Hierarchical Hybrid Systems Research Articles

Hierarchical Fuzzy Signature and Neuro-Fuzzy Hybrid System for QMS Control

Recently, the Quality Management System (QMS) control supports organizations managers identifying the best practices to upgrade the efficiency and effectiveness. This control has become a successful tool to improve the organization decision-making process. However, QMS encloses several performance indicators inputs that necessitate to be managed. In fact, it may include as inputs, customers requirements, quality policies, standard procedures and many other criteria. Hence, to provide the control of QMS problem insurance, two approaches are investigated which are Hierarchical Fuzzy Signature (HFS) and NeuroFuzzy Hierarchical Hybrid system (NFHH), respectively. These approaches are applied in the case of an industrial company operating in the electromechanical sector. This company has to be creative, agile, responsive and especially ready for fierce competition. Then, the obtained results are compared to Adaptive Neural Fuzzy Inference and Neural Network Systems, regarding the learning phase. Consequently, all of them help the company to assess its overall performance. However, NFHH reaches the best accuracy, reduces the number of neurons and uses the parameters that keep the universal approximated property of neural networks and fuzzy systems. Keywords—Quality management system, Fuzzy logic, Neuro-Fuzzy, hierarchical structure, fuzzy signature

Controllable Architecture of Mesoporous Double-Nanoshell SiO2/TiO2 Hollow Tube Based on Layer by Layer Method

Double-shell tubular on-dimensional structure can be fabricated through a layer by layer method, in which the core template was removed to create the tubular shape. In this paper, we report, for the first time, the double nanoshell SiO2/TiO2 hollow tubes prepared through a layer-by-layer deposition method involving the sol-gel process for the SiO2 and TiO2 generation. During TEOS and TEOT hydrolysis/condensation for the SiO2 and TiO2 shell layer formation, cetyltrimethylammonium bromide (CTAB) is adopted both as the structure-directing template and as the mesopore-channel template distributing around the shell. The obtained double-nanoshell hollow tubes illustrate a large surface area and high pore volume. Also, mesoporous double-nanoshell SiO2/TiO2 hollow tubes have the inner and outer shell thickness of about 80 nm and 120 nm, respectively. Plus, the shell thickness of SiO2 and TiO2 is controllable depending on the used concentration of TEOS and TEOT during their sol-gel process. Therefore, the technique for the preparation of SiO2/TiO2 mesoporous double-nanoshell hollow tubes could provide new insights into the construction of mesoporous double-shell and hollow structure for other multicomponent and hierarchical hybrid systems.

A hierarchical hybrid system of integrated longitudinal and lateral control for intelligent vehicles

A hierarchical hybrid control system is proposed to cope with highly automated driving in highway environments with multiple lanes and surrounding vehicles. In the high-level layer, the discrete driving decisions are coordinated by the finite-state machine (FSM) based on the relative position identification and predictive longitudinal distance of the surrounding vehicles. The low-level layer is responsible for the vehicle motion control, where the model predictive control (MPC) approach is utilized to integrate the longitudinal and lateral control mainly including car-following control and lane changing control. The proposed control system focuses on two issues regarding safe driving on highways. On one hand, the subject vehicle must always keep a safe distance with its leading vehicle to avoid the rear-end collision. On the other hand, the subject vehicle should also overtake the preceding vehicle by safe lane changes if the desired speed is not achieved. The effectiveness of the hybrid control is tested in the simulation, whose results verify that the driving decisions are made reasonably and the vehicle motion control obeys stability and comfort requirements. Moreover, it is also indicated by the simulations in random scenarios that the control strategy is able to deal with most of ordinary situations on highways although some emergency situations or critical driving maneuvers of other vehicles are not considered.

On the decidability and complexity of problems for restricted hierarchical hybrid systems

We study variants of a recently introduced hybrid system model, called a Hierarchical Piecewise Constant Derivative (HPCD). These variants (loosely called Restricted HPCDs) form a class of natural models with similarities to many other well known hybrid system models in the literature such as Stopwatch Automata, Rectangular Automata and PCDs. We study the complexity of reachability and mortality problems for variants of RHPCDs and show a variety of results, depending upon the allowed powers. These models form a useful tool for the study of the complexity of such problems for hybrid systems, due to their connections with existing models.We show that the reachability problem and the mortality problem are co-NP-hard for bounded 3-dimensional RHPCDs (3-RHPCDs). Reachability is shown to be in PSPACE, even for n-dimensional RHPCDs. We show that for an unbounded 3-RHPCD, the reachability and mortality problems become undecidable. For a nondeterministic variant of 2-RHPCDs, the reachability problem is shown to be PSPACE-complete.

Honeycombs in honeycombs: complex liquid crystal alumina composite mesostructures.

