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Flexible structure experiments at JPL and WPAFB - H(infinity) controller designs
Control system experiments are described that were carried out on flexible structure facilities at the Jet Propulsion Laboratory (JPL) and the Wright-Patterson Air Force Base (WPAFB). The feedback controllers were designed using the technique of weighted gap optimization to increase structural damping and achieve robust control.
Robustness of controllers designed using Galerkin type approximations
One of the difficulties in designing controllers for infinite-dimensional systems arises from attempting to calculate a state for the system. It is shown that Galerkin type approximations can be used to design controllers which will perform as designed when implemented on the original infinite-dimensional system. No assumptions, other than those typically employed in numerical analysis, are made on the approximating scheme.
Integrated flight/propulsion control design for a STOVL aircraft using H-infinity control design techniques
Results are presented from an application of H(infinity) control design methodology to a centralized integrated flight/propulsion control (IFPC) system design for a supersonic short take-off and vertical landing (STOVL) fighter aircraft in transition flight. The emphasis is on formulating the H(infinity) control design problem such that the resulting controller provides robustness to modeling uncertainties and model parameter variations with flight condition. Experience gained from a preliminary H(infinity)=based IFPC design study performed earlier is used as the base to formulate the robust H(infinity) control design problem and improve the previous design. Detailed evaluation results are presented for a reduced-order controller obtained from the improved H(infinity) control design showing that the control design meets the specified nominal performance objectives as well as provides stability robustness for variations in plant system dynamics with chnages in aircraft trim speed within the transition flight envelope.
Integrated flight/propulsion control design for a STOVL aircraft using H-infinity control design techniques
Results are presented from an application of H-infinity control design methodology to a centralized integrated flight propulsion control (IFPC) system design for a supersonic Short Takeoff and Vertical Landing (STOVL) fighter aircraft in transition flight. The emphasis is on formulating the H-infinity control design problem such that the resulting controller provides robustness to modeling uncertainties and model parameter variations with flight condition. Experience gained from a preliminary H-infinity based IFPC design study performed earlier is used as the basis to formulate the robust H-infinity control design problem and improve upon the previous design. Detailed evaluation results are presented for a reduced order controller obtained from the improved H-infinity control design showing that the control design meets the specified nominal performance objectives as well as provides stability robustness for variations in plant system dynamics with changes in aircraft trim speed within the transition flight envelope. A controller scheduling technique which accounts for changes in plant control effectiveness with variation in trim conditions is developed and off design model performance results are presented.
Robust integrated flight/propulsion control design for a STOVL aircraft using H-infinity control design techniques
Results are presented from an application of H-infinity control design methodology to a centralized integrated flight/propulsion control (IFPC) system design for a supersonic STOVL fighter aircraft in transition flight. The emphasis is on formulating the H-infinity optimal control synthesis problem such that the critical requirements for the flight and propulsion systems are adequately reflected within the linear, centralized control problem formulation and the resulting controller provides robustness to modeling uncertainties and model parameter variations with flight condition. Detailed evaluation results are presented for a reduced order controller obtained from the improved H-infinity control design showing that the control design meets the specified nominal performance objective as well as provides stability robustness for variations in plant system dynamics with changes in aircraft trim speed within the transition flight envelope.
Candidate control design metrics for an agile fighter
Success in the fighter combat environment of the future will certainly demand increasing capability from aircraft technology. These advanced capabilities in the form of superagility and supermaneuverability will require special design techniques which translate advanced air combat maneuvering requirements into design criteria. Control design metrics can provide some of these techniques for the control designer. Thus study presents an overview of control design metrics and investigates metrics for advanced fighter agility. The objectives of various metric users, such as airframe designers and pilots, are differentiated from the objectives of the control designer. Using an advanced fighter model, metric values are documented over a portion of the flight envelope through piloted simulation. These metric values provide a baseline against which future control system improvements can be compared and against which a control design methodology can be developed. Agility is measured for axial, pitch, and roll axes. Axial metrics highlight acceleration and deceleration capabilities under different flight loads and include specific excess power measurements to characterize energy meneuverability. Pitch metrics cover both body-axis and wind-axis pitch rates and accelerations. Included in pitch metrics are nose pointing metrics which highlight displacement capability between the nose and the velocity vector. Roll metrics (or torsion metrics) focus on rotational capability about the wind axis.
A Robust Control Design Framework for Substructure Models
A framework for designing control systems directly from substructure models and uncertainties is proposed. The technique is based on combining a set of substructure robust control problems by an interface stiffness matrix which appears as a constant gain feedback. Variations of uncertainties in the interface stiffness are treated as a parametric uncertainty. It is shown that multivariable robust control can be applied to generate centralized or decentralized controllers that guarantee performance with respect to uncertainties in the interface stiffness, reduced component modes and external disturbances. The technique is particularly suited for large, complex, and weakly coupled flexible structures.
