Wireless networked embedded systems are becoming increasingly important in a wide area of technical fields. In this tutorial paper we present recent results on design and control of these systems developed within the project Reconfigurable Ubiquitous Networked Embedded Systems (RUNES), which is an European Integrated Project with the aim to control complexity in networked embedded systems by developing robust and scalable middleware systems. New components for control under varying network conditions are discussed for the RUNES architecture. The complexity of the closed-loop system is increased due to the coupling with the disturbances introduced by the communication system. The network may introduce additional delays, jitter, data rate limitations, packet losses etc. Experimental work on integration test beds that demonstrates these results is shown together with motivating links to the RUNES disaster relief tunnel scenario.
We present an industrial case study in automotive control of significant complexity: the new common rail fuel injection system for Diesel engines, currently under production by Magneti Marelli Powertrain. In this system, a flow-rate valve, introduced before the High Pressure (HP) pump, regulates the fuel flow that supplies the common rail according to the engine operating point. The standard approach followed in automotive control is to use a mean-value model for the plant and to develop a controller based on this model. In this particular case, this approach does not provide a satisfactory solution as the discrete-continuous interactions in the fuel injection system, due to the slow time-varying frequency of the HP pump cycles and the fast sampling frequency of sensing and actuation, play a fundamental role. We present a design approach based on a hybrid model of the Magneti Marelli Powertrain common-rail fuel-injection system for four-cylinder multi-jet engines and a hybrid approach to the design of a rail pressure controller. The hybrid controller is compared with a classical mean-value based approach to automotive control design whereby the quality of the hybrid solution is demonstrated.
Finite plans proved to be an efficient method to steer complex control systems via feedback quantization. Such finite plans can be encoded by finite–length words constructed on suitable alphabets, thus permitting transmission on limited capacity channels. In particular flat systems can be steered computing arbitrarily close approximations of a desired equilibrium in polynomial time. The paper investigates how the efficiency of planning is affected by the choice of inputs, and provides some results as to optimal performance in terms of accuracy and range. Efficiency is here measured in terms of computational complexity and description length (in number of bits) of finite plans.
The Integral Input to State Stability (iISS) property is studied is the context of nonlinear time-invariant systems in cascade. A sufficient condition is given, in terms of the storage function of each subsystem, to ensure that the cascade composed of an iISS system driven by a Globally Asymptotically Stable (GAS) one remains GAS. Some sufficient conditions for the preservation of the iISS property under a cascade interconnection are also presented.
We present a converse Lyapunov result for nonlinear time-varying systems that are uniformly semiglobally asymptotically stable. This stability property pertains to the case when the size of initial conditions may be arbitrarily enlarged and the solutions of the system converge, in a stable way, to a closed ball that may be arbitrarily diminished by tuning a design parameter of the system (typically but not exclusively, a control gain). This result is notably useful in cascaded-based control when uniform practical asymptotic stability is established without a Lyapunov function, , ıt e.g.} via averaging. We provide a concrete example by solving the stabilization problem of a hovercraft.
This paper aims to give sufficient conditions for a cascade composed of nonlinear time-varying systems that are uniformly globally practically asymptotically stable (UGPAS) to be UGPAS. These conditions are expressed as relations between the Lyapunov function of the driven subsystem and the interconnection term. Our results generalize previous theorems that establish the uniform global asymptotic stability of cascades.
We present a robustness analysis for PID-controlled robot manipulators. For robot manipulators under the influence of external disturbances we provide a proof, and a tuning procedure, to establish uniform semiglobal practical asymptotic stability. In particular, in contrasts to other works on robust stability of PIDs, we do not use La Salle's principle but provide a strict Lyapunov function. The perturbations that we consider include discontinuous functions of the state, such as Coulomb friction. As corollaries of our main results, one may conclude the same stability property for the case of motion control using linear PID.
The stability of (not necessarily compact) sets for nonlinear systems in cascade is addressed. It is proved that if two sets are globally asymptotically stable (GAS) for the subsystems taken separately then their cross-product is GAS for the corresponding cascade, provided that the solutions of the latter are globally bounded. In the case of a suitable growth rate of the interconnection in the state of the driven subsystem, we show that this latter requirement can be relaxed to just forward completeness of the cascade. Our results extend similar results on the stability analysis of cascaded systems and find applications in partial stability analysis and adaptive control.
In this paper we describe the application of wireless sensor networking techniques to address the realization of a safe and secure decentralized traffic management system. We consider systems of many heterogeneous autonomous vehicles moving in a shared environment. Each vehicle is assumed to have different and possibly unspecified tasks, but they cooperate to avoid collisions. We are interested in designing a scalable architecture capable of accommodating a very large and dynamically changing number of vehicles, guaranteeing their safety (i.e., collision avoidance), the achievement of their goals, and security against potential adversaries. By properly distributing and revoking cryptographic keys we are able to protect communications from an external adversary as well as to detect non-cooperative, possibly malicious vehicles and trigger suitable countermeasures. In our architecture, scalability is obtained by decentralization, i.e. each vehicle is regarded as an autonomous agent capable of processing information concerning its own state and the state of only a fixed, small number of ``neighboring'' agents. Ad-hoc wireless sensor networks are employed to provide support for this architecture.
