flux oriented rotor current control, with decoupled control of active and reactive power, is adopted. This scheme allows the independent control of the generated active and reactive power as well as the rotor speed to track the maximum wind power point. Conventionally, the controller type used in vector controllers is of the PI type with a fixed proportional and integral gain. In this work, different intelligent schemes by which the controller can change its behavior are proposed. The first scheme is an adaptive gain scheduler which utilizes different characteristics to generate the variation in the proportional and the integral gains. The second scheme is a fuzzy logic gain scheduler and the third is a neuro-fuzzy controller. The transient responses using the above mentioned schemes are compared analytically and experimentally. It has been found that although the fuzzy logic and neuro-fuzzy schemes are more complicated and have many parameters; this complication provides a higher degree of freedom in tuning the controller which is evident in giving much better system performance. Finally, the simulation results were experimentally verified by building the experimental setup and implementing the developed control schemes

Development and analysis of a self-tuned neuro-fuzzy controller for induction motor drives

Induction motors (IM) have been widely utilized in industry for variable speed drives due to some of their advantages, such as rugged construction, low cost and reliable service with easy maintenance, as compared to conventional dc motors. For variable speed drive applications, the controller plays an important role so that the motor can follow the reference trajectories without any significant deviation. Furthermore, a controller which can provide fast speed response and handle uncertainties and disturbances, is absolutely necessary for high performance drive systems. Traditionally, fixed gain proportional-integral (PI) and some adaptive controllers have been utilized in industry for a long time. However, there are some disadvantages of these controllers to handle uncertainties which are inherent to a nonlinear IM. As a result, recently researchers paid their attention to apply intelligent algorithms to control the IM for high performance variable speed drive applications. Intelligent algorithms such as fuzzy logic (FL), neural network (NN), neuro-fuzzy (NF), etc, have inherent advantages as compared to the conventional controllers. In this thesis, a novel neuro-fuzzy controller (NFC) has been developed for speed control o f EM. For the complete drive, the indirect field orientation control is utilized in order to decouple the torque and flux controls. Thus, the induction motor can be controlled like a dc motor and hence the high performance can be achieved without lacking the advantage o f ac over dc motors. The proposed neuro-fuzzy controller incorporates Sugeno model based fuzzy logic laws with a five-layer artificial neural network (ANN) scheme. The controller is designed for low computational burden, which will be suitable for real-time implementation. Furthermore, for the proposed NFC an improved self-tuning method is developed based on the IM theory and its high performance requirements. The main task o f the tuning method is to adjust the parameters o f the fuzzy logic controller (FLC) in order to minimize the square of the error between actual and reference output. In this thesis, a model reference adaptive flux (MRAF) observer is also developed to estimate the d-axis rotor flux linkage in both constant flux and flux weakening regions based on motor voltage, current and reference trajectories for flux linkage. Thus, it provides safe operation to control the motor at high speeds, especially, above the rated speed. The d-axis reference flux linkage of the indirect field oriented control is provided by flux weakening method. Furthermore, a proportional-integral (PI) based flux controller is used to provide the compensation for the reference flux model by comparing the flux reference and the observed flux from Gopinath model flux observer. A complete simulation model for indirect field oriented control of IM incorporating the proposed MRAF observer based NFC is developed in Matlab/Simulink. In order to prove the superiority of the proposed controller, the performance of the proposed controller is compared with a conventional PI as well as fuzzy logic controller (FLC) based IM drives. The performance of the proposed IM drive is investigated extensively at different operating conditions in simulation. The performance of the proposed MRAF observer based NFC controller is found robust and a potential candidate for high performance industrial drive applications

Optimized state feedback regulation of 3DOF helicopter system via extremum seeking

In this paper, an optimized state feedback regulation of a 3 degree of freedom (DOF) helicopter is designed via extremum seeking (ES) technique. Multi-parameter ES is applied to optimize the tracking performance via tuning State Vector Feedback with Integration of the Control Error (SVFBICE). Discrete multivariable version of ES is developed to minimize a cost function that measures the performance of the controller. The cost function is a function of the error between the actual and desired axis positions. The controller parameters are updated online as the optimization takes place. This method significantly decreases the time in obtaining optimal controller parameters. Simulations were conducted for the online optimization under both fixed and varying operating conditions. The results demonstrate the usefulness of using ES for preserving the maximum attainable performance

