Adam Howell

Border patrol and surveillance missions using multiple unmanned air vehicles

In this paper, we propose hierarchical control architecture for a system that does border or perimeter patrol using unmanned air vehicles (AUV). By control architecture we mean a specific way of organizing the motion control and navigation functions performed by the UAV. It is convenient to organize the functions into hierarchical layers. This way, a complex design problem is partitioned into a number of more manageable subproblems that are addressed in separate layers. This paper discusses vehicle control requirements and maps them onto layered control architecture. The formalization of the hierarchy is accomplished in terms of the specific functions accomplished by each layer and of the interfaces between layers. The implementation of the layers is discussed and illustrative examples are provided.

Robust stabilization and ultimate boundedness of dynamic surface control systems via convex optimization

In this paper, a new method of analysing the controller gains and filter time constants for dynamic surface control (DSC) is presented. First, since DSC provides linear error dynamics with perturbation terms for a class of non-linear systems, the design method can be used to assign the system matrix eigenvalues of the closed loop error dynamics. Then a procedure for testing the stability and performance of the fixed controller in the face of uncertainties is presented. Finally, an ellipsoidal approximation of the tracking error bounds for a tracking problem is obtained via convex optimization.

Fault tolerant control and classification for longitudinal vehicle control

In this paper a new method of analyzing for the performance loss caused by faults in the systems is presented, and applied to the design of a fault tolerant longitudinal controller for a transit bus. Based on the amount of performance loss measured by a quadratic function, fault impact assessment is developed for both single and multiple faults. More specifically, ellipsoidal approximation of the tracking error bounds via dynamic surface control (DSC) is obtained via convex optimization technique for the nonlinear closed-loop system. Relying on the fault impact to the closed loop system and its isolatability on a fault detection and diagnosis system, the fault classification is proposed to provide a switching logic in the framework of a switched hierarchical structure. Finally, simulation results of the fault tolerant controller and corresponding fault classification are shown for multiple multiplicative faults.

Dynamic surface control design for a class of nonlinear systems

A novel method for analyzing the controller gains and filter time constants of dynamic surface control (DSC) is presented. First, DSC provides linear closed loop error dynamics with bounded perturbation terms for a class of nonlinear systems. This can be used to assign the desired eigenvalues to the system matrix of the error dynamics for the nominal stability. Then, a procedure for testing the stability and performance of the fixed controller in the face of uncertainties is presented. Finally, a feasible quadratic Lyapunov function for a regulation problem and an ellipsoidal approximation of tracking error bounds are obtained via convex optimization.

A fault management system for longitudinal vehicle control in AHS

The design of a fault management system (FMS) for longitudinal control in automated highway systems (AHS) is presented. A hierarchical AHS architecture with vehicles organized in platoons is considered. The FMS is based on a fault identification module that presents a set of residuals to the FMS. The system handles up to twelve single different faults in the actuators, sensors and communication devices. Strategies to handle faults are divided into two groups. In the first group, redundancy of the fault detection schemes is exploited to substitute faulty information; normal mode operation of the AHS is still feasible if some critical parameters are adjusted. The second group contains faults whose occurrence requires specific degraded mode maneuvers to be executed. The FMS was implemented using SHIFT, a hybrid system simulation language. The simulation results obtained in SmartAHS, a micro-simulator for AHS based on SHIFT, are presented.

Hybrid supervisory control for real-time embedded bus rapid transit applications

Complex large-scale embedded systems arise in many applications, in particular in the design of automotive systems, controllers, and networking protocols. In this paper, we attempt to present a review of salient results in modeling of complex large-scale embedded systems, including hybrid systems, and review existing results for composition, analysis, model checking, and verification of safety properties. We then present a library of vehicle models designed for vehicle following [cruise control (CC), adaptive CC (ACC), cooperative ACC (CACC)]. The models and controllers attempt to cross the chasm between theory and practice by capturing real-world challenges faced by industry and making the library accessible in a public domain form, with a gradation of levels of complexity. The most complex level was used for controller design and simulation for a bus rapid transit demonstration. Experimental results are shown.

Cooperative Range Estimation and Sensor Diagnostics for Vehicle Control

An integrated sensor fusion and fault diagnostic for the cooperative estimation of range and range rate in automated vehicles is presented in this paper. A virtual range sensor created by combining local sensor measurements and a wireless communication link between vehicles is fused with measurements from a Doppler radar and lidar. The sensor fusion is conducted by using a sequential variant of the nonparametric probabilistic data association filter with validation gating. Fault diagnostics are incorporated into the sensor fusion by thresholding the Mahalanobis distance computed in the validation stage. Performance of the integrated system is verified and demonstrated using experimental data obtained from low-speed vehicle following tests.Copyright

A complete fault diagnostic system for automated vehicles

Abstract A “complete” fault diagnostic system is developed for automated vehicles operating as a platoon on an automated highway system. The diagnostic system is designed to monitor the complete set of sensors and actuators used by the lateral and longitudinal controllers of the vehicle, including radar sensors, magnetometers and inter-vehicle communication systems. A fault in any of the twelve sensors and three actuators is identified without requiring any additional hardware redundancy. The diagnostic system uses parity equations and several reduced-order nonlinear observers constructed from a simplified dynamic model of the vehicle. Nonlinear observer design techniques are used to guarantee asymptotically stable convergence of estimates for the nonlinear dynamic system. Different combinations of die ooserver estimates and the available sensor measurements are then processed to construct a bank of residues. The paper analytically shows that a fault in any of the sensors or actuators creates a unique subset of these residues to grow so as to enable exact identification of the faulty component. This conference paper is a brief summary of the full paper submitted for journal publication. Both simulation and experimental results that demonstrate the effectiveness of the fault diagnostic system in the presence of various faults are included in the journal version of this paper.