This thesis considers two areas of robust control. Part I considers continuous H control. The theory is applied to a scalar flexible transmission system that has non-minimum phase zeros and lightly damped modes that vary with applied load. A robust solution is obtained that gives good performance results. The capabilities of H techniques are more fully demonstrated on a research civil aircraft model (RCAM) flight control problem. A novel architecture for an autopilot to fly the RCAM along the final approach to landing is designed. Good results are obtained for the autopilot that incorporates controllers designed using both two degree-of-freedom H mixed sensitivity and H loop shaping techniques. In terms of a pre-defined mission scenario the overall results for performance, robustness, ride quality, safety and control effort are some of the best published, they demonstrate to the aerospace community the applicability and benefits of the methods. Part II considers discrete time-varying finite horizon control. A number of new results in this area are presented, some being specialisations or extensions of existing finite horizon and time-invariant results, for example, means of computing the finite horizon norm and relationships between symplectic matrix equations and Riccati equations. Furthermore, normalised (coprime) factorisations and controller parameterisation results have enabled the optimum norm for the normalised left factored plant problem to be explicitly formulated. Formulae for a particular class of the problem are presented. A simplifying formula for the solution to the control Riccati equation of the problem is derived and a class of sub-optimal solutions, using non-zero terminal weights, is considered. The controller formulae are applied to a one-degree-of-freedom intercept problem with encouraging results. Robustness to relative lateral position errors and target acceleration perturbations are compared for the zero and non-zero terminal state weight cases.

Tandem cold rolling presents difficult challenges to the control engineer: the mill is a nonlinear multivariable system, limited instrumentation is available to measure product quality, the deformation process is uncertain, there are significant material transport delays and practical mill operation is required over a wide range of speeds with a variety of rolled products, introducing significant variation in the mill dynamics. A robust multivariable control solution is sought in this thesis. A nonlinear simulation of an open-loop mill is developed and validated against published data. A methodology for designing H loop shaping controllers is presented. Controller development, based on a typical industrial structure, is undertaken for comparative purposes and both types of controller are evaluated at full mill speed in the face of a wide range of disturbances. A gain scheduling scheme, with rules for weight modification at the intermediate operating points, is designed for mill acceleration. Potential for improved product quality is seen with the H controller. Theoretical studies into H optimization problems are also undertaken. In particular, the well-known problem of pole-zero cancellation is addressed. A novel construction of weighting function in a mixed sensitivity design enables the cancellation phenomenon to be exploited and is shown to act as a mechanism for partial pole placement. It is also shown how pole-zero cancellation arises with H loop shaping for particular classes of plant. Further perceived shortcomings of the H loop shaping method, namely the relationship between shaped and nominal plant uncertainty and the mathematical intractability of the uncertainty model, are afforded consideration. Several structured uncertainty models are investigated and relationships uncovered between H loop shaping and -synthesis. A structured loop shaping design is motivated: a solution via - K iteration yields an interesting robust stability interpretation, while the design is shown to have attractive robust stability and robust performance potential.

This thesis deals with the industrial application of sliding mode controllers. Sliding mode controllers based on both linear models and nonlinear-models are considered. Special attention is paid to the nonlinear modelling of the systems for sliding mode controller design. The possibility of using neural networks for model generation is explored. Novel schemes for uncertainty bounds estimation are introduced and subsequently used for robust sliding mode controller design. Later, a novel approach for sliding mode based parameter estimation for a nonlinear model with known structure but unknown parameters is introduced. This parameter estimation scheme is integrated with sliding mode controller design to provide an overall controller design framework. The stability of these schemes is proven through quadratic stability concepts. The sliding mode controller design frameworks mentioned above are verified and tested on challenging industrial examples. The temperature control of a high temperature multiburner industrial furnace is a highly coupled and extremely nonlinear problem. A multiburner furnace nonlinear simulation facility is established and used for linear identification and subsequently linear model based sliding mode controller testing. For comparison purposes a two degree of freedom H controller is also designed and tested. Then a nonlinear model based controller is tested on a single burner furnace simulation. Idle speed control of an automobile engine is an extremely difficult control problem characterised with severe nonlinearities, gross disturbances and huge time delays. A sliding mode controller is designed for this problem and successfully implemented on a test rig. Later on, a nonlinear model based sliding mode controller is designed for the same problem and successfully tested.

