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Symbolic control is an abstraction-based controller synthesis approach that provides, algorithmically, certifiable-by-construction controllers for cyber-physical systems. Symbolic control approaches usually assume that full-state information is available which is not suitable for many real-world applications with partially-observable states or output information. This article introduces a framework for output-feedback symbolic control. We propose relations between original systems and their symbolic models based on outputs. They enable designing symbolic controllers and refining them to enforce complex requirements on original systems. We provide example methodologies to synthesize and refine output-feedback symbolic controllers.

In this paper, we propose a software tool, called AMYTISS, implemented in C++/OpenCL, for designing correct-by-construction controllers for large-scale discrete-time stochastic systems. This tool is employed to (i) build finite Markov decision processes (MDPs) as finite abstractions of given original systems, and (ii) synthesize controllers for the constructed finite MDPs satisfying bounded-time high-level properties including safety, reachability and reach-avoid specifications. In AMYTISS, scalable parallel algorithms are designed such that they support the parallel execution within CPUs, GPUs and hardware accelerators (HWAs). Unlike all existing tools for stochastic systems, AMYTISS can utilize high-performance computing (HPC) platforms and cloud-computing services to mitigate the effects of the state-explosion problem, which is always present in analyzing large-scale stochastic systems. We benchmark AMYTISS against the most recent tools in the literature using several physical case studies including robot examples, room temperature and road traffic networks. We also apply our algorithms to a 3-dimensional autonomous vehicle and 7-dimensional nonlinear model of a BMW 320i car by synthesizing an autonomous parking controller., Comment: This work is accepted at the 32nd International Conference on Computer-Aided Verification (CAV) as a tool paper

Reachability analysis is a critical tool for the formal verification of dynamical systems and the synthesis of controllers for them. Due to their computational complexity, many reachability analysis methods are restricted to systems with relatively small dimensions. One significant reason for such limitation is that those approaches, and their implementations, are not designed to leverage parallelism. They use algorithms that are designed to run serially within one compute unit and they can not utilize widely-available high-performance computing (HPC) platforms such as many-core CPUs, GPUs and Cloud-computing services. This paper presents PIRK, a tool to efficiently compute reachable sets for general nonlinear systems of extremely high dimensions. PIRK has been tested on several systems, with state dimensions ranging from ten up to 4 billion. The scalability of PIRK's parallel implementations is found to be highly favorable., Comment: 20 pages, 3 figures, 2 tables. Extended version of a submission to CAV 2020

While many studies and tools target the basic stabilizability problem of networked control systems (NCS), nowadays modern systems require more sophisticated objectives such as those expressed as formulae in linear temporal logic or as automata on infinite strings. One general technique to achieve this is based on so-called symbolic models, where complex systems are approximated by finite abstractions, and then, correct-by-construction controllers are automatically synthesized for them. We present tool SENSE for the construction of finite abstractions for NCS and the automated synthesis of controllers. Constructed controllers enforce complex specifications over plants in NCS by taking into account several non-idealities of the communication channels. Given a symbolic model of the plant and network parameters, SENSE can efficiently construct a symbolic model of the NCS, by employing operations on binary decision diagrams (BDDs). Then, it synthesizes symbolic controllers satisfying a class of specifications. It has interfaces for the simulation and the visualization of the resulting closed-loop systems using OMNETPP and MATLAB. Additionally, SENSE can generate ready-to-implement VHDL/Verilog or C/C++ codes from the synthesized controllers., Comment: In Proceedings MeTRiD 2018, arXiv:1806.09330

Spoken Language Translation (SLT) is becoming more widely used and becoming a communication tool that helps in crossing language barriers. One of the challenges of SLT is the translation from a language without gender agreement to a language with gender agreement such as English to Arabic. In this paper, we introduce an approach to tackle such limitation by enabling a Neural Machine Translation system to produce gender-aware translation. We show that NMT system can model the speaker/listener gender information to produce gender-aware translation. We propose a method to generate data used in adapting a NMT system to produce gender-aware. The proposed approach can achieve significant improvement of the translation quality by 2 BLEU points., Comment: Proceedings of the Second International Conference on Natural Language and Speech Processing, 2018 IEEE

The last decade has witnessed significant attention on networked control systems (NCS) due to their ubiquitous presence in industrial applications, and, in the particular case of wireless NCS, because of their architectural flexibility and low installation and maintenance costs. In wireless NCS the communication between sensors, controllers, and actuators is supported by a communication channel that is likely to introduce variable communication delays, packet losses, limited bandwidth, and other practical non-idealities leading to numerous technical challenges. Although stability properties of NCS have been investigated extensively in the literature, results for NCS under more complex and general objectives, and in particular results dealing with verification or controller synthesis for logical specifications, are much more limited. This work investigates how to address such complex objectives by constructively deriving symbolic models of NCS, while encompassing the mentioned network non-idealities. The obtained abstracted (symbolic) models can then be employed to synthesize hybrid controllers enforcing rich logical specifications over the concrete NCS models. Examples of such general specifications include properties expressed as formulae in linear temporal logic (LTL) or as automata on infinite strings. We thus provide a general synthesis framework that can be flexibly adapted to a number of NCS setups. We illustrate the effectiveness of the results over some case studies., Comment: 22 pages, 8 figures, 1 table