Torque Control

This book is the result of inspirations and contributions from many researchers, a collection of 9 works, which are, in majority, focalised around the Direct Torque Control and may be comprised of three sections: different techniques for the control of asynchronous motors and double feed or double star induction machines, oriented approach of recent developments relating to the control of the Permanent Magnet Synchronous Motors, and special controller design and torque control of switched reluctance machine

Induction Motors

AC motors play a major role in modern industrial applications. Squirrel-cage induction motors (SCIMs) are probably the most frequently used when compared to other AC motors because of their low cost, ruggedness, and low maintenance. The material presented in this book is organized into four sections, covering the applications and structural properties of induction motors (IMs), fault detection and diagnostics, control strategies, and the more recently developed topology based on the multiphase (more than three phases) induction motors. This material should be of specific interest to engineers and researchers who are engaged in the modeling, design, and implementation of control algorithms applied to induction motors and, more generally, to readers broadly interested in nonlinear control, health condition monitoring, and fault diagnosis

Sliding Mode Control

The main objective of this monograph is to present a broad range of well worked out, recent application studies as well as theoretical contributions in the field of sliding mode control system analysis and design. The contributions presented here include new theoretical developments as well as successful applications of variable structure controllers primarily in the field of power electronics, electric drives and motion steering systems. They enrich the current state of the art, and motivate and encourage new ideas and solutions in the sliding mode control area

Intelligent control of induction motors

This thesis presents the development and implementation of an integral field oriented intelligent control for an induction motor (IM) drive using Fuzzy Logic Controller (FLC), and an Artificial Neural Network (ANN), employing a finite element controller and making use of a Proportional Integral (PI) adaptive controller as well. An analytical model of an induction motor drive has been developed. In order to prove the superiority of the proposed controller, the performance of this controller is compared with conventional PI-based IM drives. The performance of the proposed IM drive is investigated extensively at different operating conditions in simulation. The proposed adaptive PI-based speed controller’s performance is found to be robust and it is a potential candidate for high performance industrial drive applications. The novel work focuses on using a Finite Element Controller map (FECM) to manipulate adaptive controllers for motor control drives. A digital signal processing (DSP) board DS1104 and laboratory induction motor were used to implement the complete vector control scheme. The test results have been compared with simulated results at different dynamic operating conditions. The effectiveness of this control scheme has been evaluated, and it has been found to be more efficient than the conventional PI controller

Development and Implementation of Some Controllers for Performance Enhancement and Effective Utilization of Induction Motor Drive

The technological development in the field of power electronics and DSP technology is rapidly changing the aspect of drive technology. Implementations of advanced control strategies like field oriented control, linearization control, etc. to AC drives with variable voltage, and variable frequency source is possible because of the advent of high modulating frequency PWM inverters. The modeling complexity in the drive system and the subsequent requirement for modern control algorithms are being easily taken care by high computational power, low-cost DSP controllers. The present work is directed to study, design, development, and implementation of various controllers and their comparative evaluations to identify the proper controller for high-performance induction motor (IM) drives. The dynamic modeling for decoupling control of IM is developed by making the flux and torque decoupled. The simulation is carried out in the stationary reference frame with linearized control based on state-space linearization technique. Further, comprehensive and systematic design procedures are derived to tune the PI controllers for both electrical and mechanical subsystems. However, the PI-controller performance is not satisfactory under various disturbances and system uncertainties. Also, precise mathematical model, gain values, and continuous tuning are required for the controller design to obtain high performance. Thus, to overcome these drawbacks, an adapted control strategy based on Adaptive Neuro-Fuzzy Inference System (ANFIS) based controller is developed and implemented in real-time to validate different control strategies. The superiority of the proposed controller is analyzed and is contrasted with the conventional PI controller-based linearized IM drive. The simplified neuro-fuzzy control (NFC) integrates the concept of fuzzy logic and neural network structure like conventional NFC, but it has the advantages of simplicity and improved computational efficiency over conventional NFC as the single input introduced here is an error instead of two inputs error and change in error as in conventional NFC. This structure makes the proposed NFC robust and simple as compared to conventional NFC and thus, can be easily applied to real-time industrial applications. The proposed system incorporated with different control methods is also validated with extensive experimental results using DSP2812. The effectiveness of the proposed method using feedback linearization of IM drive is investigated in simulation as well as in experiment with different working modes. It is evident from the comparative results that the system performance is not deteriorated using proposed simplified NFC as compared to the conventional NFC, rather it shows superior performance over PI-controller-based drive. A hybrid fuel cell (FC) supply system to deliver the power demanded by the feedback linearization (FBL) based IM drive is designed and implemented. The modified simple hybrid neuro-fuzzy sliding-mode control (NFSMC) incorporated with the intuitive FBL substantially reduces torque chattering and improves speed response, giving optimal drive performance under system uncertainties and disturbances. This novel technique also has the benefit of reduced computational burden over conventional NFSMC and thus, suitable for real-time industrial applications. The parameters of the modified NFC is tuned by an adaptive mechanism based on sliding-mode control (SMC). A FC stack with a dc/dc boost converter is considered here as a separate external source during interruption of main supply for maintaining the supply to the motor drive control through the inverter, thereby reducing the burden and average rating of the inverter. A rechargeable battery used as an energy storage supplements the FC during different operating conditions of the drive system. The effectiveness of the proposed method using FC-based linearized IM drive is investigated in simulation, and the efficacy of the proposed controller is validated in real-time. It is evident from the results that the system provides optimal dynamic performance in terms of ripples, overshoot, and settling time responses and is robust in terms of parameters variation and external load

