In most teleoperation applications the human operator is required to monitor the status of the robot, as well as, issue controlling commands for the whole duration of the operation. Using a vision based feedback system, monitoring the robot requires the operator to look at a continuous stream of images displayed on an interaction screen. The eyes of the operator therefore, are fully engaged in monitoring and the hands in controlling. Since the eyes of the operator are engaged in monitoring anyway, inputs from their gaze can be used to aid in controlling. This frees the hands of the operator, either partially or fully, from controlling which can then be used to perform any other necessary tasks. However, the challenge here lies in distinguishing between the inputs that can be used for controlling and the inputs that can be used for monitoring. In mobile robot teleoperation, controlling is mainly composed of issuing locomotion commands to drive the robot. Monitoring on the other hand, is looking where the robot goes and looking for any obstacles in the route. Interestingly, there exist a strong correlation between human's gazing behaviours and their moving intentions. This correlation has been exploited in this thesis to investigate novel means for mobile robot teleoperation through eye-gaze, which has been named TeleGaze for short. The contribution of this thesis is a well designed and extensively evaluated novel interface for TeleGaze, that enables hands-free mobile robot teleoperation. Since the interface is the only part of an interactive system that the remote user comes into direct contact, the thesis covers different phases of design, evaluation, and critical analysis of the TeleGaze interface. Three different prototypes (Native, Multimodal & Refined Multimodal) have been designed and evaluated using observational and task-oriented studies. The result is a novel interface, that interprets the gazing behaviour of the human operator into controlling commands in an intuitive manner. The interface demonstrates a comparable performance to that of a conventional joystick operated system, with the significant advantage of hands free control, for a number of mobile robot teleoperation applications; provided the limitations of calibration and drift are taken into account.

Many functional electrical stimulation (FES) controllers have been developed using a simulation approach, the performance of these controllers depends on the muscle model accuracy. Realistic models of neuro-musculoskeletal systems can provide a safe and convenient environment for the design and evaluation of FES controllers. A typical FES system consists of FES controller, an electrical stimulator, electrodes and sensors. During FES, the stimulation level can change in a continuous fashion such that different motor-units are recruited at different muscle lengths and at different times. Furthermore, it is also not accurate to use the instantaneous length as input to the force-length relationship in dynamic (non-isometric) situations. Although instantaneous CE length is commonly used in FES control studies, empirical data from the literature were reviewed and it was concluded that the CE length at initial recruitment is a key parameter influencing total muscle force. The author presents a new multiple motor-unit Hill-type muscle model that accounts for different motor units being recruited at different CE lengths and different times. Hence the model can account for a continuously changing recruitment level whilst using the individual motor unit lengths at initial recruitment as input to the force-length relationship. Moreover, the model is capable of modelling fatigue and force enhancement & depression for the individual motor-units (i.e. the recruitment and time history effects). The model can also take account of the different force-length and force-velocity relationships for different fibre types by modelling these properties for the individual motor-units. The new multiple motor-unit model is described in detail, implemented and tested in Matlab. Open-loop simulation protocols are made on single/multiple motor-unit models using different CE lengths for the force-length relationship; on single/multiple motor-unit fatigue sub-models; and on single/ multiple motor-unit force enhancement & depression sub-models. A general model that can be used to represent all relevant models from the literature was developed. This model can also be used to build new models at different levels of complexity. Such a “General Model” could be used to study the effect of model complexity on FES controller design so that appropriate trade-offs between model complexity and accuracy could be determined. Results, limitations and possible future work are discussed.

The world around us exhibits a rich and ever changing environment of startling, bewildering and fascinating complexity. Almost everything is never as simple as it seems, but through the chaos we may catch fleeting glimpses of the mechanisms within. Throughout the history of human endeavour we have mimicked nature to harness it for our own ends. Our attempts to develop truly autonomous and intelligent machines have however struggled with the limitations of our human ability. This has encouraged some to shirk this responsibility and instead model biological processes and systems to do it for us. This Thesis explores the introduction of continuous time delays into biologically inspired dynamic control systems. We seek to exploit rich temporal dynamics found in physical and biological systems for modelling complex or adaptive behaviour through the artificial evolution of networks to control robots. Throughout, arguments have been presented for the modelling of delays not only to better represent key facets of physical and biological systems, but to increase the computational potential of such systems for the synthesis of control. The thorough investigation of the dynamics of small delayed networks with a wide range of time delays has been undertaken, with a detailed mathematical description of the fixed points of the system and possible oscillatory modes developed to fully describe the behaviour of a single node. Exploration of the behaviour for even small delayed networks illustrates the range of complex behaviour possible and guides the development of interesting solutions. To further exploit the potential of the rich dynamics in such systems, a novel approach to the 3D simulation of locomotory robots has been developed focussing on minimising the computational cost. To verify this simulation tool a simple quadruped robot was developed and the motion of the robot when undergoing a manually designed gait evaluated. The results displayed a high degree of agreement between the simulation and laser tracker data, verifying the accuracy of the model developed. A new model of a dynamic system which includes continuous time delays has been introduced, and its utility demonstrated in the evolution of networks for the solution of simple learning behaviours. A range of methods has been developed for determining the time delays, including the novel concept of representing the time delays as related to the distance between nodes in a spatial representation of the network. The application of these tools to a range of examples has been explored, from Gene Regulatory Networks (GRNs) to robot control and neural networks. The performance of these systems has been compared and contrasted with the efficacy of evolutionary runs for the same task over the whole range of network and delay types. It has been shown that delayed dynamic neural systems are at least as capable as traditional Continuous Time Recurrent Neural Networks (CTRNNs) and show significant performance improvements in the control of robot gaits. Experiments in adaptive behaviour, where there is not such a direct link between the enhanced system dynamics and performance, showed no such discernible improvement. Whilst we hypothesise that the ability of such delayed networks to generate switched pattern generating nodes may be useful in Evolutionary Robotics (ER) this was not borne out here. The spatial representation of delays was shown to be more efficient for larger networks, however these techniques restricted the search to lower complexity solutions or led to a significant falloff as the network structure becomes more complex. This would suggest that for anything other than a simple genotype, the direct method for encoding delays is likely most appropriate. With proven benefits for robot locomotion and the open potential for adaptive behaviour delayed dynamic systems for evolved control remain an interesting and promising field in complex systems research.

