Multi-objective torque control of switched reluctance machine

PhD ThesisThe recent growing interest in Switched Reluctance Drives (SRD) is due to the electrification of many products in industries including electric/hybrid electric vehicles, more-electric aircrafts, white-goods, and healthcare, in which the Switched Reluctance Machine (SRM) has potential prospects in satisfying the respective requirements of these applications. Its main merits are robust structure, suitability for harsh environments, fault-tolerance, low cost, and ability to operate over a wide speed range. Nevertheless, the SRM has limitations such as large torque ripple, high acoustic noise, and low torque density. This research focuses on the torque control of the SRD with the objectives of achieving zero torque error, minimal torque ripple, high reliability and robustness, and lower size, weight, and cost of implementation. Direct Torque Control and Direct Instantaneous Torque Control are the most common methods used to obtain desired torque characteristics including optimal torque density and minimized torque ripple in SRD. However, these torque control methods, compared to conventional hysteresis current control, require the use of power devices with a higher rating of about 150% to achieve the desired superior performance. These requirements add extra cost, conduction loss, and stress on the drive’s semiconductors and machine winding. To overcome these drawbacks, a simple and intuitive torque control method based on a novel adaptive quasi sliding mode control is developed in this study. The proposed torque control approach is designed considering the findings of an investigation performed in this thesis of the existing widely used control techniques for SRD based on information flow complexity. A test rig comprising a magnet assisted SRM driven by an asymmetric converter is constructed to validate the proposed torque control method and to compare its performance with that of direct instantaneous torque control, and current hysteresis control methods. The simulation and experimental results show that the proposed torque control reduces the torque ripple over a wide speed range without demanding a high current and/or a high switching frequency. In addition, It has been shown that the proposed method is superior to current hysteresis control method in the sensorless operation of the machine. Furthermore, the sensorless performance of the proposed method is investigated with the lower component count R-Dump converter. The simulation results have also demonstrated the excellent controller response using the standard R-Dump converter and also with its novel version developed in this thesis that needs only one current sensor

Force control using predictive functional control (PFC) algorithm for two chambers soft actuator

The current trend in the world of automation and robotics heavily applies metal structure type of the actuators which are heavy, rigid, difficult and expensive to develop. Other areas of applications like medical, agriculture, biological and welfare requires less rigid and safer robots. Thus, a biologically inspired robot is required to meet this certain criteria. This lead to the recent attraction in the study and development of Pneumatic Soft Actuator (PSA) because it has more advantages over hard actuators to suit the applications mentioned above due to its simple structure, low cost, high efficiency, high compliance, high power to weight ratio and ensures safe and more natural way of interaction. Despite the advantages of pneumatic soft actuator it has nonlinearity and hysteresis, which makes them difficult to model and control. The main objective of this study was to obtain mathematical model and control the force of a two chamber pneumatic soft actuator. Obtaining nonlinear mathematical model accurately to be used in controller design needs to determine all physical parameters of the real system which is very expensive and time consuming, to simplifying this procedure, model of system was analysed and obtained using system identification toolbox in MATLAB software. Input and output data was acquired from an experimental setup which was used to obtain a transfer function force model of the system. The best model was accepted based on the best fit criterion through SI toolbox. Predictive Functional Controller (PFC) was designed and simulated for the model via MATLAB/Simulink. The results showed that PFC controller provides better output than a conventional PID controller when tested using several references. PFC controller exhibits faster response to the system with desired transient error. The study represented in this project can be further broaden by taken position control into account and validation of the simulated control can be done on the experimental setup