Small-angle X-ray scattering (SAXS) and atomic force microscopy (AFM) were used to study orientation patterns of two polyphilic liquid crystals (LC) confined to cylindrical pores of anodic aluminum oxide (AAO). The hierarchical hybrid systems had the LC honeycomb (lattice parameter 3.5-4 nm) inside the pores of the AAO honeycomb (diameters 60 and 400 nm). By conducting complete reciprocal space mapping using SAXS, we conclude that the columns of both compounds align in planes normal to the AAO pore axis, with a specific crystallographic direction of the LC lattice aligning strictly parallel to the pore axis. AFM of LC-containing AAO fracture surfaces further revealed that the columns of the planar anchoring LC (compound 1) formed concentric circles in the plane normal to the pore axis near the AAO wall. Toward the pore center, the circles become anisometric "racetrack" loops consisting of two straight segments and two semicircles. This mode compensates for slight ellipticity of the pore cross section. Indications are, however, that for perfectly circular pores, circular shape is maintained right to the center of the pore, the radius coming down to the size of a molecule. For the homeotropically anchoring compound 2, the columns are to the most part straight and parallel to each other, arranged in layers normal to the AAO pore axis, like logs in an ordered pile. Only near the pore wall the columns splay somewhat. In both cases, columns are confined to layers strictly perpendicular to the AAO pore axis, and there is no sign of escape to the third dimension or of axial orientation, the latter having been reported previously for some discotic LCs. The main cause of the two new LC configurations, the "racetrack" and the "logpile", and of their difference from those of confined nematic LC, is the very high splay energy and low bend energy of columnar phases.

World Automata: a compositional approach to model implicit communication in hierarchical Hybrid Systems

We propose an extension of Hybrid I/O Automata (HIOAs) to model agent systems and their implicit communication through perturbation of the environment, like localization of objects or radio signals diffusion and detection. The new object, called World Automaton (WA), is built in such a way to preserve as much as possible of the compositional properties of HIOAs and its underlying theory. From the formal point of view we enrich classical HIOAs with a set of world variables whose values are functions both of time and space. World variables are treated similarly to local variables of HIOAs, except in parallel composition, where the perturbations produced by world variables are summed. In such way, we obtain a structure able to model both agents and environments, thus inducing a hierarchy in the model and leading to the introduction of a new operator. Indeed this operator, called inplacement, is needed to represent the possibility of an object (WA) of living inside another object/environment (WA).

Hybrid Hierarchical System for Identification of Genomic Sequences based on some Recognition Scores

This paper presents a synthesis of researches already published by the author and new research on data analysis related to a hybrid hierarchical system for genomic identification. The methodology of a hierarchical hybrid system for identification of genomic sequences based on some recognition scores is thus completed by the research reported in this paper.

Approximation capabilities of hierarchical hybrid systems

This paper investigates the approximation capabilities of hierarchical hybrid systems, which are motivated by research in hierarchical fuzzy systems, hybrid intelligent systems, and modeling of model partly known systems. For a function (system) with known hierarchical structure (i.e., one that can be represented as a composition of some simpler and lower dimensional subsystems), it is shown that hierarchical hybrid systems have the structure approximation capability in the sense that such a hybrid approximation scheme can approximate both the overall system and all the subsystems to any desired degree of accuracy. For a function (system) with unknown hierarchical structure, Kolmogorov's theorem is used to construct the hierarchical structure of the given function (system). It is then shown that hierarchical hybrid systems are universal approximators

Compositional modeling and refinement for hierarchical hybrid systems

In this paper, we develop a theory of modular design and refinement of hierarchical hybrid systems. In particular, we present compositional trace-based semantics for the language C haron that allows modular specification of interacting hybrid systems. For hierarchical description of the system architecture, C haron supports building complex agents via the operations of instantiation, hiding, and parallel composition. For hierarchical description of the behavior of atomic components, C haron supports building complex modes via the operations of instantiation, scoping, and encapsulation. We develop an observational trace semantics for agents as well as for modes, and define a notion of refinement for both, based on trace inclusion. We show this semantics to be compositional with respect to the constructs in the language.

Probabilistic pursuit-evasion games: theory, implementation, and experimental evaluation

We consider the problem of having a team of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) pursue a second team of evaders while concurrently building a map in an unknown environment. We cast the problem in a probabilistic game theoretical framework, and consider two computationally feasible greedy pursuit policies: local-mar and global-max. To implement this scenario on real UAVs and UGVs, we propose a distributed hierarchical hybrid system architecture which emphasizes the autonomy of each agent, yet allows for coordinated team efforts. We describe the implementation of the architecture on a fleet of UAVs and UGVs, detailing components such as high-level pursuit policy computation, map building and interagent communication, and low-level navigation, sensing, and control. We present both simulation and experimental results of real pursuit-evasion games involving our fleet of UAVs and UGVs, and evaluate the pursuit policies relating expected capture times to the speed and intelligence of the evaders and the sensing capabilities of the pursuers.

Prediction and optimization of a ceramic casting process using a hierarchical hybrid system of neural networks and fuzzy logic

This paper is a case study that describes a hybrid system integrating fuzzy logic, neural networks and algorithmic optimization for use in the ceramics industry. A prediction module estimates two quality metrics of slip-cast pieces through the simultaneous execution of two neural networks. A process improvement algorithm optimizes controllable process settings using the neural network prediction module in the objective function. An expert system module contains a hierarchy of two fuzzy logic rule bases. The rule bases prescribe processing times customized to individual production lines given ambient conditions, mold characteristics and the neural network predictions. This paper demonstrates the applicability of newer computational techniques to a very traditional manufacturing process and the system has been implemented at a major US plant.

Hierarchical hybrid systems: Geometry, controllability and applications to air traffic control *

In this paper the notions of finite analytic partition, dynamical consistency, and partition machines (originally developed in (Wei, 1995; Caines and Wei, 1998) for dynamical systems on differentiate manifolds) is generalized to hybrid systems. The theory is illustrated via a highly simplified air traffic management example which employs new conditions for the global controllability of nonlinear systems (Caines and Lemon, 1998; Lemch and Caines, 1998).