Multiple model adaptive estimation applied to the LAMBDA URV for failure detection and identification

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Multiple model adaptive estimation (MMAE) with filter spawning is used to detect and estimate partial actuator failures on the Variable-Stability In-flight Simulator Test Aircraft (VISTA) F-16. The truth model is a full six-degree-of-freedom simulation provided by Calspan and General Dynamics. The design models are chosen as 13-state linearized models, including first order actuator models. Actuator failures are incorporated into the truth model and design model assuming a "failure to free stream". Filter spawning is used to include additional filters with partial actuator failure hypotheses into the MMAE bank. The spawned filters are based on varying degrees of partial failures (in terms of effectiveness) associated with the complete-actuator-failure hypothesis with the highest conditional probability of correctness at the current time. Thus, a blended estimate of the failure effectiveness is found using the filters' estimates based upon a no-failure hypothesis, a complete actuator failure hypothesis, and the spawned filters' partial-failure hypotheses. This yields substantial precision in effectiveness estimation, compared to what is possible without spawning additional filters, making partial failure adaptation a viable methodology in a manner heretofore unachieved.

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A gradient free function optimization technique, namely particle swarm optimization (PSO) algorithm, is utilized in parameter identification of the electrochemical model of a Lithium-Ion battery having a LiCoO2 chemistry. Battery electrochemical model parameters are subject to change under severe or abusive operating conditions resulting in, for example, Navy over-discharged battery, 24-hr over-discharged battery, and over-charged battery. It is important for a battery management system to have these parameters changes fully captured in a bank of battery models that can be used to monitor battery conditions in real time. In this work, PSO methodology has been used to identify four electrochemical model parameters that exhibit significant variations under severe operating conditions. The identified battery models were validated by comparing the model output voltage with the experimental output voltage for the stated operating conditions. These identified conditions of the battery were then used to monitor condition of the battery that can aid the battery management system (BMS) in improving overall performance. An adaptive estimation technique, namely multiple model adaptive estimation (MMAE) method, was implemented for this purpose. In this estimation algorithm, all the identified models were simulated for a battery current input profile extracted from the hybrid pulse power characterization (HPPC) cycle simulation of a hybrid electric vehicle (HEV). A partial differential algebraic equation (PDAE) observer was utilized to obtain the estimated voltage, which was used to generate the residuals. Analysis of these residuals through MMAE provided the probability of matching the current battery operating condition to that of one of the identified models. Simulation results show that the proposed model based method offered an accurate and effective fault diagnosis of the battery conditions. This type of fault diagnosis, which is based on the models capturing true physics of the battery electrochemistry, can lead to a more accurate and robust battery fault diagnosis and help BMS take appropriate steps to prevent battery operation in any of the stated severe or abusive conditions.

Flight control actuators are the primary equipment of the Automatic Flight Control System (AFCS) that is used to provide short and long term stabilization. Flight control actuators are electrohydraulic actuators that are directly connected to the flight control surface. The hydraulic flow in these actuators is controlled using an Electro-Hydraulic Servo Valve (EHSV) with reference electrical command. Each EHSV has a null bias command to hold the valve in the null position. The null bias command depends on valve hysteresis, temperature, hydraulic pressure, and reference acceleration command. The null bias command and its variation reduce the tracking performance of the flight control actuators. In this article, we proposed a neural network bias compensator to compensate for the EHSV null bias command and improve the tracking performance of the controller. The nonlinear Hammerstein-Wiener model of the actuator was estimated from the test data. Then, a neural network bias compensator was designed in addition to the lead controller. The performance of the neural network bias compensator is analyzed through a series of simulations that demonstrate the desired qualities.