In this paper we address the problem of generating input plans to steer complex dynamical systems in an obstacle-free environment. Plans considered admit a finite description length and are constructed by words on an alphabet of input symbols, which could be e.g. transmitted through a limited capacity channel to a remote system, where they can be decoded in suitable control actions. We show that, by suitable choice of the control encoding, finite plans can be efficiently built for a wide class of dynamical systems, computing arbitrarily close approximations of a desired equilibrium in polynomial time. Moreover, we illustrate by simulations the power of the proposed method, solving the steering problem for two examples in the class of underactuated systems, which have attracted wide attention in the recent literature.
Research of a modular stabilizing control law for uncertain, nonholonomic mobile systems with actuators limitation has been investigated. Modular design allows the definition of a stabilizing control law for the kinematic model. The presence of uncertainties in the actuators parameters or in the vehicle dynamics has been treated both adding suitable components to the Lyapunov function and using parameters adaptation laws (e.g. adaptive control and backstepping techniques). Simulations are reported for the set point stabilization of a unicycle like vehicle showing the feasibility of the proposed approach. Torque limitations for a unicycle like vehicle has been investigated using backstepping techniques for the vehicle tracking problem. Simulations are reported.
Functional brain exploration methodologies such as functional magnetic resonance imaging (fMRI), are critical tools to study perceptual and cognitive processes. In order to develop complex and well controlled fMRI paradigms, researchers are interested in using active interfaces with electrically powered actuators and sensors. Due to the particularity of the MR environment, safety and compatibility criteria have to be strictly followed in order to avoid risks to the subject under test, to the operators or to the environment, as well as to avoid artifacts in the images. This paper describes the design of an fMRI compatible mechatronic interface based on MR compatibility tests of materials and actuators. In particular, a new statistical test looks at the mean and variations of activity as a time series. The device with two degrees of freedom, allowing one translation with positionfeedback along a horizontal axis and one rotation about a vertical axis linked to the translation, was realized to investigate the brain mechanisms of dynamic tactile perception tasks. It can be used to move and orient various objects below the finger for controlled tactile stimulation. The MR compatibility of the complete interface is shown using the same statistical test as well as a functional study with a human subject.
In this paper we propose an MR (Magnetic Resonance) compatible electrocutaneous stimulator able to inject an electric current, variable in amplitude and frequency, into the fingertips in order to elicit tactile skin receptors (mechanoreceptors). The desired goal is to evoke specific tactile sensations selectively stimulating skin receptors by means of an electric current in place of mechanical stimuli. The field of application ranges from functional Magnetic Resonance Imaging (fMRI) tactile studies to augmented reality technology. The device here proposed is designed using safety criteria in order to comply with the threshold of voltage and current permitted by regulations. Moreover, MR safety and compatibility criteria were considered in order to perform experiments inside the MR scanner during an fMRI acquisition for functional brain activation analysis. Psychophysical laboratory tests are performed in order to define the different evoked tactile sensation. After verifying the device MR safety and compatibility on a phantom, a test on a human subject during fMRI acquisition is performed to visualize the brain areas activated by the simulated tactile sensation.
We address the problem of tracking relative translation in a leader-follower spacecraft formation using feedback from relative position only and under parameter uncertainty (spacecraft mass) and uncertainty in the leader variables (true anomaly rate and rate of change). We only assume boundedness of orbital perturbations and the leader control force but with unknown bounds. Under these conditions we propose a controller that renders the closed-loop system, uniformly semiglobally practically asymptotically stable. In particular, the domain of attraction can be made arbitrarily large by picking convenient gains, and the state errors in the closed-loop system are proved to converge from any initial condition within the domain of attraction to a ball in close vicinity of the origin in a stable way; moreover, this ball can be diminished arbitrarily by increasing the gains in the control law. Simulation results of a leader-follower spacecraft formation using the proposed controller are presented.
A decentralized cooperative collision avoidance control policy for planar vehicle recently proposed is herein considered. Given some simple conditions on initial configurations of agents, the policy is known to ensure safety (i.e., collision avoidance) for an arbitrarily large number of vehicles. The method is highly scalable, and effective solutions can be obtained for several tens of autonomous agents. On the other hand, the liveness property of the policy, i.e. the capability of negotiating a solution in finite time, is not yet completely understood. First a 3D workspace extension is proposed. Furthermore, based on a condition on target configuration previously proposed, some general results on the liveness property are reported. Finally, qualitative evaluations on the strategy and on the proposed target sparsity condition are pointed out.
