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Convex Analysisの二,三の進展について

We introduce flat systems, which are equivalent to linear ones via a special type of feedback called endogenous. Their physical properties are subsumed by a linearizing output and they might be regarded as providing another nonlinear extension of Kalman's controllability. The distance to flatness is measured by a non-negative integer, the defect. We utilize differential algebra where flatness- and defect are best defined without distinguishing between input, state, output and other variables. Many realistic classes of examples are flat. We treat two popular ones: the crane and the car with n trailers, the motion planning of which is obtained via elementary properties of plane curves. The three non-flat examples, the simple, double and variable length pendulums, are borrowed from non-linear physics. A high frequency control strategy is proposed such that the averaged systems become flat.

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Flatness and defect of non-linear systems: introductory theory and examples

ing WS1S Systems to Verify Parameterized Networks . . . . . . . . . . . . 188 Kai Baukus, Saddek Bensalem, Yassine Lakhnech and Karsten Stahl FMona: A Tool for Expressing Validation Techniques over Infinite State Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 J.-P. Bodeveix and M. Filali Transitive Closures of Regular Relations for Verifying Infinite-State Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 Bengt Jonsson and Marcus Nilsson Diagnostic and Test Generation Using Static Analysis to Improve Automatic Test Generation . . . . . . . . . . . . . 235 Marius Bozga, Jean-Claude Fernandez and Lucian Ghirvu Efficient Diagnostic Generation for Boolean Equation Systems . . . . . . . . . . . . 251 Radu Mateescu Efficient Model-Checking Compositional State Space Generation with Partial Order Reductions for Asynchronous Communicating Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 Jean-Pierre Krimm and Laurent Mounier Checking for CFFD-Preorder with Tester Processes . . . . . . . . . . . . . . . . . . . . . . . 283 Juhana Helovuo and Antti Valmari Fair Bisimulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299 Thomas A. Henzinger and Sriram K. Rajamani Integrating Low Level Symmetries into Reachability Analysis . . . . . . . . . . . . . 315 Karsten Schmidt Model-Checking Tools Model Checking Support for the ASM High-Level Language . . . . . . . . . . . . . . 331 Giuseppe Del Castillo and Kirsten Winter Table of

Tools and Algorithms for the Construction and Analysis of Systems. Proc. TACAS 2009

The problem of controlling a fixed nonlinear plant in order to have its output track (or reject) a family of reference (or disturbance) signal produced by some external generator is discussed. It is shown that, under standard assumptions, this problem is solvable if and only if a certain nonlinear partial differential equation is solvable. Once a solution of this equation is available, a feedback law which solves the problem can easily be constructed. The theory developed incorporates previously published results established for linear systems. >

Output regulation of nonlinear systems

Model Predictive Control (MPC), the dominant advanced control approach in industry over the past twenty-five years, is presented comprehensively in this unique book. With a simple, unified approach, and with attention to real-time implementation, it covers predictive control theory including the stability, feasibility, and robustness of MPC controllers. The theory of explicit MPC, where the nonlinear optimal feedback controller can be calculated efficiently, is presented in the context of linear systems with linear constraints, switched linear systems, and, more generally, linear hybrid systems. Drawing upon years of practical experience and using numerous examples and illustrative applications, the authors discuss the techniques required to design predictive control laws, including algorithms for polyhedral manipulations, mathematical and multiparametric programming and how to validate the theoretical properties and to implement predictive control policies. The most important algorithms feature in an accompanying free online MATLAB toolbox, which allows easy access to sample solutions. Predictive Control for Linear and Hybrid Systems is an ideal reference for graduate, postgraduate and advanced control practitioners interested in theory and/or implementation aspects of predictive control.

Predictive Control for Linear and Hybrid Systems

Observability and diagnosability properties of a hybrid dynamical system are essential in characterizing the possibility of identifying the system’s hybrid state, and in particular the occurrence of some specific states that may correspond to a malfunctioning of the system due to a fault or an attack. Diagnosability has been extensively studied for Finite State Machines (FSMs). However, the results obtained for FSMs cannot, in general, be applied directly to hybrid systems where the discrete evolution interacts with the continuous one. In this chapter, we propose a formal definition of diagnosability for hybrid systems. Furthermore, motivated by the great importance of security issues for hybrid systems, we characterize the diagnosability property in the more general case where the available information may be corrupted by an external attacker. Finally, we establish sufficient conditions for a hybrid system to be diagnosable.

Secure Diagnosability of Hybrid Dynamical Systems

In this paper a microscopic hybrid automaton for Adaptive Cruise Control (ACC) exhibiting psycho-physical human characteristics is introduced. The objective is to let the ACC mimic the human behavior to improve passenger experience, while assuring classical ACC properties. The human-inspired automaton is combined with a predictive control strategy in order to meet physical and safety constraints, as well as fuel minimization. An optimization problem is then formulated according to efficiency and constraints satisfaction. A receding horizon approach is implemented to solve the problem. Simulations are performed in order to validate the control law and to show the efficacy of the proposed approach.

A Microscopic Human-Inspired Adaptive Cruise Control for Eco-Driving

A design methodology is presented for dynamical observers of hybrid systems with linear continuous-time dynamics that reconstruct the complete state (discrete location and continuous state) from the knowledge of the inputs and outputs of a hybrid plant. Given a current-location observable living hybrid system with minimum dwell-time, we prove that exponential ultimate boundedness for an hybrid observer can always be achieved. We also prove that the observer correctly identifies (apart from an initial finite number of transitions) the sequence of hybrid system locations even when the complementary outputs are generated with some delay with respect to the corresponding transitions in the plant.We then present the application of the theory to the problem of on–line identification of the actual engaged gear for a car, an important contribution. The relevance of this problem is related to engine control strategies achieving high performance and efficient emissions control which depend critically on the knowledge of the engaged gear. The performance of the observer was tested with (real and not simulated) experimental data obtained in Magneti Marelli Powertrain using an Opel Astra equipped with a Diesel engine and a robotized gearbox SeleSpeed.

The Design of dynamical observers for hybrid systems: Theory and Application to an Automotive Control Problem

Time-delay systems are an important class of dynamical systems that provide a solid mathematical framework to deal with many application domains of interest In this paper we focus on nonlinear control systems with unknown and time-varying delay signals and we propose one approach to the control design of such systems, which is based on the construction of symbolic models Symbolic models are abstract descriptions of dynamical systems where one symbolic state and one symbolic input correspond to an aggregate of states and an aggregate of inputs We first introduce the notion of incremental input-delay-to-state stability and characterize it by means of Lyapunov-Krasovskii functionals We then derive sufficient conditions for the existence of symbolic models that are shown to be alternating approximately bisimilar to the original system Further results are also derived which prove the computability of the proposed symbolic models in a finite number of steps

Maria Domenica Di Benedetto

Papers

Secure Diagnosability of Hybrid Dynamical Systems

A Microscopic Human-Inspired Adaptive Cruise Control for Eco-Driving

The Design of dynamical observers for hybrid systems: Theory and Application to an Automotive Control Problem

Symbolic Models for Nonlinear Time-Varying Time-Delay Systems via Alternating Approximate Bisimulation

Stabilizability based state space reductions for hybrid systems