Finite-horizon reliable control with randomly occurring uncertainties and nonlinearities subject to output quantization

The decentralized robust servomechanism problem (DRSP) for large flexible space structures (LFSS) under sensor and actuator failures is considered. Failure conditions are modelled by failure matrices. This permits a unified treatment of sensor and actuator failures. For colocated LFSS, stabilization, tracking of constant set points, and regulating constant disturbances can be simultaneously handled using a decentralized tuning PID output-feedback controller. Necessary and sufficient conditions for solvability of the DRSP for colocated LFSS under sensor and actuator failures are derived. Two detailed examples demonstrate the effectiveness of the controller.

The mean and covariance of a Kalman filter residual are computed for specific cases in which the Kalman filter model differs from a linear model that accurately represents the true system (the truth model). Multiple model adaptive estimation (MMAE) uses a bank of Kalman filters, each with a different internal model, and a hypothesis testing algorithm that uses the residuals from this bank of Kalman filters to estimate the true system model. At most, only one Kalman filter's model will exactly match the truth model and will produce a residual whose mean and standard deviation have already been analyzed. All of the other filters use internal models that mismodel the true system. We compute the effects of a mismodeled input matrix, output matrix, and state transition matrix on these residuals. The computed mean and covariance are compared to simulation results of flight control failures that correspond to mismodeled input matrices and output matrices.

Spherical joints, or rod-ends, are critical components employed in flight control systems to connect the actuator to the aerodynamic surface and to the airframe. As any mechanical component, rod-ends are subjected to a wide range of failure modes, which can cause catastrophic effects at the actuator level and hence at the aircraft level. Despite this criticality, they are often overlooked in studies concerning the definition of new Prognostics and Health Management systems for flight control actuators, mainly due to the lack of sensors to monitor their behavior. The definition of a physics-based model of the rod-ends is hence a required preliminary step to pursue the definition of novel Health Monitoring schemes able to detect the fault inception in these components and track their evolution in time up to failure conditions. In this paper, a model working under few simplifying assumptions is proposed, complete with a Finite-Difference Method solution for the behavior of the lubricating film. The proposed model is then applied to a pre-existing, experimentally validated model of the flight control actuators of an in-service, wide-body commercial aircraft in presence of excessive backlash. Comments on the rod-end model are presented and further work is laid out.

This thesis is concerned with the dissipative control and filtering problems of singular systems. Four classes of singular systems are considered: delay-free singular systems, singular systems with constant time-delay, uncertain singular systems with time-varying delay and sensor failures, and singular Markovian jump systems with actuator failures.
\nFor delay-free singular systems, the system augmentation approach is employed to study the dissipative control and filtering problems. First, the approach is used to solve the dissipative control problem by static output-feedback for standard state-space systems which are the special cases of singular systems. For a continuous-time standard state-space system, the closed-loop system is represented in an augmented system form. Based on the augmented system, a necessary and sufficient dissipativity condition is proposed, which decouples the Lyapunov matrix and controller matrix. To further separate the Lyapunov matrix and the system matrices, an equivalent condition is obtained by introducing some slack matrices. Then, a necessary and sufficient condition for the existence of a static output-feedback controller is proposed, and an iterative algorithm is given to solve the condition. For discrete-time singular systems, by giving an equivalent representation of the solution set, a necessary and sufficient dissipativity condition is proposed in terms of strict linear matrix inequality (LMI) which can be easily solved by standard commercial software. Then a state-feedback controller design method is given based on the augmentation system approach. The method is extended to the static output-feedback control problem and the reduced-order dissipative filtering problem.
\nFor continuous-time singular time-delay systems, the problem of state-feedback dissipative control is considered. An improved delay-dependent dissipativity condition in terms of LMIs is established by employing the delay-partitioning technique, which guarantees a singular system to be admissible and dissipative. Based on this, a delay-dependent sufficient condition for the existence of a state-feedback controller is proposed to guarantee the admissibility and dissipativity of the closed-loop system. In addition to delay-dependence, the obtained results are also dependent on the level of dissipativity. Moreover, the results obtained unify existing results on H∞ performance analysis and passivity analysis for singular systems.
\nFor discrete-time singular systems with polytopic uncertainties, time-varying delay and sensor failures, the problem of robust reliable dissipative filtering is considered. The filter is designed by the reciprocally convex approach such that the filtering error singular system is admissible and strictly (Q, S, R)-dissipative. For singular systems with time-varying delay and sensor failures, a sufficient condition of reliable dissipative analysis is obtained in terms of LMIs. Then the result is extended to the uncertain case by introducing some variables to decouple the Lyapunov matrices and the filtering error system matrices. Moreover, a desired filter for uncertain singular systems with time-varying delay and sensor failures is obtained by solving a set of LMIs.
\nFor continuous-time singular Markovian jump systems with actuator failures, the problem of reliable dissipative control is addressed. Attention is focused on the state-feedback controller design method such that the closed-loop system is admissible and strictly (Q, S, R)-dissipative. A sufficient condition is obtained in terms of strict LMIs. Moreover, the results obtained unify existing results on H∞control and passive control on singular Markovian jump systems.

