Robust output stabilization: improving performance via supervisory control

We analyze robust stability, in an input-output sense, of switched stable systems. The primary goal (and contribution) of this paper is to design switching strategies to guarantee that input-output stable systems remain so under switching. We propose two types of {\em supervisors}: dwell-time and hysteresis based. While our results are stated as tools of analysis they serve a clear purpose in design: to improve performance. In that respect, we illustrate the utility of our findings by concisely addressing a problem of observer design for Lur'e-type systems; in particular, we design a hybrid observer that ensures ``fast'' convergence with ``low'' overshoots. As a second application of our main results we use hybrid control in the context of synchronization of chaotic oscillators with the goal of reducing control effort; an originality of the hybrid control in this context with respect to other contributions in the area is that it exploits the structure and chaotic behavior (boundedness of solutions) of Lorenz oscillators.Comment: Short version submitted to IEEE TA

Hierarchical hybrid control: A case study

A case study of the difficulties encountered in the design of hierarchical, hybrid control systems is presented. As our example we use the Intelligent Vehicle Highway System (IVHS) architecture proposed for vehicle platooning, a system that involves both continuous state and discrete event controllers. We point out that even though conventional analysis tools suggest that the proposed design should fulfill certain performance requirements, simulation results show that it does not. We consider this as an indication that the conventional tools currently in use for the design and verification of control systems may be inadequate for the design of hierarchical controllers for hybrid systems. The analysis also indicates certain shortcomings of the current IVHS design. We propose solutions to fix these problems

A Map-Reduce Parallel Approach to Automatic Synthesis of Control Software

Many Control Systems are indeed Software Based Control Systems, i.e. control systems whose controller consists of control software running on a microcontroller device. This motivates investigation on Formal Model Based Design approaches for automatic synthesis of control software. Available algorithms and tools (e.g., QKS) may require weeks or even months of computation to synthesize control software for large-size systems. This motivates search for parallel algorithms for control software synthesis. In this paper, we present a Map-Reduce style parallel algorithm for control software synthesis when the controlled system (plant) is modeled as discrete time linear hybrid system. Furthermore we present an MPI-based implementation PQKS of our algorithm. To the best of our knowledge, this is the first parallel approach for control software synthesis. We experimentally show effectiveness of PQKS on two classical control synthesis problems: the inverted pendulum and the multi-input buck DC/DC converter. Experiments show that PQKS efficiency is above 65%. As an example, PQKS requires about 16 hours to complete the synthesis of control software for the pendulum on a cluster with 60 processors, instead of the 25 days needed by the sequential algorithm in QKS.Comment: To be submitted to TACAS 2013. arXiv admin note: substantial text overlap with arXiv:1207.4474, arXiv:1207.409

A formalism for the composition of concurrent robot behaviors

We introduce tools which help one to compose concurrent, hybrid control programs for a class of distributed robotic systems, assuming a palette of controllers for individual tasks is already constructed. These tools, which combine the backchaining of continuous robot behaviors with Petri nets, expand on successful work in sequential composition of robot behaviors. We apply these ideas to the design and verification of a robotic bucket brigade and to simple, distributed assembly tasks as found in automated factories

High-level asynchronous system design using the ACK framework

Journal ArticleDesigning asynchronous circuits is becoming easier as a number of design styles are making the transition from research projects to real, usable tools. However, designing asynchronous "systems" is still a difficult problem. We define asynchronous systems to be medium to large digital systems whose descriptions include both datapath and control, that may involve non-trivial interface requirements, and whose control is too large to be synthesized in one large controller. ACK is a framework for designing high performance asynchronous systems of this type. In ACK we advocate an approach that begins with procedural level descriptions of control and datapath and results in a hybrid system that mixes a variety of hardware implementation styles including burst-mode AFSMs, macromodule circuits, and programmable control. We present our views on what makes asynchronous high level system design different from lower level circuit design, motivate our ACK approach, and demonstrate using an example system design

Evaluation of the Thermodynamic Performance of the Traditional Passive Systems

The need to reduce urban consumption of energy in the buildings, one of the major energy waster resulting in emission of CO2, is pushing research in the field of building design to the appreciation of passive air-conditioning systems that can be integrated with conventional systems and determine, therefore, the so-called hybrid systems. Historically this passive systems were developed in the Mediterranean and in the Middle East area. Actually the research activity has been focused on this problem, through an approach that involves the application of design strategies and the development of computational tools and control systems. The synergy between current scientific knowledge, advanced manufacturing and information technology allows to conceive hybrid systems. Through the use of computer programs CFD (Computational Fluid Dynamic) have been tested different conditions iterating the process until it gets to the structure that gives the greatest contribution for the environmental comfort. The paper shows the results of research developed to the Dipartimento di Architettura of the Università di Palermo, that develops a case study where is analyzed the effect of the natural ventilation in indoor comfort

Adaptive nonlinear control using fuzzy logic and neural networks

The problem of adaptive nonlinear control, i.e. the control of nonlinear dynamic systems with unknown parameters, is considered. Current techniques usually assume that either the control system is linearizable or the type of nonlinearity is known. This results in poor control quality for many practical problems. Moreover, the control system design becomes too complex for a practicing engineer. The objective of this thesis is to provide a practical, systematic approach for solving the problem of identification and control of nonlinear systems with unknown parameters, when the explicit linear parametrization is either unknown or impossible. Fuzzy logic (FL) and neural networks (NNs) have proven to be the tools for universal approximation, and hence are considered. However, FL requires expert knowledge and there is a lack of systematic procedures to design NNs for control. A hybrid technique, called fuzzy logic adaptive network (FLAN), which combines the structure of an FL controller with the learning aspects of the NNs is developed. FLAN is designed such that it is capable of both structure learning and parameter learning. Gradient descent based technique is utilized for the parameter learning in FLAN, and it is tested through a variety of simulated experiments in identification and control of nonlinear systems. The results indicate the success of FLAN in terms of accuracy of estimation, speed of convergence, insensitivity against a range of initial learning rates, robustness against sudden changes in the input as well as noise in the training data. The performance of FLAN is also compared with the techniques based on FL and NNs, as well as several hybrid techniques

Bisimilar control affine systems

The notion of bisimulation plays a very important role in theoretical computer science where it provides several notions of equivalence between models of computation. These equivalences are in turn used to simplify verification and synthesis for these models as well as to enable compositional reasoning. In systems theory, a similar notion is also of interest in order to develop modular verification and design tools for purely continuous or hybrid control systems. In this paper, we introduce two notions of bisimulation for nonlinear systems. We present differential-algebraic characterizations of these notions and show that bisimilar systems of different dimensions are obtained by factoring out certain invariant distributions. Furthermore, we also show that all bisimilar systems of different dimension are of this form