145 research outputs found
Development of U-model enhansed nonlinear systems
Nonlinear control system design has been widely recognised as a challenging issue where the key objective is to develop a general model prototype with conciseness, flexibility and manipulability, so that the designed control system can best match the required performance or specifications. As a generic systematic approach, U-model concept appeared in Prof. Quanmin Zhu’s Doctoral thesis, and U-model approach was firstly published in the journal paper titled with ‘U-model based pole placement for nonlinear plants’ in 2002.The U-model polynomial prototype precisely describes a wide range of smooth nonlinear polynomial models, defined as a controller output u(t-1) based time-varying polynomial models converted from the original nonlinear model. Within this equivalent U-model expression, the first study of U-model based pole placement controller design for nonlinear plants is a simple mapping exercise from ordinary linear and nonlinear difference equations to time-varying polynomials in terms of the plant input u(t-1). The U-model framework realised the concise and applicable design for nonlinear control system by using such linear polynomial control system design approaches.Since the first publication, the U-model methodology has progressed and evolved over the course of a decade. By using the U-model technique, researchers have proposed many different linear algorithms for the design of control systems for the nonlinear polynomial model including; adaptive control, internal control, sliding mode control, predictive control and neural network control. However, limited research has been concerned with the design and analysis of robust stability and performance of U-model based control systems.This project firstly proposes a suitable method to analyse the robust stability of the developed U-model based pole placement control systems against uncertainty. The parameter variation is bounded, thus the robust stability margin of the closed loop system can be determined by using LMI (Linear Matrix Inequality) based robust stability analysis procedure. U-block model is defined as an input output linear closed loop model with pole assignor converted from the U-model based control system. With the bridge of U-model approach, it connects the linear state space design approach with the nonlinear polynomial model. Therefore, LMI based linear robust controller design approaches are able to design enhanced robust control system within the U-block model structure.With such development, the first stage U-model methodology provides concise and flexible solutions for complex problems, where linear controller design methodologies are directly applied to nonlinear polynomial plant-based control system design. The next milestone work expands the U-model technique into state space control systems to establish the new framework, defined as the U-state space model, providing a generic prototype for the simplification of nonlinear state space design approaches.The U-state space model is first described as a controller output u(t-1) based time-varying state equations, which is equivalent to the original linear/nonlinear state space models after conversion. Then, a basic idea of corresponding U-state feedback control system design method is proposed based on the U-model principle. The linear state space feedback control design approach is employed to nonlinear plants described in state space realisation under U-state space structure. The desired state vectors defined as xd(t), are determined by closed loop performance (such as pole placement) or designer specifications (such as LQR). Then the desired state vectors substitute the desired state vectors into original state space equations (regarded as next time state variable xd(t) = x(t) ). Therefore, the controller output u(t-1) can be obtained from one of the roots of a root-solving iterative algorithm.A quad-rotor rotorcraft dynamic model and inverted pendulum system are introduced to verify the U-state space control system design approach for MIMO/SIMO system. The linear design approach is used to determine the closed loop state equation, then the controller output can be obtained from root solver. Numerical examples and case studies are employed in this study to demonstrate the effectiveness of the proposed methods
Fault-Tolerant Flight Control Using One Aerodynamic Control Surface
University of Minnesota Ph.D. dissertation. June 2018. Major: Aerospace Engineering and Mechanics. Advisor: Peter Seiler. 1 computer file (PDF); xiii, 291 pages.Small unmanned aircraft systems (UAS) have recently found increasing civilian and commercial applications. On-board fault management is one of several technical challenges facing their widespread use. The aerodynamic control surfaces of a fixed-wing UAS perform the safety-critical functions of stabilizing and controlling the aircraft. Failures in one or more of these surfaces, or the actuators controlling them, may be managed by repurposing the other control surfaces and/or propulsive devices. A natural question arises in this context: What is the minimum number of control surfaces required to adequately control a handicapped aircraft? The answer, in general, depends on the control surface layout of the aircraft under consideration. For some aircraft, however, the answer is one. If the UAS is equipped with only two control surfaces, such as the one considered in this thesis, then this limiting case is reached with a single control surface failure. This thesis demonstrates, via multiple flight tests, the autonomous landing of a UAS using only one aerodynamic control surface and the throttle. In seeking to arrive at these demonstrations, this thesis makes advances in the areas of model-based fault diagnosis and fault-tolerant control. Specifically, a new convex method is developed for synthesizing robust output estimators for continuous-time, uncertain, gridded, linear parameter-varying systems. This method is subsequently used to design the fault diagnosis algorithm. The detection time requirement of this algorithm is established using concepts from loss-of-control. The fault-tolerant controller is designed to operate the single control surface for lateral control and the throttle for total energy control. The fault diagnosis algorithm and the fault-tolerant controller are both designed using a model of the aircraft. This model is first developed using physics-based first-principles and then updated using system identification experiments. Since this aircraft does not have a rudder, the identification of the lateral-directional dynamics requires some novelty
L1 adaptive control flight testing and extension to nonlinear reference systems with unmatched uncertainty
Building upon prior research efforts deploying L1 adaptive control in remotely piloted aerospace applications, this dissertation presents the progression of in-flight evaluation of L1 adaptive control to manned flight testing on Calspan’s variable stability Learjet and to an augmentation of an autonomous trajectory planner on a multirotor aircraft. These efforts ultimately led to the development of a new L1 adaptive controller for a class of control-affine nonlinear reference systems subject to time-varying, state-dependent matched and unmatched uncertainties.