Aircraft maintenance is one of the most important cost items faced by the operators of air fleets and is a major contributor to the aircraft life cycle cost. An aircraft fly-by-wire flight control system has a total of primary flight control actuators ranging from 10 to 20 depending on the aircraft type, with a failure rate of 1/1000 flight-hours; therefore, a health monitoring system for primary flight control actuators, able to recognize an actuator degradation in its early stage could greatly contribute to optimize the maintenance operations, reduce the airplane downtime and prevent missions interruptions.This note presents the initial part of an ongoing research project aimed at developing a prognostic and health management system for fly-by-wire primary flight control actuators. A key feature of the project is to develop a PHM system for these actuators suitable for the flight control actuators of legacy airplanes, which are poised to operate for still a long time, and not only for those of new aircraft. The primary flight control actuators of fly-by-wire flight control systems of existing aircraft are electrohydraulic servoactuators with a typical configuration and complement of transducers, and there is no practical possibility of introducing additional sensors. For this reason, the research activity was directed towards the study of algorithms able to identify faults only by using the already available information of the servoactuators state variables.The implemented algorithms are a combination of mathematical and neural network based ones, and the identification of degradations was performed by the analysis of the response of the servoactuators to a sequence of selected stimuli provided in preflight or postflight. The servovalve current and the feedback position are processed by dedicated algorithms in order to obtain significant indicators of the servocatuator health condition. The values of the indicators obtained during the sequence of stimuli are analyzed in combination with those obtained in the past.This is performed by the neural network part of the algorithm which allows a reliable identification of presence and of type of a degradation.The results obtained from the initial part of the research activity are interesting and encouraging. Individual degradations of the servoactuator parameters have so far been addressed and the algorithms for identifying them have been developed. All that makes up the foundations of the future research activity which will be focused on analyzing the effects of simultaneous multiple degradations and to the estimation of the remaining useful life.

This paper is concerned with the synthesis of constant output feedback law which possesses integrity against failures of actuator and sensor. For a linear time-invariant system, the redundancy of actuators and sensors is analyzed firstly. In the situation where actuators and sensors are redundant, the modes of open loop system which are outside a desired region of Complex plane (e.g. the open left complex plane) may remain controllable and observable after the failures of some actuator and sensor. For every such situation of permissible actuator or sensor failures, if a constant output feedback law can make the poles of close loop system in the desired region, then the feedback law is said to possess high integrity against actuator and sensor failures, A proper objective function is proposed in this paper. By using the parameter optimization method, the output feedback law possessing high integrity can be generated. A computer program is developed on the IBM PC. For a linear time invariant model of double effect evaporator and a model of a plane, the output feedback laws which possess integrity are obtained by the program. These examples illustrate the effectiveness of the method proposed in this paper. The method does not require that the open loop system is asymptotically stable, this is one of the main advantages of the method.

