Motor simulation of a shock absorber

The use of modern control theory to produce an electrical motor simulation of a Formula 1, Grand Pnx, passive motorcycle front suspension shock absorber is investigated. It is shown, using a test-rig comprising two permanent magnet DC motors directly coupled, that desired shock absorber responses to load forces can be achieved using model reference control. The controller feedback in this test rig is provided via a high resolution rotary position sensor. A stochastic Kalman filter is used to produce estimates of the load(disturbance), force and velocity from this position information. All states are then used in the controller. A mass, spring and damper model is chosen as a suitable representation of a shock absorber, and is assumed sufficiently complex to justify the control techniques used. This linear model is translated using mathematical techniques into a rotary equivalent that is compatible for use in the controller. This translation takes into account thermal effects, as well as kinematic requirements encountered by the motor on the basis of load-force data taken from the front suspension of a Formula 1 motorcycle in race conditions. The parameters of the mass spring and damper model are found from simple static tests using the shock absorber removed from the bike

Design of a DSP-based servo speed controller

The brushless servo drive is arguably the most important emerging drive category for robotics, machine tools and other applications. This places increasingly high demands on the servo motor and controller. The brushless servo drive is arguably the most important emerging drive category for robotics, machine tools and other applications. This places increasingly high demands on the servo motor and controller. Two PID design methods are studied for the speed controller, an "analog design approach" and a "grapho-analytical pole-placement procedure". The former provided an easy design and the later resulted in a more satisfactory control performance. The thermal protection controller uses a generic lumped capacitance-resistance thermal model to predict the motor temperature. A current limit regulator is developed to maintain the motor temperature below this insulation limit, and to maximize the motor output once the limit is reached. A simulation scheme for this servo system is developed to investigate the control characteristics of the system before experimental testing. The digital speed controller has been implemented using the TMS320C30, a high performance digital signal processor. The control software, written in the TMS320C30 assembly language, is developed. Experimental results are presented, which demonstrate the performance improvement of the designed control system

Real-time implementation of an object-based codec

Modern video coding algorithms are becoming increasingly complex with the result that single general purpose processors are incapable of meeting the computational power required for real time implementation. The coding algorithms are continuously evolving therefore, any multiprocessor solution must not only possess the necessary computational power but must also be flexible enough to adapt to any modifications in the algorithms. This report presents a possible multiprocessor solution with specific reference to the DCU object-based analysis-synthesis coder. Firstly, an abstract model of the multiprocessor system is defined. The model is based on the dual requirements of computational power and flexibility. An analysis of the DCU coding algorithm is performed in order to refine the basic model by identifying potential realisation options that optimise coder performance. A reciprocal relationship exists whereby hardware constraints require modification of the algorithm. Any modifications are outlined and their effect on overall coder performance is investigated. Computational power costs are given for an implementation based on TMS320C30 DSPs. From experimental results it is shown that, despite the complexity of the coding algorithm, real time operation is possible. A decoder based on a single TMS320C30 has been developed that is capable of operating at up to 8 Hz

The application of artificial neural networks to interpret acoustic emissions from submerged arc welding

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Automated fusion welding processes play a fundamental role in modern manufacturing industries. The proliferation of joint geometries together with the large permutation of associated process variable configurations has given rise to research into complex system modelling and control strategies. Many of these techniques have involved monitoring of not only the electrical characteristics of the process but visual and acoustic information. Acoustic information derived from certain welding processes is well documented as it is an established fact that skilled manual welders utilise such information as an aid to creating an optimum weld. The experimental investigation presented in this thesis is dedicated to the feasibility of monitoring airborne acoustic emissions of Submerged Arc Welding (SAW) for diagnostic and real time control purposes. The experimental method adopted for this research takes a cybernetic approach to data processing and interpretation in an attempt to replicate the robustness of human biological functions. A custom designed audio hardware system was used to analyse signals obtained from bead on mild steel plate fusion welds. Time and frequency domains were used in an attempt to establish salient characteristics or identify the signatures associated with changes of the process variables. The featured parameters were voltage / current and weld travel speed, due to their ease of validation. However, consideration has also been given to weld defect prediction due to process instabilities. As the data proved to be highly correlated and erratic when subjected to off line statistical analysis, extensive investigation was given to the application of artificial neural networks to signal processing and real time control scenarios. As a consequence, a dedicated neural based software system was developed, utilising supervised and unsupervised neural techniques to monitor the process. The research was aimed at proving the feasibility of monitoring the electrical process parameters and stability of the welding process in real time. It was shown to be possible, by the exploitation of artificial neural networks, to generate a number of monitoring parameters indicative of the welding process state. The limitations of the present neural method and proposed developments are discussed, together with an overview of applied neural network technology and its impact on artificial intelligence and robotic control. Further developments are considered together with recommendations for future areas of research

Vocal tract acoustic measurements and their application to articulatory modelling

In the field of speech research it is agreed that more real data is required to improve the articulatory modelling of the vocal tract. Acoustic techniques may be used to acquire vocal tract data. The advance of digital signal processing has allowed the development of new experimental techniques that allow fast and efficient measurements. DSP based measurement systems were set up, and acoustic impedance and transfer function measurements were performed on a wide variety of subjects in DCU’s semianechoic chamber. The measurement systems are compact and reproducible. The variation of the wall vibration load was investigated in a wide range of human subjects. The investigation was prompted by the question: Is the wall vibration load important in the study and implementation of vocal tract and articulatory models? The results point to the possible need in acoustic to articulatory inversion, of adapting the reference model to specific subjects by separately estimating the wall impedance load

Ease: a real-time multitasking executive

Ease the real time multitasking executive described m this thesis is designed for embedded systems with particular emphasis on DSP motor control applications. Ease provides an application software interface to the underlying hardware and encourages an object oriented programming approach which inherently enhances software integrity, maintainability and dependability in the potentially chaotic real time environment. Its focus is to tackle the undesirable aspects of real time programming and device dependent issues thereby allowing the application programmer to concentrate more on the application. The multitasking aspect of the executive means application tasks can be generated with ease which aids development, evolution or enhancement of an application. The multitasking aspect also facilitates tasks dedicated to on-line reconfiguration, error handling and fault correction or shutdown procedures. The software quality of a real time application running on the Ease platform is paid for by a small percentage of CPU processing power and a larger response time to external events than an unstructured monolithic interrupt driven system. During the course of research, development and prototyping of Ease , a number of suitable sample applications have been explored to test and optimise its functionality. The most notable of these is the control system for the motor simulation of a shock absorber with an active disturbance load. This was implemented as seven concurrent tasks in a uniprocessor DSP system, running Ease