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ABSTRACT: This paper presents the results of recent efforts towards the design of low cost and low weight technologies for autonomous vehicles. The test bench for such technologies is an autonomous ground vehicle (UGV) designed and built at University of Pisa. The main issues covered are related to guidance and navigation, by using an integrated system based on odometric and inertial sensors. The problem of obstacle recognition and avoidance is addressed by online vision-based algorithms, and compared with current methods (such as SLAM), presently used for this type of application. Cooperative localization and multi-vehicle coordination are also addressed using dynamic path allocation methods applied in the past to terrestrial unmanned air vehicles coordination and cooperative control. The proposed methodologies are validated through computer simulation, as well as via limited field experiments.
Recent Advances in Space Technologies, 2007. RAST '07. 3rd International Conference on; 07/2007
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ABSTRACT: The paper presents an obstacle avoidance algorithm to be used for autonomous ground vehicles applications. The proposed method improves some of the limitations of the recently developed null space based behavioral control. The technique divides the problem into tasks, which are associated to increasing priority. Activities with lower priority do not interfere with those having higher priority. The scenario is supposed known only partially, and the complete environment is reconstructed during the mission, with the aid of stereoscopic vision sensors. The validity of the method is currently verified via computer simulations.
Intelligent Vehicles Symposium, 2007 IEEE; 07/2007
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ABSTRACT: In this paper we use a probabilistic approach to detect conflicts between aircraft. The proposed control system is decentralized; each airplane detects a possible conflict and acts to resolve it without the need of cooperative work. The determination of conflict resolution trajectories is geometric. Cases of multiple conflicts have been considered.
American Control Conference, 2003. Proceedings of the 2003; 07/2003
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ABSTRACT: The paper presents some aspects that have become critical in the context of guidance navigation and control of unmanned aerial vehicles. The envisioned cost-effectiveness of unmanned air vehicles in support of a variety of military and civilian applications has introduced basic and applied research challenges in areas such as levels of autonomy and "intelligence" of the platform. interaction with manned control centers. reliability and safety of operations. and control management of single vehicle. as well as formation flights. The paper addresses issues such as dynamic modeling. formation management and control. and guidance aspects. Their origin and potential solutions are presented with particular attention to flexible formation keeping.
05/2003;
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ABSTRACT: The paper presents some results on global exponential stability of linear time invariant systems with different time scales. Once fast and slow subsystems are derived, and controllers synthesized using Reaching Law Approach, global closed loop stability is derived for the whole system using Lyapunov methods.
American Control Conference, 2002. Proceedings of the 2002; 02/2002
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ABSTRACT: Concerns formation flight of unmanned air vehicles.
Presents the evolution and finite state machine implementation of a deterministic approach to the problem of management of communication faults and aircraft loss inside a formation in autonomous flight. The aircraft formation is represented as an oriented graph and then a procedure, based on the shortest path theory, provides the optimal solution for the information flow within the formation. In case of faults this procedure run again providing with a sub-optimal solution while the formation geometry is changed by a formation manager that uses reconfiguration maps and heuristic laws to find the new best placement for the aircraft in the formation. Theoretical development and simulation results validating the fault management methodology are presented. The next step is testing of this formation management structure on a formation of flying UAV.
American Control Conference, 2002. Proceedings of the 2002; 02/2002
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ABSTRACT: A sensor failure detection and identification scheme for a closed
loop nonlinear system is described. Detection and identification tasks
are performed by estimating parameters directly related to potential
failures. An extended Kalman filter is used to estimate the
fault-related parameters, while a decision algorithm based on threshold
logic processes the parameter estimates to detect possible failures. For
a realistic evaluation of its performance, the detection scheme has been
implemented on an inverted pendulum controlled by real-time control
software. The failure detection and identification scheme is tested by
applying different types of failures on the sensors of the inverted
pendulum. Experimental results are presented to validate the
effectiveness of the approach
IEEE Transactions on Control Systems Technology 04/2001; · 1.77 Impact Factor
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ABSTRACT: This article proposes a new stability criterion for fuzzy
gain-scheduling controlled systems. This approach is based on the
differential inclusions theory. The control system design procedure uses
linear matrix inequalities techniques to find a fuzzy gain-scheduling
controller that stabilizes the nonlinear plant in a closed loop inside
the desired state space region
American Control Conference, 2001. Proceedings of the 2001; 02/2001
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ABSTRACT: This article describes an approach to close-formation flight of autonomous aircraft. A standard LQ-based structure was synthesized for each vehicle and for formation position error control using linearized equations of motion and a lifting line model of the aircraft wake. We also consider the definition of a formation management structure, capable of dealing with a variety of generic transmission and communication failures among aircraft. The procedure was developed using a decentralized approach and relies on the Dijkstra algorithm. The algorithm provides optimal path information sequencing in the nominal case, as well as the redundancy needed to accommodate failures in data transmission and reception. Several simulations were carried out, and some of the results are presented. The overall scheme appears to be a valuable starting point for further research, especially specialization to situations representing more detailed and operational failures.
