Teaching old sensors New tricks: archetypes of intelligence

In this paper a generic intelligent sensor software architecture is described which builds upon the basic requirements of related industry standards (IEEE 1451 and SEVA BS- 7986). It incorporates specific functionalities such as real-time fault detection, drift compensation, adaptation to environmental changes and autonomous reconfiguration. The modular based structure of the intelligent sensor architecture provides enhanced flexibility in regard to the choice of specific algorithmic realizations. In this context, the particular aspects of fault detection and drift estimation are discussed. A mixed indicative/corrective fault detection approach is proposed while it is demonstrated that reversible/irreversible state dependent drift can be estimated using generic algorithms such as the EKF or on-line density estimators. Finally, a parsimonious density estimator is presented and validated through simulated and real data for use in an operating regime dependent fault detection framework

Systems reliability issues for future aircraft

The reliability of adaptive controls for future aircraft are discussed. The research, formulation, and experimentation for improved aircraft performance are considered

Iterative learning control in the commissioning of industrial presses

182 p.This thesis presents solutions to the control problems that exist nowadays in industrial presses, followed by a discussion of the most appropriate control schemes that may be used for their solution. Iterative Learning Control is subsequently analyzed, as the most promising control scheme for machine presses, due to its capability to improve the performance of a system that operates repeatedly.A novel Iterative Learning Control design is presented, which makes use of the dynamic characteristics of the system to improve the current controller performance and stability. This, results in an adaptation of the presented Iterative Learning Control design to two use cases: the single-input-single-output force control of mechanical presses and the multiple-input-multiple-output position control of hydraulic presses. While existing Iterative Learning Control approaches are also described and applied to the previously mentioned use cases, the presented novel approach has been shown to outperform the existing algorithms in terms of control performance.The proposed Iterative Learning control algorithms are validated in an experimental hydraulic test rig, in which the performance, robustness and stability of the algorithm have been demonstrated

Autonomous Flight, Fault, and Energy Management of the Flying Fish Solar-Powered Seaplane.

The Flying Fish autonomous unmanned seaplane is designed and built for persistent ocean surveillance. Solar energy harvesting and always-on autonomous control and guidance are required to achieve unattended long-term operation. This thesis describes the Flying Fish avionics and software systems that enable the system to plan, self-initiate, and autonomously execute drift-flight cycles necessary to maintain a designated watch circle subject to environmentally influenced drift. We first present the avionics and flight software architecture developed for the unique challenges of an autonomous energy-harvesting seaplane requiring the system to be: waterproof, robust over a variety of sea states, and lightweight for flight. Seaplane kinematics and dynamics are developed based on conventional aircraft and watercraft and upon empirical flight test data. These models serve as the basis for development of flight control and guidance strategies which take the form of a cyclic multi-mode guidance protocol that smoothly transitions between nested gain-scheduled proportional-derivative feedback control laws tuned for the trim conditions of each flight mode. A fault-tolerant airspeed sensing system is developed in response to elevated failure rates arising from pitot probe water ingestion in the test environment. The fault-tolerance strategy utilizes sensor characteristics and signal energy to combine redundant sensor measurements in a weighted voting strategy, handling repeated failures, sensor recovery, non-homogenous sensors, and periods of complete sensing failure. Finally, a graph-based mission planner combines models of global solar energy, local ocean-currents, and wind with flight-verified/derived aircraft models to provide an energy-aware flight planning tool. An NP-hard asymmetric multi-visit traveling salesman planning problem is posed that integrates vehicle performance and environment models using energy as the primary cost metric. A novel A* search heuristic is presented to improve search efficiency relative to uniform cost search. A series of cases studies are conducted with surface and airborne goals for various times of day and for multi-day scenarios. Energy-optimal solutions are identified except in cases where energy harvesting produces multiple comparable-cost plans via negative-cost cycles. The always-on cyclic guidance/control system, airspeed sensor fault management algorithm, and the nested-TSP heuristic for A* are all critical innovation required to solve the posed research challenges.Ph.D.Aerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91453/1/eubankrd_1.pd

\u3cem\u3eGRASP News\u3c/em\u3e: Volume 9, Number 1

The past year at the GRASP Lab has been an exciting and productive period. As always, innovation and technical advancement arising from past research has lead to unexpected questions and fertile areas for new research. New robots, new mobile platforms, new sensors and cameras, and new personnel have all contributed to the breathtaking pace of the change. Perhaps the most significant change is the trend towards multi-disciplinary projects, most notable the multi-agent project (see inside for details on this, and all the other new and on-going projects). This issue of GRASP News covers the developments for the year 1992 and the first quarter of 1993

Nature’s Optics and Our Understanding of Light

Optical phenomena visible to everyone abundantly illustrate important ideas in science and mathematics. The phenomena considered include rainbows, sparkling reflections on water, green flashes, earthlight on the moon, glories, daylight, crystals, and the squint moon. The concepts include refraction, wave interference, numerical experiments, asymptotics, Regge poles, polarisation singularities, conical intersections, and visual illusions

Advanced robust control strategies of mechatronic suspensions for cars

Two novel mechatronic suspensions for road vehicles are studied in this thesis: the Series Active Variable Geometry Suspension (SAVGS) and the Parallel Active Link Suspension (PALS). The SAVGS and the PALS complement each other in terms of the vehicle categories they serve, which range from light high-performance vehicles (the Grand Tourer) to heavy SUV vehicles, respectively, based on the sprung mass and the passive suspension stiffness. Previous work developed various control methodologies for these types of suspension. Compared to existing active suspension solutions, both the SAVGS and the PALS are capable of low-frequency chassis attitude control and high-frequency ride comfort and road holding enhancement. In order to solve the limitation of both SAVGS and PALS robustness, mu-synthesis control methodologies are first developed for SAVGS and PALS, respectively, to account for structured uncertainties arising from changes to system parameters within realistic operating ranges. Subsequently, to guarantee robustness of both low-frequency and high-frequency vehicle dynamics for PALS, the mu-synthesis scheme is combined with proportional-integral-derivative (PID) control, employing a frequency separation paradigm. Moreover, as an alternative robustness guaranteeing scheme that captures plant nonlinearities and road unevenness as uncertainties and disturbances, a novel robust model predictive control (RMPC) based methodology is proposed for the SAVGS, motivated by the promise shown by RMPC in other industrial applications. Finally, aiming to provide further performance stability and improvements, feedforward control is developed for the PALS. Nonlinear simulations with a set of ISO driving situations are performed to evaluate the efficiency and effectiveness of the proposed control methods in this thesis.Open Acces