Showing papers presented at "Mediterranean Conference on Control and Automation in 2006"

A Survey of Control Allocation Methods for Ships and Underwater Vehicles

Abstract: Control allocation problems for marine vessels can be formulated as optimization problems, where the objective typically is to minimize the use of control effort (or power) subject to actuator rate and position constraints, power constraints as well as other operational constraints. In addition, singularity avoidance for vessels with azimuthing thrusters represent a challenging problem since a non-convex nonlinear program must be solved. This is useful to avoid temporarily loss of controllability in some cases. In this paper, a survey of control allocation methods for overactuated vessels are presented.

Control Allocation for Over-actuated Systems

Abstract: Much emphasis has been placed on over-actuated systems for air vehicles. Over-actuating an air vehicle provides a certain amount of redundancy for the flight control system, thus potentially allowing for recovery from off-nominal conditions. Due to this redundancy, control allocation algorithms are typically utilized to compute a unique solution to the over-actuated problem. Control allocators compute the commands that are applied to the actuators so that a certain set of forces or moments are generated by the control effectors. Usually, control allocation problems are formulated as optimization problems so that all of the available degrees of freedom can be utilized and, when sufficient control power exists, secondary objectives can be achieved. In this work, a survey of control allocation techniques will be given.

Vehicle and Mission Control of the DELFIM Autonomous Surface Craft

Abstract: DELFIM is an autonomous surface craft developed at ISR/IST for automatic marine data acquisition and to serve as an acoustic relay between submerged craft and a support vessel. The paper describes the navigation, guidance, and control systems of the vehicle, together with the mission control system that allows end-users to seamlessly program and run scientific missions at sea. Practical results obtained during sea tests in the Atlantic, near Azores islands, are briefly summarized and discussed.

Autonomous Surface Craft: prototypes and basic research issues

Abstract: An overview of the prototypes of Autonomous Surface Craft (ASC) developed in the last years is presented in this paper, together with a discussion of main research issues, design trends and technological developments.

Modeling and Control System Design for a UAV Helicopter

Abstract: We present in this paper a linearized hovering model of a UAV helicopter obtained using the in-flight data generated through a perturbation method. The UAV helicopter is constructed from a radio-controlled helicopter by integrating an onboard system, which includes a data processing unit, a data acquisition system, a wireless communications and all necessary sensors. A flight control law is then designed using a newly developed nonlinear control technique, i.e. the composite nonlinear feedback control. Actual flight testing shows that the design is successful.

A Neural Network Solution for Fixed-Final Time Optimal Control of Nonlinear Systems

Abstract: We consider the use of neural networks and Hamilton-Jacobi-Bellman equations towards obtaining fixed-final time optimal control laws in the input nonlinear systems. The method is based on Kronecker matrix methods along with neural network approximation over a compact set to solve a time-varying Hamilton-Jacobi-Bellman equation. The result is a neural network feedback controller that has time-varying coefficients found by a priori offline tuning. Convergence results are shown. The results of this paper are demonstrated on two examples.

Adaptive flow control using slope seeking

Abstract: Besides controller synthesis based on a high dimensional discretization or low dimensional description of the Navier-Stokes equation or based on black-box models identified in wind tunnel experiments, model-free methods such as extremum seeking control can be used advantageously to control fluid flows. This contribution gives a survey on several successful applications of extremum seeking control showing its versatility and ease of application. Emphasis is put on the slope seeking variant of extremum seeking control. SISO and MISO examples are considered. Extremum seeking control is applied to minimize the drag of a bluff body, to increase the lift of a generic high-lift wing, and to reduce the noise emitted by a turbo-machine.

A Finite Time Unknown Input Observer For Linear Systems

Abstract: This paper presents a finite time unknown input observer for linear systems, i.e. an observer which estimates the exact state of a linear system with unknown input disturbances in a predefined finite time. Based on recent results in observer design for linear systems, conditions are established to guarantee finite time convergence of the estimation error dynamics. The proposed observer is demonstrated on a DC motor for the estimation of the rotor current and the angular velocity despite an unknown input disturbance in the stator voltage.

Decentralized Cohesive Motion Control of Multi-Agent Formations

Abstract: This paper presents a set of decentralized control laws for the cohesive motion of 2-dimensional multi-agent formations. We consider rigid and constraint-consistent formations that can be modeled by directed graphs. We analyze both of the two main hierarchical structures for such 2-dimensional formations: The leader-follower and the three-coleader structures. For each structure, we derive a control scheme that moves a given rigid and constraint-consistent formation whose initial position and orientation are specified to a new desired position and orientation cohesively, i.e., without deforming the shape of the formation during the motion. We elaborate our designs considering the path smoothness, chattering, and agent kinematics issues and demonstrate their effectiveness via a set of simulation results. Manuscript received February 15, 2006. This work is supported by National ICT Australia, which is funded by the Australian Government?s Department of Communications, Information Technology and the Arts and the Australian Research Council through the Backing Australia?s Ability Initiative.