IEEE control systems 01/2001; · 2.49 Impact Factor
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ABSTRACT: An approach to augment a linear compensator with an online neural
network is presented. This scheme provides the benefits of adaptation
with only minor modification to the existing control architecture, which
is a substantial advantage over other approaches that require complete
redesign. A neural network update law that guarantees bounded tracking
for the augmented architecture is outlined. The advantages of the
proposed technique are demonstrated through an application to an
autonomous underwater vehicle. The design requirement is for attitude
control such that robust trajectory following is achieved. A detailed
nonlinear model of the AUV is given, and an operating point for nominal
design is selected, about which a linear approximation is obtained.
Structured uncertainties due to errors in the computation of
hydrodynamic coefficients, linearization and truncation of plant
dynamics, as well as effects of unknown disturbances are included in the
control synthesis and compensated for by the neural network
American Control Conference, 2000. Proceedings of the 2000; 10/2000
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ABSTRACT: The paper proposes a dual loop controller for a particular class
of singularly perturbed linear systems. Two variable structure control
systems are synthesized on the reduced models and a particular choice of
switching surfaces allows robustness with respect to variations in pole
separation characteristics
American Control Conference, 2000. Proceedings of the 2000; 10/2000
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ABSTRACT: Rapid prototyping and controlled motion evaluation of complex
human-machine interfaces, from nuclear plant operation panels to deep
submerged underwater vehicles to advanced airplane cockpits, require
hardware-in-the-loop, man-in-the-loop, and software integration. What
appears to be needed is specific software to give designers tools for
analyzing and simulating complex and integrated projects. The research
software described in this article promises to fill that need, providing
a new synthetic environment for simulation and control synthesis of
dynamic systems. The article addresses problems of high performance,
realistic environments, and vehicle simulation, with particular
attention to synthetic world creation and visualization. The new
software is capable of handling most of the simulation and visualization
requirements highlighted
IEEE control systems 05/2000; · 2.49 Impact Factor
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ABSTRACT: MvTools, (Multivariable Tools) is a toolbox for Matlab 5.3
developed within the Department of Electrical Systems and Automation
(DSEA), University of Pisa, with the aim to offering to the Matlab users
(especially control engineers and control engineering students) a
complete toolbox for linear systems analysis and robust control
synthesis. All the operations are carried out by means of a single
graphical user interface, which allows the management of all the
different design steps, and the comparison between the most rewarded
robust control techniques. MvTools is not meant to replace the main
control synthesis toolboxes, but instead it relies on them to yield a
single environment in which all their best capabilities are integrated
and easily achieved. A help file in HTML format is provided and is
accessible within the program
Computer-Aided Control System Design, 2000. CACSD 2000. IEEE International Symposium on; 02/2000
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ABSTRACT: A controller synthesis based on state dependent Riccati equation
methods is presented. The methodology is applied to the path control of
a slow moving robot manipulator, for the purpose of method validation.
Due to hardware limitations, not all the manipulator joints were
controlled, and the resulting gains are obtained off-line using
numerical simulation on a model identified via least squares techniques.
Satisfactory results were obtained as compared to standard PID and
computed torque control methods
American Control Conference, 2000. Proceedings of the 2000; 02/2000
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ABSTRACT: Illustrates some strategies for dynamic systems simulation.
