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In industries where harsh environments and stringent safety requirements are prevalent, the widespread use of applications has made it essential to focus on fault detection and diagnosis (FDD) in hydraulic actuators. To achieve this, model-based FDD techniques are utilized, which employ estimation tools like observers and filters. However, for many applications, particularly in fluid power systems, observability, and parameter uncertainty pose constraints to extracting information and estimating parameters. To address these issues, an efficient form of interactive multiple model (IMM), called updated IMM (UIMM), is applied to an electro-hydraulic actuator (EHA) to detect and isolate persisting friction and leakage faults. UIMM method progresses through a series of models that correspond to the fault condition's progression instead of considering all models at once (as is done in IMM). This reduces the number of models running simultaneously, providing two significant benefits: enhanced computational efficiency and avoidance of the combinatorial explosion. The smooth variable structure filter with variable boundary layer (SVSF-VBL) is used for state and parameter estimation in conjunction with UIMM. SVSF-VBL is a reliable suboptimal estimation method that performs better than the Kalman filter regarding uncertainties related to the system and modeling. The performance of the UIMM method is validated by the simulation of fault conditions for a typical EHA. A fault tolerable control system (FTCS) has been designed to demonstrate the use of the proposed FDD strategy for fault management in a closed-loop system. [ABSTRACT FROM AUTHOR]

This paper discusses the application of four nonlinear estimation techniques on two benchmark target tracking problems. The first problem is a generic air traffic control (ATC) scenario, which involves nonlinear system equations with linear measurements. The second study is a classical ground surveillance problem, where a moving airborne platform with a sensor is used to track a moving target. The tracking scenario is set in two dimensions, with the measurement providing nonlinear bearing-only observa-tions. These two target tracking problems provide a good bench-mark for comparing the following nonlinear estimation techniques: the common extended and unscented Kalman filters (EKF/UKF), the particle filter (PF), and the relatively new smooth variable structure filter (SVSF). The results of applying the SVSF on the two target tracking problems demonstrate its sta-bility and robustness. Both of these attributes make use of the SVSF advantageous over other popular methods. The filters per-formances are quantified in terms of robustness, resilience to poor initial conditions and measurement outliers, and tracking accu-racy and computational complexity. The purpose of this paper is to demonstrate the effectiveness of applying the SVSF on nonlin-ear target tracking problems, which in the past have typically been solved by Kalman or particle filters. [ABSTRACT FROM AUTHOR]

This article presents the development of a multiple inner-loop control strategy for improving the performance of hydrostatic actuation systems. In these actuators, the presence of nonlinearities associated with pump/motor static friction and backlash, pressure drop in the piping system, and nonlinear friction at the load have a significant effect on the performance and positional accuracy of the system. The effect of nonlinear friction at the pump/motor interface has been overcome by the use of a high gain pump-speed inner-loop control strategy. In this article, the concept of inner-loop control will be extended to target other specific sources of performance degradation. Velocity feedback will be incorporated in this manner to decrease the effects of pump backlash and nonlinear friction at the load. Simulation results supported by theoretical analysis indicate that a considerable improvement in performance can be achieved by the implementation of this control strategy. [ABSTRACT FROM AUTHOR]

A method that is often used for parameter estimation is the extended Kalman filter (EKF). EKF is a model-based strategy that implicitly considers the effect of modeling uncertainties. This implicit consideration often leads to the tuning of the filter by trial and error. When formulated for parameter estimation, the "tuned" EKF becomes sensitive to uncertainties in its internal model. The EKF's robustness can be improved by combining it with the recently proposed variable structure filter (VSF) concept. In a combined form, the modeling uncertainties no longer affect stability, but impact the performance and the quality of the estimation process. Furthermore, the VSF concept provides a secondary set of indicators of performance that is in addition to the estimation error and that pertains to the range of parametric uncertainties. As such, the robustness of the combined method and its multiple indicators of performance allow the use of intelligent adaptation for improving the performance of the estimation process. For real-time applications, online neural network adaptation may be used to improve the performance by progressively reducing specific modeling uncertainties in the system. In this paper, a new parameter estimation method that uses concepts associated with the EKF, the VSF, and neural network adaptation is introduced. The performance of this method is considered and discussed for applications that involve parameter estimation such as fault detection. [ABSTRACT FROM AUTHOR]

This manuscript pertains to the application of an inner-loop control strategy to electromechanical flight surface actuation systems. Modular electromechanical actuators (EMAs) are increasingly used in lieu of centralized hydraulics for the control of flight surfaces in the aerospace sector. The presence of what is termed as a dead zone in these actuators significantly affects the maneuverability, stability, and the flight profiles of aircrafts that use this actuation concept. The hypothesis of our research is that flight surface actuation systems may be desensitized to the effects of dead zone by using a control strategy with multiple inner loops. The proposed strategy involves (a) high-gain inner-loop velocity control of the driving motor and (b) inner-loop compensation for the differential velocity between the motor versus the aileron. The above hypothesis is confirmed by theoretical and simulated analyses using the model of an EMA flight surface actuator. Our results indicate that for small input signals, this strategy is very effective and that it can (a) considerably increase the bandwidth and the crossover frequency of the system and (b) considerably improve the time response of the system. Further to this analysis, this manuscript presents guidelines for the design of EMA systems. [ABSTRACT FROM AUTHOR]

The article presents a study investigating the ability of the hydrostatic actuation system in moving heavy loads. As part of the research, the design of a high-precision hydrostatic actuation system referred to as the ElectroHydraulic Actuator is presented. The result showed that hydrostatic actuation systems are able to manipulate heavy loads with submicron precision and a large stroke, after moving a large load of 20 Kg with a precision of 100 nm and a stroke of 12 cm.