F. Conticelli

Bio: F. Conticelli is an academic researcher from Sant'Anna School of Advanced Studies. The author has contributed to research in topics: Exponential stability & Adaptive control. The author has an hindex of 8, co-authored 21 publications receiving 247 citations.

Real-time control system analysis: an integrated approach

Abstract: A typical approach for realizing digital controllers is to synthesize the control law in the continuous-time domain and then to implement it as a set of periodic threads complying with tight temporal constraints. The strict respect of all deadlines can often be obtained only by selecting low activation rates which determine a remarkable performance degradation. On the other hand, many control systems are known to tolerate a certain amount of deadline misses. We realized a software tool which allows to numerically evaluate the quality of the control resulting from the scheduling. The tool has been applied to a robotic case study. Considering a meaningful set of trajectories, we have drawn experimental evidence that the use of soft real-time constraints on the threads leads to significant improvements in the system performance. The performance improvement is more evident if scheduling approaches like resource reservation schemes, able to separate the thread importance from its activation rate, are used.

Image-based visual servoing of nonholonomic mobile robots

Abstract: In this paper, a novel image-based visual approach for the position control of a nonholonomic mobile robot is presented. The mobile robot is endowed with a fixed camera, and visual feedback is used to control the robot pose with respect to a rigid object of interest. After introducing a three dimensional state space representation of the camera-object visual interaction model fully defined in the image plane, a closed-loop stabilizing control law is designed, based on Lyapunov's direct method. The image-based control scheme, which uses a discontinuous change of coordinates, ensures global asymptotic stability of the closed-loop visual system. Moreover, in the case of known height of the object, global stability is formally proved using an adaptive control law. Experimental results obtained with a tank model validate the framework, both in terms of system convergence and control robustness.

Nonlinear controllability and stability analysis of adaptive image-based systems

Abstract: In this paper, a novel adaptive visual feedback scheme is presented to solve the problem of controlling the relative pose between a robot camera and a rigid object of interest. By exploiting nonlinear controllability properties, uniform asymptotic stability in the large of the image reference set-point is proved using Lyapunov's direct method. Moreover, uniform boundedness of the whole state vector is ensured by using an adaptive nonlinear control scheme, in case of unknown object depth. Experimental results with a six-degree-of-freedom robot manipulator endowed with a camera on its wrist validate the framework.

Discrete-time robot visual feedback in 3D positioning tasks with depth adaptation

Abstract: An adaptive visual feedback scheme is designed to perform 3D positioning tasks. The dynamic camera-object interaction model is derived in discrete time, since the visual sampling time is not negligible at the current state of technology. Active contours are used to track the 2D projection of the visible object's surface in the image plane. Uniform asymptotic stability of the image reference set-point is proved using the Lyapunov direct method, and a 3D estimation procedure, based on prediction errors, is used to cope with the unknown depth of the object. Experimental results with a 6-DOF robot manipulator in eye-in-hand configuration validate the theoretical framework in real conditions.

Nonlinear controllability and stability analysis of adaptive image-based systems

Abstract: In this paper, a novel adaptive visual feedback scheme is presented to solve the problem of controlling the relative pose between a robot camera and a rigid object of interest. After deriving the image-based state space representation of the camera-object visual interaction model in terms of global coordinates (2D points) fully defined in the image plane, it is shown that the system is completely controllable. By exploiting nonlinear controllability properties, global uniform asymptotic stability of the image reference set-point is proved using Lyapunov's direct method. Moreover, global uniform boundedness of the whole state vector is ensured by using an adaptive nonlinear control scheme, in case of unknown depth of the object. Experimental results with a 6-DOF robot manipulator endowed with a camera on its wrist validate the framework.