The L1 adaptive controller for the Learjet flight tests was designed as stability augmentation system, modifying the pilot's stick-to-surface commands, and was evaluated in a series of flying and handling qualities tests. The results of the Learjet flight tests demonstrated the ability of the L1 adaptive controller to recover desired flying qualities and safe, consistent handling qualities in the presence of off-nominal dynamics, some of which had severe flying qualities deficiencies and aggressive tendencies toward adverse pilot-aircraft interaction, and simulated aircraft failures. A modification of the Learjet control law was implemented, with a nonlinear reference system and estimation of both matched and unmatched uncertainties, for a multirotor aircraft as an augmentation of a geometric trajectory-tracking baseline controller, tracking a reference trajectory generated by a model predictive path integral trajectory planner. Simulation results demonstrated that, with the L1 augmentation, the vehicle was able to navigate a complex environment in the presence of uncertainty and external disturbances.
The new L1 adaptive controller provides a theoretical foundation for the L1 augmentation in the multirotor application, and may be applicable to tilt-rotor, tilt-wing, and split-propulsion vertical takeoff and landing aircraft proliferating in the urban air mobility sector. The theory is based on incremental stability for robust trajectory tracking and uses a piecewise-constant adaptive law. It proposes a feedforward compensator (in the form of an embedded linear parameter-varying system), synthesized for the variational dynamics of the system using linear matrix inequality-based robust control methods to minimize the peak-to-peak gain from unmatched uncertainty to the system state. A realization of the feedforward compensator in the ambient space can be directly applied to the nonlinear system. Analysis of the closed-loop system provides an incremental stability guarantee and bounds the transient and steady-state trajectory-tracking error
Topics in Automotive Rollover Prevention: Robust and Adaptive Switching Strategies for Estimation and Control
The main focus in this thesis is the analysis of alternative approaches for estimation and control of automotive vehicles based on sound theoretical principles. Of particular importance is the problem rollover prevention, which is an important problem plaguing vehicles
with a high center of gravity (CG). Vehicle rollover is, statistically, the most dangerous accident type, and it is difficult to prevent it due to the time varying nature of the problem. Therefore, a major objective of the thesis is to develop the necessary theoretical and practical
tools for the estimation and control of rollover based on robust and adaptive techniques that are stable with respect to parameter variations.
Given this background, we first consider an implementation of the multiple model switching and tuning (MMST) algorithm for estimating the unknown parameters of automotive vehicles
relevant to the roll and the lateral dynamics including the position of CG. This results in high performance estimation of the CG as well as other time varying parameters, which can be used in tuning of the active safety controllers in real time. We then look into automotive rollover prevention control based on a robust stable control design methodology. As part of this we introduce a dynamic version of the load transfer ratio (LTR) as a rollover detection
criterion and then design robust controllers that take into account uncertainty in the CG position. As the next step we refine the controllers by integrating them with the multiple
model switched CG position estimation algorithm. This results in adaptive controllers with higher performance than the robust counterparts.
In the second half of the thesis we analyze extensions of certain theoretical results with important implications for switched systems. First we obtain a non-Lyapunov stability result for a certain class of linear discrete time switched systems. Based on this result, we suggest switched controller synthesis procedures for two roll dynamics enhancement control applications. One control design approach is related to modifying the dynamical response
characteristics of the automotive vehicle while guaranteeing the switching stability under parametric variations. The other control synthesis method aims to obtain transient free reference tracking of vehicle roll dynamics subject to parametric switching.
In a later discussion, we consider a particular decentralized control design procedure based on vector
Lyapunov functions for simultaneous, and structurally robust model reference tracking of both the lateral and the roll dynamics of automotive vehicles. We show that this controller design approach guarantees the closed loop stability subject to certain types of structural
uncertainty.