This thesis deals with sampled-data implementations of continuous-time, non-linear control systems. The basis for the analysis is a static, continuous-time feedback law for non-linear, affine systems with bounded input gain. The sampled-data implementation is obtained from the discretization of the control via a sample-and-hold-process. With the incorporation of the aspect of robustness, a theoretical framework is created which supersedes previous work concentrating on stability. Bounding constraints for the closed-loop differential system allow uncertainty and disturbances to be considered. Other assumptions for the continuous-time control are Lipschitz continuity, exponential decay outside a compact set and existence of a Lyapunov function. The important parameter for the discretization analysis is the sampling time; fast sampling implies robust stability. The controller sampling residual, the difference between the discretized and the original control, is of key interest within a Lyapunov-type stability analysis; suitable norms, such as the Euler norm, are chosen to find upper bounds for the sampling residual. The generalization of a result from linear to non-linear sampled-data control permits the application of the Lp-norm. The theoretical framework is also suitable for dynamic control systems and the investigation of computational delays. The analysis approaches are demonstrated for two different robust control. strategies .based on sliding-mode approaches. A state-feedback sliding-mode-based control extends ideas for smoothing discontinuous sliding-mode control components by introducing a cone-shaped sliding-mode layer. A non-smooth Lyapunov function is used to prove stability of the discretized control. An observer-based tracking control improves a previous control scheme by considering a class of non-minimum phase and relative-degree-zero plants. Simulation and numerical fast-sampling analysis results are provided for all developed discretization and sliding-mode-based control techniques in application to non-trivial examples. The simulation of a highly non-linear, large-scale chemical plant for benzene production with non-minimum phase and relative-degree-zero characteristics proves the effectiveness of sliding-mode output control.

This thesis deals with perturbation and error analysis in robust control, mainly H control, but the H2 norm is also considered. Perturbation analysis investigates the sensitivity of a solution or structure to perturbations or uncertainties in the input data. Error analysis is used to make statements about the numerical stability of an algorithm and uses results from perturbation analysis. Although perturbation and error analysis is a well-developed field in linear algebra, very little work has been done to introduce these concepts into the field of control. This thesis attempts to improve this situation. The main emphasis of the thesis is on H norm computations. Nonlinear and linear perturbation bounds are derived for the H norm. A rigorous error analysis is presented for two methods of computing the H norm: the Hamiltonian method and the SVD method. Numerical instability of the Hamiltonian method is shown with several examples. The SVD method, which is shown to be numerically stable, is updated with new upper and lower bounds for the frequency response between two given frequency points. Then using an upper frequency bound, a new algorithm is presented. This new algorithm can be implemented in a parallel process and has a similar performance to the Hamiltonian method in terms of computing time. In addition, nonlinear and linear perturbation bounds are derived for the H2 norm, and for the solutions of Lyapunov equations. Finally the H control problem is considered and perturbation bounds for the corresponding parameterized Riccati equations are derived. This leads to an estimation of the norm of the perturbation in the H controller.

This thesis has discussed the development and implementation of robust nonlinear tracking control for a parallel and serial topology Tetrahedral robot (Tetrabot), although the theoretical control strategy presented is applicable to any manipulator tracking problem. The design of robust tracking controllers involves deriving a tracking law for uncertain dynamic systems, such that the actual positions closely track desired trajectories. Two new schemes, a robust sliding mode control and a Lyapunov-based robust tracking control, have been presented for uncertain dynamical systems in the presence of model uncertainty and disturbances. The foci of this study are the concepts and techniques of robust nonlinear tracking control with a bias toward industrial applications. The Tetrabot system structure, hardware, software and the results of implementation on the three degree of freedom parallel geometry have been studied. In order to implement robust tracking control laws, the Tetrabot system software has been further developed. Most importantly, the results of implementation of a nonlinear tracking controller on the Tetrabot rig facility are also studied. To demonstrate the performance attainable by this control strategy, the trajectory involved movement across the primary working volume to the end-effect point which is the largest distance possible and involved the continuous motion; such a motion will invoke a wide range of possible nonlinear dynamic representations. The proposed control strategy is robust to variations in robot loading. The experimental results obtained for the closed-loop response indicate that compensation, which employs explicit off-line parameter estimation, can improve tracking accuracy significantly. Using the robust tracking controllers, the position errors were smaller than those obtained using the original PID controllers. The robust tracking controller showed excellent results.

