A Method to Guarantee Local Convergence for Sequential Quadratic Programming with Poor Hessian Approximation

Sequential Quadratic Programming (SQP) is a powerful class of algorithms for solving nonlinear optimization problems. Local convergence of SQP algorithms is guaranteed when the Hessian approximation used in each Quadratic Programming subproblem is close to the true Hessian. However, a good Hessian approximation can be expensive to compute. Low cost Hessian approximations only guarantee local convergence under some assumptions, which are not always satisfied in practice. To address this problem, this paper proposes a simple method to guarantee local convergence for SQP with poor Hessian approximation. The effectiveness of the proposed algorithm is demonstrated in a numerical example

Modelling and control of a 2-DOF planar parallel manipulator for semiconductor packaging systems

A novel direct-drive planar parallel manipulator for high-speed and high-precision semiconductor packaging systems is presented. High precision kinematics design, significant redaction on moving mass and driving power of the actuators over traditional XY motion stages are the benefits of the proposed manipulator. The mathematical model of the manipulator is obtained using the Newton-Enter method and a practical model-based control design approach is employed to design the PID computed-torque controller. Experimental results demonstrate that the proposed planar parallel manipulator has significant improvements on motion performance in terms of positioning accuracy, settling time and stability when compared with traditional XY stages. This shows that the proposed planar parallel manipulator can provide a superior alternative for replacing traditional XY motion stages in high precision low-payload applications. © 2005 IEEE.published_or_final_versio

Critical Aspects of Electric Motor Drive Controllers and Mitigation of Torque Ripple - Review

Electric vehicles (EVs) are playing a vital role in sustainable transportation. It is estimated that by 2030, Battery EVs will become mainstream for passenger car transportation. Even though EVs are gaining interest in sustainable transportation, the future of EV power transmission is facing vital concerns and open research challenges. Considering the case of torque ripple mitigation and improved reliability control techniques in motors, many motor drive control algorithms fail to provide efficient control. To efficiently address this issue, control techniques such as Field Orientation Control (FOC), Direct Torque Control (DTC), Model Predictive Control (MPC), Sliding Mode Control (SMC), and Intelligent Control (IC) techniques are used in the motor drive control algorithms. This literature survey exclusively compares the various advanced control techniques for conventionally used EV motors such as Permanent Magnet Synchronous Motor (PMSM), Brushless Direct Current Motor (BLDC), Switched Reluctance Motor (SRM), and Induction Motors (IM). Furthermore, this paper discusses the EV-motors history, types of EVmotors, EV-motor drives powertrain mathematical modelling, and design procedure of EV-motors. The hardware results have also been compared with different control techniques for BLDC and SRM hub motors. Future direction towards the design of EV by critical selection of motors and their control techniques to minimize the torque ripple and other research opportunities to enhance the performance of EVs are also presented.publishedVersio

An investigation on micro cutting mechanics: Modelling, simulations and experimental case studies

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University London.Micro cutting is becoming increasingly important since miniature and micro components/products have become more and more demanded in precision engineering applications and consumer goods in a daily life. Meanwhile, it has not been thoroughly investigated yet. Scientific understanding of the fundamentals in micro cutting mechanics and physics is vital for micro manufacturing of micro or miniature components and products. Consequently, the scientific investigation on micro cutting mechanics is critically needed, particularly on its key fundamental aspects on which a systematic approach and key enabling technologies are developed for micro manufacturing. Therefore, three key fundamental aspects of micro cutting mechanics have been identified for this PhD project and a comprehensive systematic research has been performed through both theoretical and experiment-based investigations. The three aspects of micro cutting mechanics mainly include dynamic stiffness investigation, innovative micro cutting force modelling, and the study on micro cutting heat, temperature and their partitioned distribution. All experiment-based investigations are undertaken on a diamond turning machine test rig supported with a fast tool servo (FTS) using different reconfigured experimental setups. The finite element (FE)-based analysis is conducted to further support the in-depth analysis on the micro cutting phenomena especially the modelling and simulation of micro cutting force and temperature. Accordingly, both micro cutting force modelling and micro cutting temperature are investigated using modelling and simulation supported by well-designed experimental cutting trials and validations.The investigation on dynamic stiffness in the micro cutting system is focused on its effects on the micro cutting process and its control strategies. The burrs formation and machining accuracy are explored in relation with control of the dynamic stiffness. Furthermore, the control algorithm for dynamic stiffness is developed accordingly in order to minimise burrs formation and stabilize the micro cutting accuracy.The micro cutting force modelling is performed based on specific cutting force, i.e. modelling the cutting force at the unit cutting length or area as coined as the amplitude aspect of the proposed cutting force modelling. The cutting force against a dynamically varied cutting time interval is proposed as the spatial aspect of the cutting force formulation. The amplitude aspect can provide the insight into the micro cutting phenomena particularly in relation with the chip formation and size-effects. The spatial aspect, using a on the wavelet transform (WT) technique and standard deviation analysis can render the dynamic behaviour of the micro cutting force, particularly representing the dynamic effects of the cutting process and its correlation with tool wear.The micro cutting temperature is investigated to formulate the scientific understanding of cutting temperature, heat and their partitioned distribution particularly at the tool-workpiece-chip interface zone in ultraprecision and micro cutting using a diamond cutting tool. The contribution to knowledge at this aspect is to represent the partitioned cutting heat in the micro cutting process and their different behaviours compared to the conventional metal cutting. The scientific approach to modelling micro cutting application (MMCA), i.e. based on modelling-simulation combined with experimental validation, is further evaluated and validated to illustrate the overall benefits of this research investigation through micro cutting of single crystal silicon (for ultraprecision machining of large-sized infrared devices). This approach is established in light of combining all the three aspects of the above investigation on micro cutting mechanics. The research results show the approach can lead to industrial scale advantages for ultraprecision and micro cutting but driven by the scientific understanding of micro manufacturing technology. The systematic investigation on dynamic stiffness control, micro cutting force modelling, micro cutting heat and temperature and their integrated approach can contribute well to the future micro cutting applications