Vision-Based Autonomous Probe and Drogue Aerial Refueling

Abstract: This paper presents a simulation setup for probe and drogue autonomous aerial refueling. The overall system consists of tanker and UAV models, the hose model, the atmospheric disturbances and the formation keeping controllers and of a robust artificial vision system. The UAV model is a YF-22 developed at West Virginia University. The vision system is employed to allow the UAV to measure its relative displacement from the drogue with no radio communication between the two aircrafts. Simulation results show the performances of the entire system, with a main focus on the vision system

Experiments of Formation Control with Collisions Avoidance using the Null-Space-Based Behavioral Control

Abstract: In this paper an approach to formation control with collisions avoidance of a multi-robot system is presented. The proposed technique, namely the Null-Space-Based Behavioral Control, is a behavior based approach aimed at coordinating a platoon of mobile robots while performing different missions. The overall mission is firstly decomposed in elementary tasks and, for each of them, a motion reference command to each robot is elaborated referring to an inverse kinematic approach. The proposed technique is novel in the way it combines the output required by each task in order to obtain the final motion command for each robot; in details, it uses a hierarchy-based approach that uses the null-space projection to handle multiple, eventually conflicting, tasks. The proposed technique has been experimentally validated while performing a formation control mission with a platoon of 5 Khepera II mobile robots; during the mission a change of formation is commanded that requires the vehicles to avoid collisions among themselves and with external obstacles.

3-Aircraft Formation Flight Experiment

Abstract: This paper will present the results obtained from a formation flight experiment using 3 YF-22 research UAVs built and developed at West Virginia University. In the planned 3-aircraft flight configuration, a Radio Control (R/C) pilot maintains manual control of the 'leader' aircraft while two autonomous 'follower' aircraft maintain a pre-defined position and orientation with respect to the lead vehicle. The flight-testing program associated with this effort was quite substantial and involved approximately 100 sorties involving all three aircraft models in the program. Initial flight-testing phases evaluated a variety of issues, including; aircraft handling qualities, dynamic characteristics, electronic payload performance; specifically the data acquiring capabilities and the real time execution of control laws. During the final flight season program, a total of five formation flight experiments were successfully performed; specifically four 2-aircraft formations and one 3-aircraft formation flight demonstration.

Swarm Formation Control with Potential Fields Formed by Bivariate Normal Functions

Abstract: A novel method is presented for swarm formation control with potential fields generated from bivariate normal probability density functions (pdfs) that construct the surface the swarm members move upon controlling the swarm geometry and member spacing as well as manage obstacle avoidance. Limiting functions provide tighter swarm control by modifying and adjusting a set of control variables, forcing the swarm to behave according to set constraints. Bivariate normal functions and limiting functions are combined to guarantee obstacle avoidance and control swarm member orientation and swarm movement as a whole. The presented approach, compared to others, is simple, computationally efficient, and scales well to different swarm sizes and swarm models. The method is applied to a simple vehicle model, and simulation results are presented on a homogeneous swarm of ten robot vehicles for different formations.

LPV fault detection of glucose-insulin system

Abstract: A new approach is proposed in the paper for unknown glucose inlet estimation in case of diabetic patients under insensitive care in form of a Linear Parameter Varying (LPV) model class. The nonlinear two compartment glucose-insulin system is rewritten in affine parameter varying form in order to handle the dynamics with LPV Fault Detection and Isolation (FDI) method. The aim of the closed-loop fault detection, on the one hand, is to estimate the unknown disturbance input of the system, on the other hand to recognize the actuator fault. A parameter varying controller assures the performance requirements and stability of the system.

A comparison of Pose Estimation algorithms for Machine Vision based Aerial Refueling for UAVs

Abstract: This paper focuses on the analysis of the performance of specific `detection and labeling? and `pose estimation? algorithms within a Machine Vision (MV)-based approach for the problem of Autonomous Aerial Refueling (AAR) of UAVs. A robust `detection and labeling algorithm? for the correct identification and sorting of the optical markers is proposed; a sorted list of marker positions is then provided as input to the `pose estimation? algorithm. A detailed study of the performance of two specific `pose estimation? algorithms (GLSDC and LHM) is performed with special emphasis on the required computational effort as well as on the robustness and error propagation characteristics. Extensive simulation studies demonstrate the performance of the LHM and GLSDC algorithms and show the importance of a robust `detection and labeling? algorithm. The simulation effort is performed using a detailed modeling of the AAR maneuver according to the USAF refueling method.

