This thesis describes a practical application of two CAD packages, CORMAT and CAIAD, for the determination of transfer function models from input/output records and their use in a controller synthesis design. Data records used are taken from PRBS tests applied to a MIMO pilot-scale process running under computer control, while operating in both open and closed loop modes. Both CORMAT and CAIAD are capable of being run within the constraints of a mini computer with backing store and provide, for the SISO and MIMO case; 1) Correlation Model Matching 2) Automatic parameter estimation via Least Squares 3) Model verification via simulation 4) Limited version of 1), 2) and 3) above 5) Automatic model order determination 6) Controller design via conventional PID algorithm 7) Controller synthesis via Block Diagram Algebra (1-3 CORMAT) (4 -7 CAID) Both packages promote user interaction, with final and intermediate results being supplied/displayed in the time-domain. Several 'rules of thumb' have been developed for the application of PRBS tests in the MIMO Case. Identified process models are analysed from open and closed loop tests and used in a controller design. Design is performed using both conventional PID and synthesised controllers.

In the real world there are three types of multivariable control systems. The first one is when the number of inputs is equal to the number of the outputs, this type of multivariable control system is defined as a squared multivariable control system and the main type of controller designed is a decoupling controller which minimizes interactions and gives good set-point tracking. The second type of multivariable control system is where the number of inputs is greater than the number of the outputs, for this type of system the main controller designed is a fail-safe controller. This controller remains stable if a sub-set of actuator fail. The third type of multivariable control system is the number of outputs is greater than the number of inputs, for this type of system the main controller designed is an override control system. This controller only controls a sub-set of outputs based on a lowest wins control strategy. All the three types of multivariable control systems are included in this thesis. In this thesis the design of multivariable decoupling control, multivariable fail-safe control and multivariable override control as considered. The invention of evolutionary computing techniques has changed the design philosophy for control system design. Rather than using conventional techniques such as Nyquest plots or root-loci control systems can be designed using evolutionally algorithm. Such algorithms evolve solutions using cost functions and optimization. There are a variety of system performance indicators such as integral squared error operator has been used as cost functions to design controllers using such algorithms. The design of both fail-safe and override multivariable controllers is a difficult problem and there are very few analytical design methods for such controllers. Therefore, the main objective of this thesis is to use the genetic algorithms to involve both fail-safe and override controller multivariable controllers, such that they perform well in the time-domain.

A topical and important aspect of robotics research is in the area of human-robot interaction (HRI), which addresses the issue of cooperation between a human and a robot to allow tasks to be shared in a safe and reliable manner. This thesis focuses on the design and development of an appropriate set of behaviour strategies for human-robot interactive control by first understanding how an equivalent human-human interaction (HHI) can be used to establish a framework for a robotic behaviour-based approach. To achieve the above goal, two preliminary HHI experimental investigations were initiated in this study. The first of which was designed to evaluate the human dynamic response using a one degree-of-freedom (DOF) HHI rectilinear test where the handler passes a compliant object to the receiver along a constrained horizontal path. The human dynamic response while executing the HHI rectilinear task has been investigated using a Box-Behnken design of experiments [Box and Hunter, 1957] and was based on the McRuer crossover model [McRuer et al. 1995]. To mimic a real-world human-human object handover task where the handler is able to pass an object to the receiver in a 3D workspace, a second more substantive one DOF HHI baton handover task has been developed. The HHI object handover tests were designed to understand the dynamic behavioural characteristics of the human participants, in which the handler was required to dexterously pass an object to the receiver in a timely and natural manner. The profiles of interactive forces between the handler and receiver were measured as a function of time, and how they are modulated whilst performing the tasks, was evaluated. Three key parameters were used to identify the physical characteristics of the human participants, including: peak interactive force (fmax), transfer time (Ttrf), and work done (W). These variables were subsequently used to design and develop an appropriate set of force and velocity control strategies for a six DOF Stäubli robot manipulator arm (TX60) working in a human-robot interactive environment. The optimal design of the software and hardware controller implementation for the robot system has been successfully established in keeping with a behaviour-based approach. External force control based on proportional plus integral (PI) and fuzzy logic control (FLC) algorithms were adopted to control the robot end effector velocity and interactive force in real-time. ii The results of interactive experiments with human-to-robot and robot-to-human handover tasks allowed a comparison of the PI and FLC control strategies. It can be concluded that the quantitative measurement of the performance of robot velocity and force control can be considered acceptable for human-robot interaction. These can provide effective performance during the robot-human object handover tasks, where the robot was able to successfully pass the object from/to the human in a safe, reliable and timely manner. However, after careful analysis with regard to human-robot handover test results, the FLC scheme was shown to be superior to PI control by actively compensating for the dynamics in the non-linear system and demonstrated better overall performance and stability. The FLC also shows superior performance in terms of improved sensitivity to small error changes compared to PI control, which is an advantage in establishing effective robot force control. The results of survey responses from the participants were in agreement with the parallel test outcomes, demonstrating significant satisfaction with the overall performance of the human-robot interactive system, as measured by an average rating of 4.06 on a five point scale. In brief, this research has contributed the foundations for long-term research, particularly in the development of an interactive real-time robot-force control system, which enables the robot manipulator arm to cooperate with a human to facilitate the dextrous transfer of objects in a safe and speedy manner.

