Spectra: a specification language for reactive systems

We introduce Spectra, a new specification language for reactive systems, specifically tailored for the context of reactive synthesis. The meaning of Spectra is defined by a translation to a kernel language. Spectra comes with the Spectra Tools, a set of analyses, including a synthesizer to obtain a correct-by-construction implementation, several means for executing the resulting controller, and additional analyses aimed at helping engineers write higher-quality specifications. We present the language in detail and give an overview of its tool set. Together with the language and its tool set, we present four collections of many, non-trivial, large specifications, written by undergraduate computer science students for the development of autonomous Lego robots and additional example reactive systems. The collected specifications can serve as benchmarks for future studies on reactive synthesis. We present the specifications, with observations and lessons learned about the potential use of reactive synthesis by software engineers.

     

A specialized on-the-fly algorithm for lexicon and language model composition

This paper presents an algorithm for the composition of weighted finite-state transducers which is specially tailored to speech recognition applications: it composes the lexicon with the language model while simultaneously optimizing the resulting transducer. Furthermore, it performs these computations "on-the-fly" to allow easier management of the tradeoff between offline and online computation and memory. The algorithm is exact for local knowledge integration and optimization operations such as composition and determinization. Minimization and pushing operations are approximated. Our results have confirmed the efficiency of these approximations.     

Case-based reactive navigation: a method for on-line selection andadaptation of reactive robotic control parameters

We present a new line of research investigating on-line adaptive reactive control mechanisms for autonomous intelligent agents. We discuss a case-based method for dynamic selection and modification of behavior assemblages for a navigational system. The case-based reasoning module is designed as an addition to a traditional reactive control system, and provides more flexible performance in novel environments without extensive high level reasoning that would otherwise slow the system down. The method is implemented in the ACBARR (case-based reactive robotic) system and evaluated through empirical simulation of the system on several different environments, including "box canyon" environments known to be problematic for reactive control systems in general.     

Supervisory control and reactive synthesis: a comparative introduction

This paper presents an introduction to and a formal connection between synthesis problems for discrete event systems that have been considered, largely separately, in the two research communities of supervisory control in control engineering and reactive synthesis in computer science. By making this connection mathematically precise in a paper that attempts to be as self-contained as possible, we wish to introduce these two research areas to non-expert readers and at the same time to highlight how they can be bridged in the context of classical synthesis problems. After presenting general introductions to supervisory control theory and reactive synthesis, we provide a novel reduction of the basic supervisory control problem, non-blocking case, to a problem of reactive synthesis with plants and with a maximal permissiveness requirement. The reduction is for fully-observed systems that are controlled by a single supervisor/controller. It complements prior work that has explored problems at the interface of supervisory control and reactive synthesis. The formal bridge constructed in this paper should be a source of inspiration for new lines of investigation that will leverage the power of the synthesis techniques that have been developed in these two areas.     

Integrating discrete controller synthesis into a reactive programming language compiler

We define a mixed imperative/declarative programming language: declarative contracts are enforced upon imperatively described behaviors. This paper describes the semantics of the language, making use of the notion of Discrete Controller Synthesis (DCS). We target the application domain of adaptive and reconfigurable systems: our language can serve programming closed-loop adaptation controllers, enabling flexible execution of functionalities w.r.t. changing resource and environment conditions. DCS is integrated into a1 programming language compiler, which facilitates its use by users and programmers, performing executable code generation. The tool is concretely built upon the basis of a reactive programming language compiler, where the nodes describe behaviors that can be modeled in terms of transition systems. Our compiler integrates this with a DCS tool, making it a new environment for formal methods. We define the trace semantics of our contracts language, describe its compilation and establish its correctness, and discuss implementation and examples.     

A*: a language for implementing language processors

A* is an experimental language designed to facilitate the creation of language-processing tools. It is analogous either to an interpreted yacc with Awk as its statement language, or to a version of Awk which processes programs rather than records. A* offers two principal advantages over the combination of lex, yacc, and C: a high-level interpreted base language and built-in parse tree construction. A* programmers are thus able to accomplish many useful tasks with little code. This paper describes the motivation for A*, its design, and its evolution. Experience with A* is described, and then the paper concludes with an analysis of that experience     

Pumping lemmas for the control language hierarchy

We investigate a progression of grammatically defined language families, thecontrol language hierarchy. This hierarchy has been studied recently from the perspective of providing a linguistic framework for natural language syntax. We exhibit a progression of pumping lemmas, one for each family in the hierarchy, thereby showing that the hierarchy is strictly separable.The research reported in this paper was conducted in part at the Department of Computer and Information Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA, and was supported under ARO Grant DAA29-84-9-0027, NSF Grants MCS-8219116-CER, MCS-82-07294, DCR-84-10413 and MCS-83-05221, and DARPA Grant N00014-85-K-0018.     

A fussy-logic control language for embedded controllers

Microcontrollers are being used in many commercial and consumer products to introduce a higher level of intelligence. There exist an opportunity and need to develop high-level languages to be used specifically in industrial product development. A recent trend in such embedded applications is the use of fuzzy-logic control. An ongoing project in the Industrial Research Laboratory at the University of Florida investigates the various aspects of microcontroller architectures, operating systems and languages. This report summarizes our progress in developing a fuzzy-logic control language for microcontrollers.     