Tracking with Steady-State Optimization: an Application to Air-Breathing Hypersonic Vehicle Control

Abstract: The specific control problem addressed in the paper is the design of controllers that ensure asymptotic tracking of output reference trajectories for overactuated systems. The redundancy in the input space is used to optimize the steady state performance of the closed-loop system. Since the considered plant models are not square, the control input and state trajectories in steady state that enforce perfect tracking are not unique. The proposed methodology employs a continuous parameterization of all possible steady state input trajectories, that is used for optimizing the selection of the steady state input, while providing perfect tracking and fulfillment of constraints on the magnitude of the control input. An application to altitude and velocity tracking control for an hypersonic vehicle employing air-breathing (scramjet) propulsion is presented and discussed.

Decentralized Formation Tracking of Multi-vehicle Systems with Nonlinear Dynamics

Abstract: The problem of formation tracking can be stated as multiple vehicles are required to follow spatial trajectories while keeping a desired inter-vehicle formation pattern in time. This paper considers vehicles with nonlinear dynamics and nonholonomic constraints and very general trajectories that can be generated by some reference vehicles. We specify formations using the vectors of relative positions of neighboring vehicles and use consensus-based controllers in the context of decentralized formation tracking control. The key idea is to combine consensus-based controllers with the cascaded approach to tracking control, resulting in a group of linearly coupled dynamical systems. We examine the stability properties of the closed loop system using cascaded systems theory and nonlinear synchronization theory. Simulation results are presented to illustrate the proposed method.

Adaptive Optimizing Dynamic Control Allocation Algorithm for Yaw Stabilization of an Automotive Vehicle using Brakes

Abstract: In this paper we present a yaw stabilization scheme for an automotive vehicle, that has been implemented in a realistic nonlinear multi body vehicle simulation environment. The stabilization strategy is based on two modules independent in design, a high level module that deals with the motion control objective and a low level module that deals with the actuator control allocation. The high level module consists of yaw-rate reference generator and high level controller that provides the low level control allocation module with a desired torque about the yaw axis. The task of the low level module is to command the individual brakes, the longitudinal clamping force, such that the actual torque about the yaw axis tends to the desired torque. These commands are generated by a dynamic control allocation algorithm that also takes actuator constraints and uncertainty in the tyre-road friction model into consideration. Simulation cases where the tyre-road friction parameter was considered both known and unknown, show that the control scheme stabilizes the vehicle in extreme manoeuvres where the nonlinear vehicle yaw dynamics otherwise becomes unstable in the sense of over or under-steering.

Adaptive Control Using Neural Network Augmentation for a Modified F-15 Aircraft

Abstract: Description of the performance of a simplified dynamic inversion controller with neural network augmentation follows. Simulation studies focus on the results with and without neural network adaptation through the use of an F-15 aircraft simulator that has been modified to include canards. Simulated control law performance with a surface failure, in addition to an aerodynamic failure, is presented. The aircraft, with adaptation, attempts to minimize the inertial cross-coupling effect of the failure (a control derivative anomaly associated with a jammed control surface). The dynamic inversion controller calculates necessary surface commands to achieve desired rates. The dynamic inversion controller uses approximate short period and roll axis dynamics. The yaw axis controller is a sideslip rate command system. Methods are described to reduce the cross-coupling effect and maintain adequate tracking errors for control surface failures. The aerodynamic failure destabilizes the pitching moment due to angle of attack. The results show that control of the aircraft with the neural networks is easier (more damped) than without the neural networks. Simulation results show neural network augmentation of the controller improves performance with aerodynamic and control surface failures in terms of tracking error and cross-coupling reduction.

Model-Based Control with Intermittent Feedback

Abstract: In this paper we apply the concept of Intermittent Feedback to a class of networked control systems known as Model-Based Networked Control Systems (MB-NCS). MB-NCS use an explicit model of the plant in order to reduce the network traffic while attempting to prevent performance degradation. In the previous body of work regarding MB-NCS, updates of the plant were given instantaneously; however, in this paper we consider the case where the loop remains closed for a finite length fixed interval before the control system returns to open-loop. We provide a full description of the output, as well as a necessary and sufficient condition for stability of the system. We also provide examples in order to illustrate the behavior indicated by the theory, and we show the advantages of the approach. Finally, we conclude the paper with discussions on possible future extensions.

Formation Control Laws for Autonomous Flight Vehicles

Abstract: The problem of aircraft formation dynamics and control is investigated from the viewpoint of formation architecture. Three different formation structures, Leader-Wingman, Virtual Leader and Behavioral approaches are introduced. A comparative study is made using an unified approach through a suitable control law based on the dynamic inversion approach.