Pattern Recognition Control Design
Spacecraft control algorithms must know the expected spacecraft response to any command to the available control effectors, such as reaction thrusters or torque devices. Spacecraft control system design approaches have traditionally relied on the estimated vehicle mass properties to determine the desired force and moment, as well as knowledge of the effector performance to efficiently control the spacecraft. A pattern recognition approach can be used to investigate the relationship between the control effector commands and the spacecraft responses. Instead of supplying the approximated vehicle properties and the effector performance characteristics, a database of information relating the effector commands and the desired vehicle response can be used for closed-loop control. A Monte Carlo simulation data set of the spacecraft dynamic response to effector commands can be analyzed to establish the influence a command has on the behavior of the spacecraft. A tool developed at NASA Johnson Space Center (Ref. 1) to analyze flight dynamics Monte Carlo data sets through pattern recognition methods can be used to perform this analysis. Once a comprehensive data set relating spacecraft responses with commands is established, it can be used in place of traditional control laws and gains set. This pattern recognition approach can be compared with traditional control algorithms to determine the potential benefits and uses.
Pattern Recognition Control Design
Spacecraft control algorithms must know the expected vehicle response to any command to the available control effectors, such as reaction thrusters or torque devices. Spacecraft control system design approaches have traditionally relied on the estimated vehicle mass properties to determine the desired force and moment, as well as knowledge of the effector performance to efficiently control the spacecraft. A pattern recognition approach was used to investigate the relationship between the control effector commands and spacecraft responses. Instead of supplying the approximated vehicle properties and the thruster performance characteristics, a database of information relating the thruster ring commands and the desired vehicle response was used for closed-loop control. A Monte Carlo simulation data set of the spacecraft dynamic response to effector commands was analyzed to establish the influence a command has on the behavior of the spacecraft. A tool developed at NASA Johnson Space Center to analyze flight dynamics Monte Carlo data sets through pattern recognition methods was used to perform this analysis. Once a comprehensive data set relating spacecraft responses with commands was established, it was used in place of traditional control methods and gains set. This pattern recognition approach was compared with traditional control algorithms to determine the potential benefits and uses.
Brain-Computer Interfaces for 1-D and 2-D Cursor Control: Designs Using Volitional Control of the EEG Spectrum or Steady-State Visual Evoked Potentials
We have developed and tested two EEG-based brain-computer interfaces (BCI) for users to control a cursor on a computer display. Our system uses an adaptive algorithm, based on kernel partial least squares classification (KPLS), to associate patterns in multichannel EEG frequency spectra with cursor controls. Our first BCI, Target Practice, is a system for one-dimensional device control, in which participants use biofeedback to learn voluntary control of their EEG spectra. Target Practice uses a KF LS classifier to map power spectra of 30-electrode EEG signals to rightward or leftward position of a moving cursor on a computer display. Three subjects learned to control motion of a cursor on a video display in multiple blocks of 60 trials over periods of up to six weeks. The best subject s average skill in correct selection of the cursor direction grew from 58% to 88% after 13 training sessions. Target Practice also implements online control of two artifact sources: a) removal of ocular artifact by linear subtraction of wavelet-smoothed vertical and horizontal EOG signals, b) control of muscle artifact by inhibition of BCI training during periods of relatively high power in the 40-64 Hz band. The second BCI, Think Pointer, is a system for two-dimensional cursor control. Steady-state visual evoked potentials (SSVEP) are triggered by four flickering checkerboard stimuli located in narrow strips at each edge of the display. The user attends to one of the four beacons to initiate motion in the desired direction. The SSVEP signals are recorded from eight electrodes located over the occipital region. A KPLS classifier is individually calibrated to map multichannel frequency bands of the SSVEP signals to right-left or up-down motion of a cursor on a computer display. The display stops moving when the user attends to a central fixation point. As for Target Practice, Think Pointer also implements wavelet-based online removal of ocular artifact; however, in Think Pointer muscle artifact is controlled via adaptive normalization of the SSVEP. Training of the classifier requires about three minutes. We have tested our system in real-time operation in three human subjects. Across subjects and sessions, control accuracy ranged from 80% to 100% correct with lags of 1-5 seconds for movement initiation and turning.
Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model
In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to as the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly; however, a large adaptive gain can lead to high-frequency oscillations which can adversely affect the robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient robustness. A damping term (v) is added in the modification to increase damping as needed. Simulations were conducted on a damaged F-18 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) with both the standard baseline dynamic inversion controller and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model.