Search and Rescue is a vitally important subject, and one which can be improved through the use of modern technology. This work presents a number of advances aimed towards the creation of a swarm of autonomous, collaborative, unmanned aerial vehicles for land-based search and rescue. The main advances are the development of a diffusion based search strategy for route planning, research into GPS (including the Durham Tracker Project and statistical research into altitude errors), and the creation of a relative positioning system (including discussion of the errors caused by fast-moving units). Overviews are also given of the current state of research into both UAVs and Search and Rescue.

This thesis addresses the problem of real-time optimal control of aircraft systems using parallel processing techniques. It is shown that transputer hardware can be used in designing a suitable optimal controller for general nonlinear time-varying aircraft. In the first part of the thesis, nonlinearties and time varying aspects of the aircraft system, together with the current available solutions are investigated and suitable designs presented. Here the linear regulator approach for linear time-varying aircraft is investigated first but it is shown that real-time performance is difficult to achieve. The problem is then approached differently in that the aircraft is considered as a linear time-invariant system for short time intervals and it is then found possible to implement an optimal control solution in real-time, and suitable multi-transputer architectures are presented. The receding/moving horizon approach is applied to the aircraft system and is shown to be adequate for achieving satisfactory results. The problem of selection of the weights in the performance index of the optimal control problem is then studied and a design procedure is presented. The modeling of the aircraft as decoupled longitudinal and lateral dynamics is investigated and approached in such a way as to reduce the cross-coupling effects. Another important aspect of this research involves the consideration of failure detection and diagnosis in the aircraft hardware. Problems including actuator failure are studied and some remedial methods for handling the failures by enabling system reconfiguration after the occurrence of the failure are presented. The multi-processor based control system design is shown to offer a viable solution to solving complicated optimisation problems without the need for the simplification of the system dynamical equations and thereby loosing accuracy. Such simplification is usually a prerequisite for enabling practical designs. However with the use of parallel processing techniques such designs can be achieved for the more complicated (and more computationally demanding) cases as well.

This thesis is concerned with the control aspects for underwater tasks performed by marine robots. The mathematical models of an underwater vehicle and an underwater vehicle with an onboard manipulator are discussed together with their associated properties. The task-space regulation problem for an underwater vehicle is addressed where the desired target is commonly specified as a point. A new control technique is proposed where the multiple targets are defined as sub-regions. A fuzzy technique is used to handle these multiple sub-region criteria effectively. Due to the unknown gravitational and buoyancy forces, an adaptive term is adopted in the proposed controller. An extension to a region boundary-based control law is then proposed for an underwater vehicle to illustrate the flexibility of the region reaching concept. In this novel controller, a desired target is defined as a boundary instead of a point or region. For a mapping of the uncertain restoring forces, a least-squares estimation algorithm and the inverse Jacobian matrix are utilised in the adaptive control law. To realise a new tracking control concept for a kinematically redundant robot, subregion tracking control schemes with a sub-tasks objective are developed for a UVMS. In this concept, the desired objective is specified as a moving sub-region instead of a trajectory. In addition, due to the system being kinematically redundant, the controller also enables the use of self-motion of the system to perform sub-tasks (drag minimisation, obstacle avoidance, manipulability and avoidance of mechanical joint limits).