Experimental Validation of a Real-Time Model-Based Sensor Fault Detection and Isolation System for Unmanned Ground Vehicles

Abstract: This paper presents experimental validation and implementation issues of a model-based sensor fault detection and isolation (FDI) system applied to unmanned ground vehicles (UGVs) Enhanced structural analysis is followed to build the residual generation module, followed by different residual evaluation modules capable of detecting single and multiple sensor faults The overall proposed sensor fault detection and isolation system (SFDIS) has been tested in real-time on the ATRV-Jr mobile robot when following different trajectories in an outdoors environment The robot sensor suite includes a Global Positioning System (GPS) antenna, an Inertial Measurement Unit (IMU), and two incremental optical encoders To increase residual sensitivity to sensor faults, the IMU readings are filtered using a Kalman filter (KF), resulting in a robust and accurate FDI system that detects and isolates single/multiple sensor faults

On strong regular stabilizability for linear neutral type systems

Abstract: For a large class of linear neutral type systems the problem of stabilizing feedback is studied. The proposed feedback is regular, in this sense that it does not contain the derivative of delayed state as it is usually considered. This allows to maintain the system in the same class. The obtained closed loop system is asymptotically stable but not expondentially stable.

Planning Optimal Motions for a DELTA Parallel Robot

Abstract: This article deals with the problem of planning optimal trajectories for a DELTA parallel robot. The planning process consists of searching for a motion ensuring the accomplishment of the assigned task, minimizing a cost function and satisfying various constraints inherent to the robot kinematics and dynamics. This problem is treated via (i) an adequate parameterization of the operational coordinates of the mobile platform and (ii) the use of the sequential quadratic programming method for solving the resulting nonlinear optimization problem. The proposed approach is applied to tasks involving either point-to-point motions or motions along specified paths.

Modelling and identification of the Charlie2005 ASC

Abstract: This paper discusses a practical model, with respect to the performance of basic sensors available on-board the vessel, and the corresponding identification procedure for guidance and control of the Charlie2005 ASC. The work is supported by extended at sea trials.

Autotuning Autopilots for Micro-ROVs

Abstract: Underwater vehicles are highly nonlinear and complex systems, that makes designing autopilots extremely difficult. This paper presents autotuning as a method for tuning parameters of a micro-ROV autopilot. The main benefit of this procedure is that the model of the process does not have to be known. Autotuning is often used for industrial processes but not on marine vessels. This procedure, which is performed in closed-loop, is completely automated and enables the operator to retune an autopilot whenever ROV performance is degraded (due to different operating points, tether influence, currents, etc.). In this article we use already known different autotuning recommendations (primarily designed for Type 0 processes) with some modifications which we recommend for micro-ROVs. We also give results of using different types of PID controllers, whose parameters are being tuned. A real life demonstration on a VideoRay Pro II micro-ROV is provided.

High-Order Sliding-Mode Observer for Linear Systems with Unknown Inputs

Abstract: Extended sufficient conditions for the observation of linear time invariant systems with unknown inputs are formulated. A new observation scheme is proposed. An additional linear term ensuring global stability is included for this sake in the differentiation algorithm based on high-order sliding-modes. The global robust finite-time-convergent estimation of observable states and unknown inputs is obtained, exact in the absence of measurement noises. Under the detectability conditions the whole state is asymptotically estimated. The accuracy of the estimation in the presence of bounded deterministic Lebesgue-measurable noises and discrete sampling is worked out.

Performance Indices and Tuning in Process Control

Abstract: Industrial practice in process control shows a very wide gap with respect to the theory, as usually taught at the university. Standard controller tuning is often a compromise between performance and robustness. In this paper we examine some common PI(D) controller tuning rules and the achievable performances for a PI(D) controlled plant modeled as a first order plus time delay. The performance indices considered are IAE and ISE in a particular non-dimensional form including also controller output variations. The output performance indices are weakly dependent on loop gain. Therefore loop gain is essentially constrained by robustness, while the indices are dominated by the frequency response. Conversely the controller output variations are strongly dependent on the loop gain.

Soft Computing Design of a Linear Quadratic Gaussian Controller for an Unmanned Surface Vehicle

Abstract: To develop an unmanned surface vehicle (USV), several issues need to be addressed, however, the most important being the navigation, guidance and control which dictates the performance of the whole system. Herein, the control problem is addressed by designing a fuzzy logic based linear quadratic Gaussian autopilot for the Springer USV being developed at the University of Plymouth, UK. A model is first developed by the application of system identification techniques to the acquired vehicle data. Simulation results are presented to demonstrate the efficacy of the proposed approach.