RECENT TECHNIQUES ON OBSERVER DESIGN FOR DISTURBANCE ESTIMATION AND REJECTION IN PERMANENT MAGNET SYNCHRONOUS MOTORS

Permanent magnet synchronous machines (PMSMs) (either motor or generator) have attracted attention of research community comparing to other types of AC machines in the recent two decades. PMSMs are preferable than other AC machines in terms of large power-factor, broad speed of operation, compact proportions, and effective operation. Unfortunately, different sources of nonlinearities, model uncertainties, and external perturbations determine severity in a design of accurate speed control scheme for PMSMs. In the era of developing science and technologies, many advanced control solutions are proposed to control PMSMs. Although new solutions show their advantages comparing to traditional methods in terms of performance evaluation, practical realization of those algorithms could require expensive hardware with high computational capabilities. Furthermore, people in industry with less knowledge about the motor control may experience difficulties in using such advanced controllers on their own. Traditional PI/PID control schemes still work as a major control technique in modern industry, and in motor control as well. Numerous positive facts about the PI/PID schemes make such superiority of these control schemes. Firstly, the PI/PID can be implemented easily on most industrial software and hardware components. Secondly, while its scheme has clear mechanism of operation, most industrial processes could be controlled via the PI/PID scheme. These schemes are good in terms of small number of parameters to tune and tuning process itself could be very straightforward. Finally, implementation of the PI/PID controllers would require smaller time comparing to most proposed complex control solutions. It is studied that the traditional PI/PID controllers usually cannot deal with unpredictable disturbances, which in turn leads to degraded performance of an overall control system. Inspired by the advantages and widespread application of PI/PID control structure in industry, we propose a disturbance observer based composite control scheme which uses the PI-like controller for the feedback regulation and disturbance observer for estimation of lumped disturbances presented in a PMSM control system. Under this circumstance, this thesis work proposes three different control solutions for PMSM such as High-order disturbance observer-based composite control (HDOBCC), Disturbance rejection PI (DR-PI) control, and Hierarchical optimal disturbance observer-based control (HODOBC). Furthermore, to deeply understand the similarity and difference between the traditional disturbance observer-based control (DOBC) and active-disturbance rejection control (ADRC) schemes, this thesis also presents results of unification of these two control approaches in the speed control of a PMSM. The HDOBCC as the first method proposed in this thesis is designed to improve reference speed tracking performance of a PMSM under various operational conditions. A structure of the HDOBCC comprises a fuzzy-PI controller in a feedback stabilization part and novel high-order disturbance observer in a feedforward compensation part of the speed control system. The proposed controller is designed based on the research questions such as: firstly, although a fixed gain traditional PI controller is able to present satisfactory performance at some extent, still it does not guarantee such performance when sudden disturbances occur in a system; secondly, many disturbance observers designed for a PMSM in literature consider only a load torque as a disturbance, neglecting model uncertainties and parameter variations in design stage. Therefore, the HDOBCC is proposed such that it utilizes a fuzzy approach to determine parameters of the PI controller to overcome limitations of the fixed gain PI controller. Furthermore, the proposed scheme includes a high-order disturbance observer, which estimates not only the load torque, but also disturbances due to model uncertainties and parameter variations. Moreover, extended simulation and experimental studies are conducted to affirm performance of the HDOBCC under various form of the load torque. In addition to commonly tested step form of a load torque, severe forms of the load torque such as triangular form and sinusoidal form are tested with the proposed controller. Stability analysis of the closed-loop HDOBCC system is further provided. The next proposed method, DR-PI control, is designed by seeking answer for questions such as: firstly, although the traditional DOBC scheme applied for PMSM shows reasonable results in a PMSM control, its design can be limited to known actual parameters of the PMSM. In practice, actual parameters are usually not available, hence it could be hard to design the traditional DOBC in the absence of a plant information; secondly, for tuning a PI controller the traditional Ziegler-Nichols tuning approach still remains as one of the popular tuning approaches, however it does not give a rigorous explanation on selection of parameters during its design. Consequently, to answer these questions, the DR-PI control is designed for the PMSM speed control. The DR-PI control is designed such that it has a simple PI-like structure with intrinsic disturbance rejection mechanism determined by the parameters of a filtering element, desired plant model, and desired closed-loop system. Simulation and experimental validations are provided to validate the performance of the DR-PI. Furthermore, gain tuning mechanism and stability analysis of the closed-loop DR-PI-based speed control are also presented. The HODOBC scheme as a third proposed control scheme targets on the next research questions as: first, parameters of the traditional PI controller are mostly obtained by trial-and-error approach, which in turn may not guarantee satisfactory results; in a cascaded PMSM control, the outer speed loop performance highly depends on the performance of the inner current loop. The well-tuned speed control loop may degrade in performance, if the inner current loop is not tuned properly. To address these questions, we propose the HODOBC scheme, which consists of optimal PIlike controller in the feedback stabilization part and optimal extended-state observer (ESO) in the disturbance compensation part. The proposed HODOBC showed better performance when it is compared with other traditional controllers via experiments. Stability analysis is provided via the root locus approach. The study on unification of the DOBC and ADRC schemes has the following research question: the DOBC and ADRC are both used in estimation of total disturbance, but these two schemes are considered differently in literature. Hence, the study of both scheme is conducted to show the condition at which these two schemes show identical performance. The analysis of the traditional DOBC and ADRC schemes concludes that both scheme are equivalent in terms of performance characteristics if the dynamical delays of disturbance observers in each scheme are same. The results of analysis reveal that both scheme can be utilized to design a robust control system for PMSM, i.e. once the gains of disturbance observers can be calculated under the DOBC framework, further the disturbance rejection mechanism can be achieved via the ADRC framework. The results of PMSM control with the proposed control schemes have been tested on the Lucas-Nuelle DSP-based experimental setup

The 1st International Conference on Computational Engineering and Intelligent Systems

Computational engineering, artificial intelligence and smart systems constitute a hot multidisciplinary topic contrasting computer science, engineering and applied mathematics that created a variety of fascinating intelligent systems. Computational engineering encloses fundamental engineering and science blended with the advanced knowledge of mathematics, algorithms and computer languages. It is concerned with the modeling and simulation of complex systems and data processing methods. Computing and artificial intelligence lead to smart systems that are advanced machines designed to fulfill certain specifications. This proceedings book is a collection of papers presented at the first International Conference on Computational Engineering and Intelligent Systems (ICCEIS2021), held online in the period December 10-12, 2021. The collection offers a wide scope of engineering topics, including smart grids, intelligent control, artificial intelligence, optimization, microelectronics and telecommunication systems. The contributions included in this book are of high quality, present details concerning the topics in a succinct way, and can be used as excellent reference and support for readers regarding the field of computational engineering, artificial intelligence and smart system