Finally, assuming a purely theoretical pitch, and motivated by the problems considered during the course of the thesis, we give new stability results on common Lyapunov solution
(CLS) existence for two classes of switching linear systems; one is concerned with switching pair of systems in companion form and with interval uncertainty, and the other is concerned with switching pair of companion matrices with general inertia. For both problems we give easily verifiable spectral conditions that are sufficient for the CLS existence. For proving the second result we also obtain a certain generalization of the classical Kalman-Yacubovic-Popov lemma for matrices with general inertia
A Condition Based Maintenance Approach to Forecasting B-1 Aircraft Parts
United States Air Force (USAF) aircraft parts forecasting techniques have remained archaic despite new advancements in data analysis. This approach resulted in a 57% accuracy rate in fiscal year 2016 for USAF managed items. Those errors combine for 12.6 million worth of parts in those categories alone for the B-1 aircraft
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A longitudinal flight control law to accommodate sensor loss in the RECONFIGURE benchmark
The feedback gains in state-of-the-art flight control laws for commercial aircraft are scheduled as a function of values such as airspeed, mass, and centre of gravity (CoG). If measurements or estimates of these are lost due to multiple simultaneous sensor failures, the pilot must revert to an alternative control law, or, in the ultimate case, directly command control surface positions. This work develops a robust backup load-factor tracking control law, that does not depend on these parameters, based on application of theory from robust MPC and optimal control. Firstly, the methods are applied with loss only of airdata, and subsequently also with loss of mass and CoG estimates. Local linear analysis indicates satisfactory performance over a wide range of operating points. To keep the aircraft within an acceptable operating region, an outer protection loop is implemented using an override approach, based on ground speed, a model of the trim angle of attack and variation of load factor with respect to angle of attack, and bounds on the wind speed. Finally, the resulting control laws are demonstrated on the nonlinear RECONFIGURE benchmark, which is derived from an Airbus high fidelity, industrially-validated simulator.European Union Seventh Framework Programme FP7/2007- 2013 (Grant ID: 314 544, project “RECONFIGURE”
Optimal fault-tolerant flight control for aircraft with actuation impairments
Current trends towards greater complexity and automation are leaving modern
technological systems increasingly vulnerable to faults. Without proper action, a
minor error may lead to devastating consequences. In flight control, where the
controllability and dynamic stability of the aircraft primarily rely on the control
surfaces and engine thrust, faults in these effectors result in a higher extent of risk for
these aspects. Moreover, the operation of automatic flight control would be suddenly
disturbed. To address this problem, different methodologies of designing optimal
flight controllers are presented in this thesis. For multiple-input multiple-output
(MIMO) systems, the feedback optimal control is a prominent technique that solves
a multi-objective cost function, which includes, for instance, tracking requirements
and control energy minimisation.
The first proposed method is based on a linear quadratic regulator (LQR) control
law augmented with a fault-compensation scheme. This fault-tolerant system handles
the situation in an adaptive way by solving the optimisation cost function and
considering fault information, while assuming an effective fault detection system is
available. The developed scheme was tested in a six-degrees-of-freedom nonlinear
environment to validate the linear-based controller. Results showed that this fault
tolerant control (FTC) strategy managed to handle high magnitudes of the actuator’s
loss of effciency faults. Although the rise time of aircraft response became slower,
overshoot and settling errors were minimised, and the stability of the aircraft was
maintained.
Another FTC approach has been developed utilising the features of controller
robustness against the system parametric uncertainties, without the need for reconfiguration
or adaptation. Two types of control laws were established under this scheme,
the
H∞
and µ-synthesis controllers. Both were tested in a nonlinear environment
for three points in the flight envelope: ascending, cruising, and descending. The
H∞
controller maintained the requirements in the intact case; while in fault, it yielded
non-robust high-frequency control surface deflections. The µ-synthesis, on the other
hand, managed to handle the constraints of the system and accommodate faults
reaching 30% loss of effciency in actuation. The final approach is based on the control allocation technique. It considers the tracking requirements and the constraints of
the actuators in the design process. To accommodate lock-in-place faults, a new
control effort redistribution scheme was proposed using the fuzzy logic technique,
assuming faults are provided by a fault detection system. The results of simulation
testing on a Boeing 747 multi-effector model showed that the system managed to
handle these faults and maintain good tracking and stability performance, with some
acceptable degradation in particular fault scenarios. The limitations of the controller
to handle a high degree of faults were also presented
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