Robust control design for aerospace applications
Time-domain control design for stability robustness of linear systems with structured uncertainty is addressed. Upper bounds on the linear perturbation of an asymptotically stable linear system are obtained, making it possible to maintain stability by using the structural information of the uncertainty. A quantitative measure called the stability robustness index is introduced and used to design controllers for robust stability. The proposed state feedback control design algorithm can be used, for a given set of perturbations, to select the range of control effort for which the system is stability-robust. Conversely it can be used, for a given control effort, to determine the size of the tolerable perturbation. The algorithm is illustrated with examples from aircraft control and large-space-structure control problems.
Designing for Damage: Robust Flight Control Design using Sliding Mode Techniques
A brief review of sliding model control is undertaken, with particular emphasis upon the effects of neglected parasitic dynamics. Sliding model control design is interpreted in the frequency domain. The inclusion of asymptotic observers and control 'hedging' is shown to reduce the effects of neglected parasitic dynamics. An investigation into the application of observer-based sliding mode control to the robust longitudinal control of a highly unstable is described. The sliding mode controller is shown to exhibit stability and performance robustness superior to that of a classical loop-shaped design when significant changes in vehicle and actuator dynamics are employed to model airframe damage.
An application of the IMC software to controller design for the JPL LSCL Experiment Facility
A software package which Integrates Model reduction and Controller design (The IMC software) is applied to design controllers for the JPL Large Spacecraft Control Laboratory Experiment Facility. Modal Cost Analysis is used for the model reduction, and various Output Covariance Constraints are guaranteed by the controller design. The main motivation is to find the controller with the 'best' performance with respect to output variances. Indeed it is shown that by iterating on the reduced order design model, the controller designed does have better performance than that obtained with the first model reduction.
A Comparison of Multivariable Control Design Techniques for a Turbofan Engine Control
This paper compares two previously published design procedures for two different multivariable control design techniques for application to a linear engine model of a jet engine. The two multivariable control design techniques compared were the Linear Quadratic Gaussian with Loop Transfer Recovery (LQG/LTR) and the H-Infinity synthesis. The two control design techniques were used with specific previously published design procedures to synthesize controls which would provide equivalent closed loop frequency response for the primary control loops while assuring adequate loop decoupling. The resulting controllers were then reduced in order to minimize the programming and data storage requirements for a typical implementation. The reduced order linear controllers designed by each method were combined with the linear model of an advanced turbofan engine and the system performance was evaluated for the continuous linear system. Included in the performance analysis are the resulting frequency and transient responses as well as actuator usage and rate capability for each design method. The controls were also analyzed for robustness with respect to structured uncertainties in the unmodeled system dynamics. The two controls were then compared for performance capability and hardware implementation issues.
Distributed Conditions for Small-signal Stability of Power Grids and Local Control Design
Operating modern power grids with stability guarantees is markedly important. Typical methods for analyzing and certifying power grid stability are largely centralized relying on the ability of the system operator to gather network-wide information and accurately compute the system's eigenvalues. These methods are oftentimes not privacy-preserving and computationally burdensome. They are therefore, not well-suited to modern power grids where small-signal stability has to be evaluated timely, efficiently and in a privacy-preserving fashion. Herein, we introduce a distributed methodology for certifying small-signal stability of power grids and designing the local controllers. First, we analytically derive distributed conditions for network-wide stability that bus agents can inspect using local information. By leveraging these conditions, we then introduce a distributed control design algorithm (DCDA) that can guide the local control design so that stability of the interconnected system is guaranteed. The agents that adopt the proposed distributed algorithm are responsible for tuning their local controllers, producing their local control commands and ensuring that their local stability condition is met. The system operator is only responsible for verifying network-wide stability upon receiving affirmative responses from all agents and, announcing, that the overall system is stable. The proposed DCDA algorithm is numerically validated via simulations using the IEEE 39-bus system.
Two Reconfigurable Flight-Control Design Methods: Robust Servomechanism and Control Allocation
Two methods for control system reconfiguration have been investigated. The first method is a robust servomechanism control approach (optimal tracking problem) that is a generalization of the classical proportional-plus-integral control to multiple input-multiple output systems. The second method is a control-allocation approach based on a quadratic programming formulation. A globally convergent fixed-point iteration algorithm has been developed to make onboard implementation of this method feasible. These methods have been applied to reconfigurable entry flight control design for the X-33 vehicle. Examples presented demonstrate simultaneous tracking of angle-of-attack and roll angle commands during failures of the fight body flap actuator. Although simulations demonstrate success of the first method in most cases, the control-allocation method appears to provide uniformly better performance in all cases.