J. W. Curtis

Robust nonlinear aircraft tracking control using synthetic jet actuators

A robust, nonlinear tracking control strategy is presented for an aircraft equipped with synthetic jet actuators (SJA). The control law is designed to be easily implementable, requiring no observers, function approximators, or adaptive laws. By exploiting minimal knowledge of the structure of the nonlinear SJA dynamic model, a matrix decomposition technique is exploited to compensate for the input-multiplicative parametric uncertainty inherent in the SJA dynamics. The control law is shown to yield global asymptotic trajectory tracking in the presence of parametric uncertainty, actuator nonlinearity, and unknown, nonlinear external disturbances. A rigorous Lyapunov-based stability analysis is utilized to prove the theoretical result, and numerical simulation results are provided to demonstrate the performance of the proposed control law.

CLF-based nonlinear control with polytopic input constraints

This paper presents a practical method for generating high-performance control laws which are guaranteed to be stabilizing in the presence of known input constraints. We address the class of smooth non-linear systems which are affine in the control with non-smooth (rectangular or polytopic) actuator constraints and a known control Lyapunov function. We present a result which uses a complete state-dependent description of the stabilizing control value set to generate, point-wise, the set of input values which contains all the (Lyapunov) stabilizing control values that simultaneously obey the input constraints. The vertex enumeration algorithm is then used to derive a complete parameterization of this set, and a nonlinear program is employed to select a high-performance control from this feasible and stabilizing control set for an illustrative example.

Saturated RISE Tracking Control of Store-Induced Limit Cycle Oscillations

This paper presents the development of a saturated robust integral of the sign of the error (RISE) feedback controller for an airfoil section undergoing store-induced limit cycle oscillations. The controller is designed to asymptotically track the airfoil section angle of attack (AoA) in the presence of structural and aerodynamic uncertainties without breaching actuator limits through a smooth saturation function. A Lyapunov-based stability analysis is used to prove global asymptotic tracking of the AoA. Simulation results demonstrate the performance of the developed controller.

Optimal estimation of multidimensional data with limited measurements

Recent results indicate how to optimally schedule transmissions of a measurement to a remote estimator when there are limited uses of the communication channel available. The resulting optimal encoder and estimation policies solve an important problem in networked control systems when bandwidth is limited. Previous results were obtained only for scalar processes, and the previous work was unable to address questions regarding informational relevance. We extend the state of-the art by treating the case where the source process and measurements are multi-dimensional. To this end, we develop a non-trivial re-working of the underlying proofs. Specifically, we develop optimal encoder policies for Gaussian and Gauss Markov measurement processes by utilizing a measure of the informational value of the source data. Explicit expressions for optimal hyper-ellipsoidal regions are derived and utilized in these encoder policies. Interestingly, it is shown in this paper that analytical expressions for the hyper-ellipsoids exist only when the states dimension is even; in odd dimensions (as in the scalar case) the solution requires a numerical look up (e.g., use of the erf function). We also have extended the previous analyses by introducing a weighting matrix in the quadratic cumulative cost function, whose purpose is to allow the system designer to designate which states are more important or relevant to total system performance.

Stabilizing a nonlinear model-based networked control system with communication constraints

In this paper, a class of nonlinear networked control systems (NCS) operating over a shared-channel are considered. For sensor networks and networks requiring information collaboration among various devices, the objective to reduce contention and use the bandwidth limited network resources more efficiently can be achieved by developing “smart” sensors. Model-based control and event-based triggering can be fused such that smart sensors determine the “value of information” for stable operation of control systems. A context-aware feedback policy can be developed for a class of nonlinear NCS based on the informational value of sensor measurements that minimizes network usage or traffic. The developed aperiodic feedback policy guarantees global asymptotic tracking of output states of an uncertain system along the desired time-varying trajectory. A direct adaptive parameter update law is formulated to estimate the uncertain system dynamics that can further reduce feedback requirements. A piecewise continuous tracking controller is developed and validated using extensive simulation results for nonlinear scalar and coupled MIMO systems.