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored

Application of Fuzzy Logic for Performance Enhancement of Drives

Fuzzy logic shows enormous potential for advancing power electronics technology. Its application to DC and AC drives control is discussed here. Initially, a phase-controlled bridge converter DC drive was considered. Analysis of converter performance at continuous and discontinuous conduction modes was first conducted. Fuzzy control was used to linearize the transfer characteristics of the converter in discontinuous conduction mode. It was then extended to current and speed loops, replacing the conventional proportional-integral controllers. The control algorithms were developed in detail, and verified by PC-SIMNON (developed by Lund Institute of Technology Sweden) digital simulation. Significant performance improvement was achieved over conventional control methods. Efficiency optimization of an indirect vector controlled induction motor drive was next considered. An accurate loss model of the converter induction machine system was first developed. Steady-state fundamental and harmonics loss characteristics, besides the dynamic of the machine were analyzed and incorporated in the model, resulting in a new synchronous frame dynamic De-Qe equivalent circuit. The converter system has been modeled accurately for conduction and switching losses. The lossy models were then used in the validation of the fuzzy logic based on-line efficiency optimization control. At steady-state, the fuzzy controller adaptively changes the excitation current on the basis of measured input power, until the maximum efficiency point is reached. The pulsating torque, due to flux reduction, has been compensated by an ingenious feedforward scheme. During transients, rated flux is established, to get the best transient response. After a comprehensive simulation study, an experimental 5 hp drive system was tested, with the proposed controller implemented on a Texas Instrument TMS320C25 digital signal processor, and the theoretical development was fully validated. Finally, fuzzy logic was applied in combination with model-reference adaptive control (MRAC) technique to slip gain tuning of an indirect vector controlled induction motor drive. The MRAC methods based on reactive power and D-axis voltage were combined through a weighting factor, generated by a fuzzy controller, that ensures the use of the best method for any point in the torque-speed plane. A second fuzzy controller tunes the slip gain based on combined detuning error and its slope. The drive performance was extensively investigated through simulations and experiments. The results confirmed the validity of the proposed method

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

Design and Control of Electrical Motor Drives

Dear Colleagues, I am very happy to have this Special Issue of the journal Energies on the topic of Design and Control of Electrical Motor Drives published. Electrical motor drives are widely used in the industry, automation, transportation, and home appliances. Indeed, rolling mills, machine tools, high-speed trains, subway systems, elevators, electric vehicles, air conditioners, all depend on electrical motor drives.However, the production of effective and practical motors and drives requires flexibility in the regulation of current, torque, flux, acceleration, position, and speed. Without proper modeling, drive, and control, these motor drive systems cannot function effectively.To address these issues, we need to focus on the design, modeling, drive, and control of different types of motors, such as induction motors, permanent magnet synchronous motors, brushless DC motors, DC motors, synchronous reluctance motors, switched reluctance motors, flux-switching motors, linear motors, and step motors.Therefore, relevant research topics in this field of study include modeling electrical motor drives, both in transient and in steady-state, and designing control methods based on novel control strategies (e.g., PI controllers, fuzzy logic controllers, neural network controllers, predictive controllers, adaptive controllers, nonlinear controllers, etc.), with particular attention to transient responses, load disturbances, fault tolerance, and multi-motor drive techniques. This Special Issue include original contributions regarding recent developments and ideas in motor design, motor drive, and motor control. The topics include motor design, field-oriented control, torque control, reliability improvement, advanced controllers for motor drive systems, DSP-based sensorless motor drive systems, high-performance motor drive systems, high-efficiency motor drive systems, and practical applications of motor drive systems. I want to sincerely thank authors, reviewers, and staff members for their time and efforts. Prof. Dr. Tian-Hua Liu Guest Edito