State estimation and inferential control for a reactive batch distillation column

An optimal reflux ratio profile is obtained for a reactive batch distillation system utilizing the capacity factor as the objective function in a nonlinear optimization problem. Then, an Artificial Neural Network (ANN) estimator system, which utilizes the use of several ANN estimators, is designed to predict the product composition values of the distillation column from temperature measurements inferentially. The network used is an Elman network with two hidden layers. The designed estimator system is used in the feedback inferential control algorithm, where the estimated compositions and the reflux ratio information are given as inputs to the controller to see the performance of the ANN. In the control law, a scheduling policy is used and the optimal reflux ratio profile is considered as pre-defined set-points. It is found that, it is possible to control the compositions in this dynamically complex system by using the designed ANN estimator system with error refinement whenever necessary.     

Two-point control of a reactive distillation column for composition and conversion

Reactive distillation is a hybrid process with dual process objectives: reactant conversion and product composition. Control schemes for reactive distillation frequently neglect the effect of the principal operating parameters on the reactant conversion, and this has a detrimental effect on the overall process profitability. An ETBE reactive distillation column has been used as a case study to show how a two-point control configuration, which recognises the importance of both composition and conversion, can be developed and implemented for a reactive distillation process. The combined composition and conversion control configuration was tested using SpeedUp dynamic simulations and proved to be effective in maintaining a high isobutylene conversion despite process disturbances. The two-point control scheme also had superior disturbance rejection capability, especially for feed rate changes, and composition set-point sensitivity compared with a one-point control scheme.     

ORCA-FMS: a dynamic architecture for the optimized and reactive control of flexible manufacturing scheduling

Reactive and effective hybrid manufacturing control architectures, combining hierarchy and heterarchy adapted to the current constraints of the industrial market and its environment were created. In this article, a new generic hybrid control architecture called ORCA (dynamic Architecture for an Optimized and Reactive Control) is first proposed. This hybrid architecture is able to dynamically and partially switch between a hierarchical predictive architecture and a heterarchical reactive architecture, if an event forbidding the planned behavior to be followed occurs. In this article, this architecture was applied to a Flexible Manufacturing System (FMS) problem and denoted ORCA-FMS. ORCA-FMS was tested on an existing manufacturing cell with simulations and real experiments to prove the applicability and the effectiveness of this kind of hybrid architecture in an industrial environment.     

Hybrid deliberative/reactive control of a scanning system for landmine detection

Antipersonnel mines infest fields all over the world. According to recent estimates, landmines are killing and maiming more than 2000 innocent civilians per month. The problem of landmine detection and removal requires the cooperation of a number of engineering fields, which in turn poses a need for new technologies, such as improved sensors, efficient manipulators and mobile robots. This paper describes the configuration and control architecture of a scanning manipulator for detecting antipersonnel landmines. The scanning system is part of a demining system based on a walking robot that acts as the carrier for the scanning manipulator. Broadly speaking, the scanning system consists of a sensor head that can detect certain kinds of landmines and, to move the sensor head over large areas, a manipulator that has been appropriately sensorized to scan irregular terrains in the presence of obstacles. The proposed control architecture is of the hybrid deliberative/reactive type: A deliberative controller defines a sweep trajectory that furnishes complete coverage of the infested area, while two reactive controllers are involved in on-line adaptation to the environment. Experiments show good performance of the whole system.     

Incremental supervised learning for mobile robot reactive control

Reactive control for a mobile robot can be defined as a mapping from a perceptual space to a command space. This mapping can be hard-coded by the user (potential fields, fuzzy logic), and can also be learnt. This paper is concerned with supervised learning for perception to action mapping for a mobile robot. Among the existing neural approaches for supervised learning of a function, we have selected the grow and learn network for its properties adapted to robotic problems: incrementality and flexible structure. We will present the results we have obtained with this network using first raw sensor data and then pre-processed measures with the automatic construction of virtual sensors.     

A reactive extension of the OpenMusic visual programming language

Objectives: OpenMusic (OM) is a domain-specific visual programming language designed for computer-aided music composition. This language based on Common Lisp allows composers to develop functional processes generating or transforming musical data, and to execute them locally by demand-driven evaluations. As most historical computer-aided composition environments, OM relies on a transformational declarative paradigm, which is hard to conciliate with reactive data-flow (an evaluation scheme more adequate to the development of interactive systems). We propose to link these two evaluation paradigms in the same and consistent visual programming framework.Methods: We establish a denotational semantics of the visual language, which gives account for its demand-driven evaluation mechanism and the incremental construction of programs. We then extend this semantics to enable reactive computations in the functional graphs.Results: The resulting language merges data-driven executions with the existing demand-driven mechanism. A conservative implementation is proposed.Conclusions: We show that the incremental construction of programs and their data-driven and demand-driven evaluations can be smoothly integrated in the visual programming workflow. This integration allows for the propagation of changes in the programs, and the evaluation of graphically designed functional expressions as a response to external events, a first step in bridging the gap between computer-assisted composition environments and real-time musical systems.     

Nonlinear model predictive control of a reactive distillation column

This paper considers the application of nonlinear model predictive control (NLMPC) to a highly nonlinear reactive distillation column. NLMPC was applied as a nonlinear programming problem using orthogonal collocation on finite elements to approximate the ODEs that constitute the model equations for the reactive distillation column. Diagonal PI controls were used to identify that the [L/D,V] and the [L/D,V/B] configurations performed best. NLMPC was applied using the [L/D,V] configuration and found to provide a factor of 2–3 better performance than the corresponding PI controller. The effect of process/model mismatch on the performance of the NLMPC controller was also evaluated.