Adaptive Vision-based Missile Guidance in the Presence of Evasive Target Maneuvers

Abstract A nonlinear adaptive visual servo guidance law is presented for a bank-to-turn (BTT) missile airframe that achieves near zero miss distance interception of a target undergoing unknown evasive maneuvers. The controller is developed assuming unknown missile linear velocity and target depth measurements; hence can be regarded as a pure vision-based guidance law. By approximating the unknown, scaled relative velocity via power series expansion, a continuous adaptive parameter update law is developed to compensate for the unknown missile-target relative velocity and the depth measurements. In addition, robust elements are included in the guidance law to compensate for external disturbances and parameter identification errors. A rigorous Lyapunov-based stability analysis is utilized to prove uniformly ultimately bounded (UUB) stability of the system states, and high-fidelity numerical simulation results are provided to verify the performance of the proposed missile guidance law.

Vision-based navigation and guidance of a sensorless missile☆

Abstract The objective of this paper is to develop a vision-based terminal guidance system for sensorless missiles. Specifically, monocular vision-based relative navigation and robust control methods are developed for a sensorless missile to intercept a ground target maneuvering with unknown time-varying velocity. A mobile wireless sensor and actor network is considered wherein a moving airborne monocular camera (e.g., attached to an aircraft) provides image measurements of the missile (actor) while another moving monocular camera (e.g., attached to a small UAV) tracks a ground target. The challenge is to express the unknown time-varying target position in the time-varying missile frame using image feedback from cameras moving with unknown trajectories. In a novel relative navigation approach, assuming the knowledge of a single geometric length on the missile, the time-varying target position is obtained by fusing the daisy-chained image measurements of the missile and the target into a homography-based Euclidean reconstruction method. The three-dimensional interception problem is posed in pursuit guidance, proportional navigation, and the proposed hybrid guidance framework. Interestingly, it will be shown that by appropriately defining the error system a single control structure can be maintained across all the above guidance methods. The control problem is formulated in terms of target dynamics in a ‘virtual’ camera mounted on the missile, which enables design of an adaptive nonlinear visual servo controller that compensates for the unknown time-varying missile–target relative velocity. Stability and zero-miss distance analysis of the proposed controller is presented, and a high-fidelity numerical simulation verifies the performance of the guidance laws.

A touch interface for soft data modeling in Bayesian estimation

A novel approach for human-generated “soft information” modeling and Bayesian fusion using touch interface devices is presented. The human-generated soft information can be encoded using a combination of single, multiple, and overlapping strokes that represent arbitrary measurement likelihood functions which can be approximated using non-parametric density estimators. The proposed interface offers a flexible and natural medium to encode a large class of qualitatively distinct types of information for both positive and negative observations. The touch interface naturally provides robustness with respect to human variability in terms of psycho-physiological and environmental parameters without the need for offline training. An urban-target tracking example is provided to illustrate fusion of soft information (generated using the proposed soft sensor model) with measurements from traditional automated sensors.

Continuous congestion control for Differentiated-Services networks?

Network traffic in the transport layer of end-to-end congestion networks plays a vital role in effecting the throughput in the Medium Access Control (MAC) layer. Common queue length management techniques on nodes in such networks focus on servicing the packets based on their Quality of Service (QoS) requirements (e.g., Differentiated-Services, or DiffServ, networks). In this paper, a continuous control strategy is suggested for a DiffServ network to track the desired ensemble average queue length level specified by the network operator. A Lyapunov-based stability analysis is provided to illustrate global asymptotic tracking, and simulations demonstrate the performance and feasibility of the controller, along with showing global asymptotic tracking of the queue lengths in the Premium Service buffer.

Balancing Mission Requirement for Networked Autonomous Rotorcrafts Performing Video Reconnaissance

Abstract : Current and emerging missions, including active surveillance and tracking, terminal guidance and search and rescue, require image-feedback from camera-equipped vehicles. Certain mission scenarios and sensor restrictions may require the collaboration of assets over an ad-hoc network. The development in this paper extends efforts to balance trade-offs between asset/sensor cone positioning to satisfy mission requirements and network requirements such as maintaining network connectivity. To address the trade-offs between asset positioning and network connectivity, a prioritized task-function based guidance law is developed for a simple scenario containing three assets tracking teams of mobile targets. One developed task-function maintains a communication network by ensuring the distance between the UAV s does not exceed a critical threshold. Additional task-functions enable assets to keep targets of interest in the image cone by regulating image features derived from the camera view. The UAV s are modeled as rotorcraft using an LTI model equipped with a gimbaled camera. Early simulation results are provided to examine the behavior of the assets for different configurations of objects observed by the asset cameras. Future efforts will seek to improve performance by modifying the control law, possibly adding time varying tasks shaped by trajectory planning techniques.