Gas bearings are popular for their high speed capabilities, low friction and clean operation, but suffer from poor damping, which poses challenges for safe operation in presence of disturbances. Enhanced damping can be achieved through active lubrication techniques using feedback control laws. Such control design requires models with low complexity, able to describe the dominant dynamics from actuator input to sensor output over the relevant range of operation. The mathematical models based on first principles are not easy to obtain, and in many cases, they cannot be directly used for control design due to their complexity and parameter uncertainties. As an alternative, this paper presents an experimental technique for "in situ" identification of low complexity models of the entire rotor-bearingactuator system. Using grey-box identification techniques, the approach is shown to be easily applied to industrial rotating machinery with gas bearings and to allow for subsequent control design. The paper shows how piezoelectric actuators in a gas bearing are efficiently used to perturb the gas film for identification over relevant ranges of rotational speed and gas injection pressure. Parameter-varying linear models are found to capture the dominant dynamics of the system over the range of operation. Based on the identified models, decentralised proportional control is designed and is shown to obtain the required damping in theory as well as in a laboratory test rig.

a b s t r a c tJournal bearings can be lubricated through controllable injectors using pressurised fluids, whose viscosity highly determines the dynamic responses of the rotating machine. The use of fluids with low viscosity is attracting a growing interest due to the reduced friction forces and consequent losses when the machine is in operation. However low viscosity also entails poor damping properties, which may lead to degraded performance or even instability when the rotating machine operates at or near one of the modal frequencies. This issue can be properly addressed by employing active feedback control systems to regulate the injection pressure of the fluid. Due to the strong dependencies of system performance on system parameters, the sought controller should be robust over a large range of operational conditions. This paper addresses the damping enhancement of controllable gas bearings through robust control approaches. Through an extensive experimental campaign the paper evaluates two robust controllers, a linear parametervarying (LPV) controller and ∞  controller, on their capability to guarantee stability and performance of a gas bearing across the large operational envelopes in rotational speed and injection pressure. The control systems are designed applying state-of-the-art methods in the respective areas. The experimental results clearly demonstrate the feasibility of enhancing the damping properties of a gas bearing by means of robust control methods.

Gas bearings have inherent dynamics that gives rise to low damping and potential instability at certain rotational speeds. Required damping and stabilization properties can be achieved by active flow control if bearing parameters are known. This paper deals with identification of parameters in a dynamic model of an active gas bearing and subsequent control loop design. A grey box model is determined based on experiments where piezo actuated valves are used to perturb the journal and hence excite the rotor-bearing system. Such modelling from actuator to output is shown to efficiently support controller design, in contrast to impact models that focus on resonance dynamics. The identified model is able to accurately reproduce the lateral dynamics of the rotor-bearing system in a desired operating range, in this case around the first two natural frequencies. The identified models are validated and used to design a model-based controller capable of improving the damping of the gas bearing. Experimental impact responses show an increase in damping by a factor nine for the investigated conditions.

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This paper treats L 1 adaptive hovering control of an unmanned surface vehicle in a station-keeping mode where a region of zero control authority and under-actuation are main challenges. Low-speed and reversing dynamics are identified from full scale sea trials, and parameter uncertainty is estimated. With significant parameter variation, an L 1 adaptive controller is employed for heading control. The L 1 family of controllers allows for several topologies and an architecture is suggested that suits heading control of a vessel, the requirements of which differ from that of previous L 1 literature. The control design is tackled directly in discrete time to allow a fast embedded implementation in the vehicle. Analysis of robustness, tracking performance and wave disturbance response are detailed in the paper.