Caused by a rising mass customisation and the high variety of equipment versions, the exibility of manufacturing systems in car productions has to be increased. In addition to a exible handling of production load changes or hardware breakdowns that are established research areas in literature, this thesis presents a skill-based recon guration mechanism for industrial mobile robots to enhance functional recon gurability. The proposed holonic multi-agent system is able to react to functional process changes while missing functionalities are created by self-organisation. Applied to a mobile commissioning system that is provided by AUDI AG, the suggested mechanism is validated in a real-world environment including the on-line veri cation of the recon gured robot functionality in a Validity Check. The present thesis includes an original contribution in three aspects: First, a recon - guration mechanism is presented that reacts in a self-organised way to functional process changes. The application layer of a hardware system converts a semantic description into functional requirements for a new robot skill. The result of this mechanism is the on-line integration of a new functionality into the running process. Second, the proposed system allows maintaining the productivity of the running process and exibly changing the robot hardware through provision of a hardware-abstraction layer. An encapsulated Recon guration Holon dynamically includes the actual con guration each time a recon guration is started. This allows reacting to changed environment settings. As the resulting agent that contains the new functionality, is identical in shape and behaviour to the existing skills, its integration into the running process is conducted without a considerable loss of productivity. Third, the suggested mechanism is composed of a novel agent design that allows implementing self-organisation during the encapsulated recon guration and dependability for standard process executions. The selective assignment of behaviour-based and cognitive agents is the basis for the exibility and e ectiveness of the proposed recon guration mechanism.

The thesis considers the development and application of second order sliding mode control algorithms. Second order sliding mode control keeps the main advantages of standard sliding modes and has the additional advantage that it can be used to remove chattering effect, providing smooth or at least piecewise smooth control. The method also provides better accuracy with respect to switching delays.;A comparison has been made between dynamic sliding modes and higher order sliding modes. The application of dynamic sliding mode control has been demonstrated for systems not affine in the control in a MIMO case study for the control of an IC engine. The super-twisting algorithm has been implemented for robust speed control of a diesel engine available in the laboratory where the sliding variable has relative degree one with respect to the control input. A theoretical case has been made for the application of the algorithm and bounds on the controller parameters have been generated. The implementation results demonstrate the practical importance of higher order sliding mode control.;A new second order-sliding algorithm has been developed to stabilize systems where the sliding variable has relative degree two with respect to the control input. More over, it does not require the derivative of the sliding variable to be measured or observed and hence reduces the number of sensors required for control implementation. Closed loop simulation of various systems has been carried out to validate the theory. The algorithm has been applied using dSPACE for position and speed control of a DC motor in SISO configuration.;The algorithm has also been extended for a class of nonlinear uncertain MIMO systems. A MIMO case study for water level control in coupled twin-tanks system has been presented. The controller has been implemented in the laboratory to validate the theoretical assertions made in the thesis.

This thesis constitutes a contribution to the theory of extremal control systems which come within the automatic control field of learning in engineering science. An extremal control system comprises an extremal process (which is to be controlled) and an extremal controller. The class of extremal control systems referred to in the title of the thesis refers to those systems in which the extremal process concerned can represented by a particular form of mathematical model. Investigation of the application of optimal control theory to this class of extremal control system is motivated by two basic requirements. The first of these originates in the control of complex industrial processes, particularly in the direct digital control situation. Here there are a number of possible applications for extremal control, and since costs involved are generally high, the requirement is generally for extremal controllers maintaining as low a system operating cost as possible, rather then for controllers with a simple structure. Hence there is a need for optimal extremal controllers. The second requirement for establishing optimal extremal controllers lies in the design of simpler extremal controllers. The performance of the optical extremal controller is required as a basic on which to judge the simpler controllers and decide whether any more significant improvement can be made. The major part of this investigation of the application of optimal control theory to extremal control systems is concerned with the simplest possible case, where no account is taken of input or output lags or noise, or of multiple inputs. Since no previous optical extremal controllers known this is the natural starting point. A rigorous analysis of state variables, probability nu sufficient statistics for this simplified case is presented, and this leads on to a new approach to the application of dynamic programming which in turn results in an original functional recurrence equation. Analysis of this functional recurrence equation leads to s numerical solution procedure including many checks. This eventually establishes the optical extremal controller. Simulation techniques are used to confirm the performance of the optimal extremal controller, and hybrid computing facilities used to show that it can be implemented on a small on-line computer and used in a direct digital control situation without suffering from interfacing effects. Thus for the first time there is now available an optimal extremal controller, and moreover it can be confidently expected to perform optimally in a practical situation. Comparison of the performance of the optimal extremal controller with the performance of simpler controllers shows that, in the simplified case, there is still room for considerable improvement on the simple controllers, and a quantitative measure of just how much improvement might be possible is now available. An initial investigation of the application of optimal control theory to more complex processes, involving noise, lags and multiple inputs, is presented and this shows that theoretical difficulties are likely to prevent further optimal extremal controllers from being established. In these cases there is therefore a requirement to establish closely optimal controllers. One approach would be just to use the optimal controller from the simplified case in these more complex situations. Simulations are presented establishing the performance of the optimal extremal controller, and a suboptimal extremal controller, controlling not the process for which they were designed but a similar process involving output noise. These simulations show that these controllers are certainly not optimal in the more complex situation. A different approach must therefore be taken to establishing closely optimal controllers in the more complex situation. The thesis finishes with a discussion of how this might be achieved.

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