Simulation is an important tool in control system design. Real-time simulation of flight controllers for the GARTEUR designed RCAM challenge was previously conducted on the University of Toronto Institute for Aerospace Studies real-time systems simulator (RTSS). As a next step to the controller design and simulation problem, it was desired to test a controller in the flight training device (FTD), which presents a more complex and realistic aircraft model, as well as offering a different visual perspective. The FTD runs on a commercial simulation software package called FLSIM. This project consisted of transferring two controllers from the RTSS to a FLSIM module. In order to duplicate the RCAM landing approach, the trajectory generator was also transferred. All other systems, such as flight dynamics and control actuators, were modeled by FLSIM. Through this exercise, a procedure for transferring models from the RTSS to the FTD was developed. Furthermore, it was found that controllers developed in the RTSS function in the FTD environment, but require tuning to achieve optimal results due to the more complex operational environment.

The issue of fault-tolerant decentralized control is investigated for large-scale civil engineering structures. Considering the correlation of the sub-control system, the sensor failures and the actuator failures, a sufficient condition for decentralized stabilizability is proposed for the class system of discrete-time systems with delay interconnections by using the Lyapunov stability theory and the linear matrix inequality (LMI) approach. It is shown that this condition is equivalent to the feasibility problem of the linear matrix inequality. Furthermore, a decentralized state feedback control law is derived as a convex optimization problem, and the latter can be solved by using existing efficient convex optimization techniques. The obtained controller enables the closed-loop systems to be stable. Considering sensor failures and the actuator failures, the ASCE 9-story benchmark building is selected as a numerical example to evaluate the control performance of the partially independent decentralized control and overlapping decentralized control. Numerical simulation results indicate that the proposed small gain decentralized stabilization control (LMI-SGDSC) algorithm performs as well as the traditional centralized control, and the overlapping decentralized control has a greater level of reliability. The fault tolerant decentralized control (LMI-SGFTDSC) achieves satisfactory control effects.

Reliability and vehicle survivability are key factors in achieving mission success for UAV aircraft. Maximizing these qualities is a challenging goal for tactical UAV’s exposed to target defenses as well as adverse environmental conditions and to structural or control system failures during extended length missions. Under damage conditions, using any operable control effectors becomes a critical need. These effectors could include conventional control surfaces, propulsion changes for multi-engine vehicles, and mass (fuel) transfer in lateral or longitudinal axes. Also needed may be recovery situations from extreme loss of control and upset conditions requiring correction flight control commands during flight with large angle of attack and sideslip. A major control effector for these conditions is the propulsion system of the vehicle. This control method requires two or more engines on the UAV. Engine thrust changes can change the flight path and attitude of the vehicle, and can be used as either an augmentor or for primary control of the vehicle. This use of propulsion changes to stabilize and control flight path of UAV’s is possible if sufficiently fast response time can be obtained from the engines. Flight test research conducted by NASA and Boeing on both high performance tactical aircraft and transport aircraft have demonstrated excellent potential for use of Propulsion Flight Control as part of the primary control system for UAV aircraft. Control techniques, remote pilot command methods and control station displays from these flight development programs can be applied to UAV aircraft. An important consideration for UAV aircraft is flight path control during operation outside of the normal maneuver boundaries of the vehicle, possibly caused by gust upsets, severe maneuvers for threat avoidance, structural failure, or other unanticipated causes. Propulsion control offers better response at extreme angle of attack, often better than using conventional control surfaces. Another UAV design issue is control of a tailless aircraft configuration, where the usual approach is use of split ailerons or flaps to give directional forces to the vehicle. The problem with this approach is the drag generated by these split surfaces can reduce range and speed. An alternate approach for tailless UAV’s with two or more engines is to use commanded differential thrust from the left and right engines to act as the control effector for yaw stability and for crosswind landings. Propulsion control can be a significant factor in UAV normal and adverse operating conditions. Engine controller modes integrated with flight control offer the means to achieve required flight path control during varied operating conditions of the UAV.