Unique historical data from UK criticality experiments with intermediate enriched uranium (IEU) have been collated, reviewed and evaluated as criticality safety benchmark experiments. Four benchmark evaluations, detailing 136 configurations, have been accepted by the International Criticality Safety Benchmark Evaluation Project (ICSBEP) and published in the International Handbook of Evaluated Criticality Safety Benchmark Experiments. This work has increased the number of published IEU benchmark configurations from 125 to the current total of 261. An overview of the experiments, a description of the evaluations and a summary of the benchmark models are provided. Sample calculational results obtained with the Monte Carlo codes MONK and MCNP, using the JEF-2.2 and ENDF/B-VII.0 nuclear data-sets are presented. In order to analyse the data, a novel data assimilation technique employing Kalman filtering is derived. This uses sensitivity data, relating changes in the neutron multiplication parameter keff , to perturbations in the underlying nuclear data. The sensitivity module of MONK, used to obtain these data, is compared to similar codes as part of an expert group study and is shown to give results in good agreement. Also utilised are covariance matrices for uncertainties in the nuclear data, benchmark keff and the sensitivity data itself-the sources of these data are explained. The assimilation scheme is tested using a sample set of benchmark experiments to demonstrate its functionality. The newly developed IEU benchmarks are used with the assimilation scheme coupled to MONK, in order to calculate adjustments to the ENDF/B-VII.0 nuclear data. Similar, independent benchmarks are also selected for use in the analysis, eliminating those which show significant statistical inconsistencies. Conclusions are drawn from this analysis; regions for consideration of the nuclear data are discussed and computational biases and associated trends in the calculated keff data are provided. Finally, suggestions for further work are described; these include further expansion of benchmark data, software developments, alternative data assimilation methods and possible design properties for future integral experiments.

Humanoid robots are considered as complex and challenging platforms, and the state of the art in robotics. Humanoid robots are naturally expected to perform a wide variety of tasks using the same tools as humans, to operate in unconstrained environments, and to interact with other robots and humans in the same way we do. Humanoid robots are envisaged to be used in hazardous environments and as assistants to humans in the home or work place. In space, these platforms are considered as pre-human explorers operating in dangerous environments. The suitability of humanoid robots for space exploration has been acknowledged by NASA with the launch of the humanoid Robonaut to the International Space Station. As the expectations of these platforms continues to grow, many challenges still exist on how to control and manipulate such systems to perform the tasks expected humans. For example, maintaining the robots balance under different perturbation, as well as generating a stable, fast and efficient walking gait, is an important requirement that has to be naturally inherited in these platforms. However, the large number of degrees of freedom, and the non-linear chaotic nature of robot dynamics, result in the increased difficulty in manipulating the full body behaviours of these robots. The main goal of this research is to develop an efficient model that captures the full body behaviour accurately, while restoring balance and controlling the locomotion system. The Spherical Inverted Pendulum (SIP) concept was developed to model the biped robot centre of mass motion using the ankle joints. A novel balancing control law based on the principles of dissipative systems is developed and presented. It has been demonstrated that this controller restores balance by dissipating the kinetic energy introduced in the system as a result of disturbances. The SIP model is later used in the development of a balance and locomotion control framework using the concept of passive dynamic walking, and full body inverse kinetics, to achieve efficient and robust locomotion gait for the biped robot. Simulations were used to validate the SIP model and the new control framework for balance restoration and walking. Hardware validation of the multi-task manipulation and the simultaneous execution of tasks is also developed and presented in this thesis using the Nao humanoid robot.

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Robots have been widely used for various applications, such as smart transportation, environment monitoring, surveillance, search and rescue. Autonomous navigation, as a core prerequisite for the robots to successfully realise these applications, relies heavily on robot localisation. Global Positioning System (GPS) fails to satisfy many applications in robotics in terms of accuracy and availability. Therefore, robot localisation in GPS-denied 3D space is in great demand. However, due to sensor noise and real world uncertainty, robot localisation in GPS-denied 3D space is a challenging problem. The work in this thesis describes three novel localisation algorithms to localise the robots accurately and efficiently in different .scenarios. .optimal state estimation, including filter based and optimisation based methods, is adopted to elegantly deal with the noise and the uncertainty in a probabilistic perspective. Firstly, a Moving Horizon Estimation (MHE) based localisation algorithm is proposed for single beacon based robot localisation. The performance and observability analyses are also conducted to evaluate the proposed method. Secondly, single beacon based multi-robot cooperative localisation problem is addressed by a constrained MHE based approach. Its discussion answers why and how multi-robot cooperation and optimisation constraints benefit the localisation system. The initial pose estimation problem and observability analysis of the multi-robot system are also studied. Thirdly, an unscented Kalman filter based algorithm is proposed for Vision-aided Inertial Navigation System (VINS) by only using low-cost camera and Inertial Measurement Unit (IMU) to perform pose estimation and camera-IMU extrinsic self-calibration. Trifocal tensor based geometric constraints and point transfer of three-view geometry are incorporated into VINS. Tested by both simulations and experiments, the proposed methods are verified to be effective for robot localisation in GPS-denied 3D space.

No description available.

No description available.

No description available.