Design of Outrunner Eectric Machines for Green Energy Applications

Interests in using rare-earth free motors such as switched reluctance motors (SRMs) for electric and hybrid electric vehicles (EV/HEVs) continue to gain popularity, owing to their low cost and robustness. Optimal design of an SRM, to meet specific characteristics for an application, should involve simultaneous optimization of the motor geometry and control in order to achieve the highest performance with the lowest cost. This dissertation firstly presents a constrained multi-objective optimization framework for design and control of a SRM based on a non-dominated sorting genetic algorithm II (NSGA-II). The proposed methodology optimizes SRM operation for high volume traction applications by considering multiple criteria including efficiency, average torque, and torque ripple. Several constraints are defined by the application considered, such as the motor stack length, minimum desired efficiency, etc. The outcome of this optimization includes an optimal geometry, outlining variables such as air gap length, rotor inner diameter, stator pole arc angle, etc as well as optimal turn-on and turn-off firing angles. Then the machine is manufactured according to the obtained optimal specifications. Finite element analysis (FEA) and experimental results are provided to validate the theoretical findings. A solution for exploring optimal firing angles of nonlinear current-controlled SRMs is proposed in order to minimize the torque ripple. Motor torque ripple for a certain electrical load requirement is minimized using a surrogate-based optimization of firing angles by adjusting the motor geometry, reference current, rotor speed and dc bus voltage. Surrogate-based optimization is facilitated via Neural Networks (NN) which are regression tools capable of learning complex multi-variate functions. Flux and torque of the nonlinear SRM is learned as a function of input parameters, and consequently the computation time of design, which is crucial in any micro controller unit, is expedited by replacing the look-up tables of flux and torque with the surrogate NN model. This dissertation then proposes a framework for the design and analysis of a coreless permanent magnet (PM) machine for a 100 kWh shaft-less high strength steel flywheel energy storage system (SHFES). The PM motor/generator is designed to meet the required specs in terms of torque-speed and power-speed characteristics given by the application. The design challenges of a motor/generator for this architecture include: the poor flux paths due to a large scale solid carbon steel rotor and zero-thermal convection of the airgap due to operation of the machine in vacuum. Magnetic flux in this architecture tends to be 3-D rather than constrained due to lack of core in the stator. In order to tackle these challenges, several other parameters such as a proper number of magnets and slots combination, number of turns in each coil, magnets with high saturated flux density and magnets size are carefully considered in the proposed design framework. Magnetic levitation allows the use of a coreless stator that is placed on a supporting structure. The proposed PM motor/generator comprehensive geometry, electromagnetic and mechanical dimensioning are followed by detailed 3-D FEA. The torque, power, and speed determined by the FEA electromagnetic analysis are met by the application design requirements and constraints for both the charging and discharging modes of operation. Finally, the motor/generator static thermal analysis is discussed in order to validate the proposed cooling system functionality

Oceanic Wave Energy Conversion by a Novel Permanent Magnet Linear Generator Capable of Preventing Demagnetization

© 1972-2012 IEEE. In the conventional permanent magnet linear generators (PMLGs) used for oceanic wave energy conversion system, demagnetization could cause everlasting degradation in electrical power generation. This paper presents a new design that can be applied to various PMLGs to avoid demagnetization. To check the effectiveness of the proposed technique, a PMLG is considered, which allows both the fixed and variable length of airgaps for analysis. The finite element analysis is used by using the software package ANSYS/Ansoft to simulate the testing PMLG for two conditions: with and without using the proposed technique. Different parameters and characteristics of the PMLG under both conditions are presented in detail. Both the simulation and test results show that the proposed design is able to avoid the demagnetization problem successfully

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