This thesis describes research which is aimed at devising a framework for a feature based workshop oriented NC planning. The principal objective of this thesis is to utilize a feature based method which can rationalize and enhance part description and in particular part planning and programming on the shop-floor. This work has been done taking into account new developments in the area of shop floor programming. The importance of the techniques and conventions which are addressed in this thesis stems from the recognition that the most effective way to improve and enhance part description is to capture the intent of the engineering drawing by devising a medium in which the recurring patterns of turned components can be modelled for machining. Experimental application software which allows the user to describe the workpiece and subsequently generate the manufacturing code has been realized.

Robot grasping and manipulation require very accurate and timely knowledge of the manipulated object's shape and pose to succesfully perform a desired task. One of the main reasons current systems fail to carry out complex tasks in a real, unstructured environment is their inability to accurately determine where in the object the fingers are touching. Most systems use vision to detect the pose of an object, but the performance of this sensing modality deteriorates as soon as the robot grasps the object. When the robot hand contacts an object, it partially occludes it, which makes it difficult for vision systems to track the object's location. This thesis presents algorithms to use the robot's available tactile sensing to correct the visually determined pose of a grasped object. This method is extended to globally estimate the pose of the object even when no initial estimate is given. Two different tactile sensing strategies have been employed: single-point and distributed, and measurement models for these two strategies are presented. Different optimisation algorithms are developed and tested to minimise the output of these measurement models and find one or more poses that satisfy current tactile measurements. Results show that the method is able to successfully estimate the pose of a grasped object with high accuracy, even for objects with a high degree of geometric complexity. Other applications of the method are proposed, such as determining grasp stability or identifying the grasped object, as well as future research directions.

This thesis establishes the “assurance technique” as the central mechanism through which we gather evidence to make claims of assurance about security. The use of such assurance techniques in the process of assessing Industrial Control System (ICS) environments is explored. In doing so it provides six key contributions to knowledge: (i) a state-of-the-art survey of ICS security research, which culminates in a framework for future research, of which the assessment of security control efficacy is one element; (ii) claims about the effectiveness and cost-effectiveness of 20 assurance techniques used to assess the efficacy of security control implementation (e.g., a penetration test); (iii) claims about the effectiveness and cost-effectiveness of 5 assurance techniques used to assess the competency of individuals to use the assurance techniques that assess security controls (e.g., a multiple-choice examination); (iv) demonstration of the need for standardisation in a subset of these assurance techniques, based on an analysis of the real-world readiness and competence of the industry to deliver them; (v) the establishment of five novel principles (“PASIV”) to guide the safe use of assurance techniques within operationally sensitive areas of ICS environments, and the determination of potential assurance technique use across three phases of the system development life cycle; and (vi) the mapping of assurance techniques to security control families within ISO/IEC 27001:2013 (and its ICS-specific counterpart, ISO/IEC TR 27019:2013) to identify potential sources of audit evidence generation about security control efficacy.

Performance and redundancy requirements imposed on state-of-the-art unmmaned combat aerial vehicles often lead to over-actuated systems with a mix of conventional and novel moment generators. Consequently, control allocation schemes have become a crucial part of the flight control architecture and their design is now a growing problem. This thesis presents a four control allocation scheme designed to meet multiple objectives and resolve objective conflicts by finding the ‘Pareto’ optimal solution, namely; Weighted Control Allocation, Minimax Control Allocation, Canonical Control Allocation and Classical. This is defined as a solution to the multi-objective optimisation problem which is non-dominated for all objectives. The scheme is applied to a six degrees of freedom nonlinear simulation of an aircraft equipped with conventional control surfaces as well as fluidic thrust vectoring and circulation control. The results indicate a perfect allocation of the total control demand onto the actuator suite.