Hardware in the loop, man in the loop and software integration are key
points for rapid prototyping and safe design of complex man machine
interfaces, from nuclear plants operation panels to deep submerged
underwater vehicles to hypersonic airplanes cockpits. Specific software
appears to be needed in order to give designers tools to analyze and
simulate complex integration projects. Problems of high performance,
realistic environment and vehicles simulation are addressed, with
particular attention to synthetic worlds creation and visualization. A
new software is presented, capable of handling most of the simulation
and visualization requirements highlighted in the paper
American Control Conference, 1999. Proceedings of the 1999; 02/1999
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ABSTRACT: This paper presents two robust control synthesis methods for an
autonomous underwater. The problem statement requires the design of a
position and attitude control system for robust vehicle trajectory
following. A detailed nonlinear model of the vehicle was derived, an
operating point for nominal design was selected, and a multivariable
linear model of the vehicle was obtained by linearization around the
operating point. The presence of structured uncertainties due to errors
in the computation of hydrodynamic coefficients, dynamic linearization
and truncation, unknown disturbances, is included in the control
synthesis. Two robust controllers were designed: a nonlinear one using a
sliding mode approach, and a linear one using linear matrix inequalities
(LMI) synthesis techniques. The performance of the two controllers were
extensively evaluated and compared in simulation with a full nonlinear
model of the vehicle
American Control Conference, 1999. Proceedings of the 1999; 02/1999
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ABSTRACT: This paper shows the results of a research effort focused on
demonstrating the capabilities of hardware based online learning
parallel neural networks for a fault-tolerant flight control system.
Particularly, for a given aircraft mathematical model, two different
fault-tolerant schemes have been implemented in different neural
networks embedded on a mother-board with 4 TMS320C40 DSPs. The first
scheme provides sensor failure detection, identification, and
accommodation (SFDIA) for different types of sensor failures within a
flight control system assumed to be without physical redundancy in the
sensory capabilities. The second scheme provides actuator failure
detection, identification and accommodation (AFDIA) for different
actuator failures. Emphasis has been placed to ensure real-time
capabilities as well as an efficient integration between the AFDIA and
the SFDIA schemes without degradation of performance in terms of false
alarm rates and incorrect failure identification. The results of the
simulation following different types of failures are reported
American Control Conference, 1999. Proceedings of the 1999; 02/1999
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ABSTRACT: Detection, identification, and accommodation of sensor failures can be a challenging task for complex dynamic systems. This paper presents the comparison of two different approaches for the task of sensor failure detection, identification, and accommodation in a flight control system assumed to be without physical redundancy in the sensory capabilities. The first approach is based on the use of a set of online learning neural networks; the second approach is based on the use of a bank of Kalman filters. The objective is to evaluate the robustness of both schemes; the comparison is performed through testing of the schemes for several types of failures presenting different level of complexity in terms of detectability. The required computational effort for both schemes is also evaluated. For each of these failure types this comparison is performed at nominal conditions, that is with the system model and its noise perfectly modeled (with the Kalman filter scheme performing at nominal conditions), and at conditions, where discrepancies occur for the modeling of the system as well as the system and measurement noises. While the Kalman-filter-based scheme takes advantage of its robustness capabilities, the neural-network-based scheme, starting from a random numerical architecture, relies on the learning accumulated either online or from off-line simulations. The study reveals that online learning neural architectures have potential for online estimation purposes in a sensor validation scheme, particularly in the case of poorly modeled dynamics
Control Systems Technology, IEEE Transactions on 10/1998; 6(5):596-611. · 1.86 Impact Factor
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ABSTRACT: Develops a sliding mode controller in the presence of inequality
constraints on the system state variables. State constraints may arise
in many situations, such as limitations on allowable position and speed
for the case of mechanical systems. A formal framework for the
controller synthesis presented, and a validation using a spacecraft
attitude control problem is used for the testing of the proposed
algorithm
American Control Conference, 1998. Proceedings of the 1998; 07/1998
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ABSTRACT: A new approach to the synthesis of longitudinal autopilots for
missiles flying at high angle of attack regimes is presented. The
methodology is based on sliding mode control, and uses a combination of
aerodynamic surfaces and reaction jet thrusters, to achieve
controllability beyond stall. The autopilot is tested on a small section
of the flight envelope consisting of a fast 180° heading reversal in
the vertical plane, which requires robustness with respect to
uncertainties in the system's dynamics induced by large variations in
dynamic pressure and aerodynamic coefficients. Nonlinear simulation
results show excellent performance and capabilities of the control
system structure
IEEE Transactions on Control Systems Technology 06/1998; · 1.77 Impact Factor