Feedback Control Real-Time Scheduling: Framework, Modeling, and Algorithms*

Abstract: We develop Feedback Control real-time Scheduling (FCS) as a unified framework to provide Quality of Service (QoS) guarantees in unpredictable environments (such as e-business servers on the Internet). FCS includes four major components. First, novel scheduling architectures provide performance control to a new category of QoS critical systems that cannot be addressed by traditional open loop scheduling paradigms. Second, we derive dynamic models for computing systems for the purpose of performance control. These models provide a theoretical foundation for adaptive performance control. Third, we apply established control methodology to design scheduling algorithms with proven performance guarantees, which is in contrast with existing heuristics-based solutions relying on laborious design/tuning/testing iterations. Fourth, a set of control-based performance specifications characterizes the efficiency, accuracy, and robustness of QoS guarantees. The generality and strength of FCS are demonstrated by its instantiations in three important applications with significantly different characteristics. First, we develop real-time CPU scheduling algorithms that guarantees low deadline miss ratios in systems where task execution times may deviate from estimations at run-time. We solve the saturation problems of real-time CPU scheduling systems with a novel integrated control structure. Second, we develop an adaptive web server architecture to provide relative and absolute delay guarantees to different service classes with unpredictable workloads. The adaptive architecture has been implemented by modifying an Apache web server. Evaluation experiments on a testbed of networked Linux PC's demonstrate that our server provides robust relative/absolute delay guarantees despite of instantaneous changes in the user population. Third, we develop a data migration executor for networked storage systems that migrate data on-line while guaranteeing specified I/O throughput of concurrent applications.

Feedback–Feedforward Scheduling of Control Tasks

Abstract: A scheduling architecture for real-time control tasks is proposed. The scheduler uses feedback from execution-time measurements and feedforward from workload changes to adjust the sampling periods of the control tasks so that the combined performance of the controllers is optimized. The performance of each controller is described by a cost function. Based on the solution to the optimal resource allocation problem, explicit solutions are derived for linear and quadratic approximations of the cost functions. It is shown that a linear rescaling of the nominal sampling frequencies is optimal for both of these approximations. An extensive inverted pendulum example is presented, where the performance obtained with open-loop, feedback, combined feedback and feedforward scheduling, and earliest-deadline first scheduling are compared. The performance under earliest-deadline first scheduling is explained by studying the behavior of periodic tasks under overload conditions. It is shown that the average values of the sampling periods equal the nominal periods, rescaled by the processor utilization.

Image-Based Visual Servoing for Nonholonomic Mobile Robots Using Epipolar Geometry

Abstract: We present an image-based visual servoing strategy for driving a nonholonomic mobile robot equipped with a pinhole camera toward a desired configuration. The proposed approach, which exploits the epipolar geometry defined by the current and desired camera views, does not need any knowledge of the 3-D scene geometry. The control scheme is divided into two steps. In the first, using an approximate input-output linearizing feedback, the epipoles are zeroed so as to align the robot with the goal. Feature points are then used in the second translational step to reach the desired configuration. Asymptotic convergence to the desired configuration is proven, both in the calibrated and partially calibrated case. Simulation and experimental results show the effectiveness of the proposed control scheme

Feedback Control Architecture and Design Methodology for Service Delay Guarantees in Web Servers

Abstract: This paper presents the design and implementation of an adaptive Web server architecture to provide relative and absolute connection delay guarantees for different service classes. The first contribution of this paper is an adaptive architecture based on feedback control loops that enforce desired connection delays via dynamic connection scheduling and process reallocation. The second contribution is the use of control theoretic techniques to model and design the feedback loops with desired dynamic performance. In contrast to heuristics-based approaches that rely on laborious hand-tuning and testing iteration, the control theoretic approach enables systematic design of an adaptive Web server with established analytical methods. The adaptive architecture has been implemented by modifying an Apache server. Experimental results demonstrate that the adaptive server provides robust delay guarantees even when workload varies significantly

Homography-based visual servo regulation of mobile robots

Abstract: A monocular camera-based vision system attached to a mobile robot (i.e., the camera-in-hand configuration) is considered in this paper. By comparing corresponding target points of an object from two different camera images, geometric relationships are exploited to derive a transformation that relates the actual position and orientation of the mobile robot to a reference position and orientation. This transformation is used to synthesize a rotation and translation error system from the current position and orientation to the fixed reference position and orientation. Lyapunov-based techniques are used to construct an adaptive estimate to compensate for a constant, unmeasurable depth parameter, and to prove asymptotic regulation of the mobile robot. The contribution of this paper is that Lyapunov techniques are exploited to craft an adaptive controller that enables mobile robot position and orientation regulation despite the lack of an object model and the lack of depth information. Experimental results are provided to illustrate the performance of the controller.