Predictive control,embedded cyberphysical systems and systems of systems – A perspective

Today’s world is changing rapidly due to advancements in information technology, computation and communication. Actuation, communication, sensing, and control are becoming ubiquitous. These technological advancements have led to the widespread availability of information and the possibility to connect systems in unforeseen manner. There is a strong desire for smart(er) cities, buildings, devices, factories, health monitoring – a smarter world. However, designing such a smarter world requires addressing also many challenges resulting from the emerging complex interactions and interoperation of systems. How is it possible to handle the increasing complexity during design and maintenance of such systems? How can one guarantee safety and performance of systems operating over networks which are subject to erroneous communication, delays, and failures of sensors and actuators? Is it possible to design control systems which allow for easy reconfiguration or even self-organization, for example by letting subsystems join and leave larger systems via plug and play strategies? Can one guarantee privacy of the controlled subsystems while exchanging information, which is necessary for maintaining overall system performance? We believe that predictive control is a well suited control approach to tackle some of these challenges due to its flexibility with respect to the formulation of the problem and the possibility to directly take constraints, preview information, as well as models of different complexity of the physical world into account. In this perspective we limit our attention to three areas we believe predictive control methods can provide a basis to tackle the appearing challenges: the efficient and easy implementation of predictive control on omnipresent embedded computation hardware, the question of resource and network aware control, as well as control on the network level of systems of systems. We briefly summarize results from these fields and outline some ideas on challenges, which arise.     

Neural networks in mechanics of structures and materials – new results and prospects of applications

Basic ideas of back-propagation neural networks (BPNNs) are presented in short. Then BPNN applications in analysis of the following problems are discussed: (1) bending analysis of elastoplastic beams, (2) elastoplastic plane stress problem, (3) estimation of fundamental vibration periods of real buildings, (4) detection of damage in a steel beam, (5) identification of loads applied to an elastoplastic beam. Regularization neural network is briefly discussed and its application to estimation of concrete fatigue durability it shown. A modified Hopfield network is used to the analysis of an elastic angular plate with unilateral constraints. In the end some conclusions and prospects of neurocomputing applications are pointed out.     

Analysis and control of general logical networks – An algebraic approach

Since Boolean network is a powerful tool in describing the genetic regulatory networks, accompanying the development of systems biology, the analysis and control of Boolean networks have attracted much attention from biologists, physicists, and systems scientists. From mathematical point of view, the dynamics of a Boolean (control) network is a discrete-time logical dynamic process. This paper surveys a recently developed technique, called the algebraic approach, based on semi-tensor product. The new technique can deal with not only Boolean networks, which allow each node to take two values, but also k-valued networks, which allow each node to take k different values, and mix-valued networks, which allow nodes to take different numbers of values.The paper provides a comprehensive introduction to the new technique, including (1) mathematical background of this new technique – semi-tensor product of matrices and the matrix expression of logic; (2) dynamic models of Boolean networks, and general (multi- or mix-valued) logical networks; (3) the topological structure of Boolean networks and general networks; (4) the basic control problems of Boolean/general control networks, which include the controllability, observability, realization, stability and stabilization, disturbance decoupling, identification and optimization, etc.; (5) some other related applications.     

Hybrid systems of differential-algebraic equations – Analysis and numerical solution

We consider hybrid systems of differential-algebraic equations and present a general framework for general nonlinear over- and underdetermined hybrid systems that allows the analysis of existence and uniqueness and the application of index reduction methods for hybrid differential-algebraic systems. A particular difficulty in the numerical simulation of hybrid systems is (numerical) chattering, i.e., fast oscillations between modes of operations. A regularization technique using sliding modes allows us to regularize the system behavior in the case of chattering. Further, we show how chattering behavior during the numerical solution can be prevented using sliding mode simulation. The advantage of the sliding mode simulation is illustrated by numerical examples.     

Scalable mpNoC for massively parallel systems – Design and implementation on FPGA

The high chip-level integration enables the implementation of large-scale parallel processing architectures with 64 and more processing nodes on a single chip or on an FPGA device. These parallel systems require a cost-effective yet high-performance interconnection scheme to provide the needed communications between processors. The massively parallel Network on Chip (mpNoC) was proposed to address the demand for parallel irregular communications for massively parallel processing System on Chip (mppSoC). Targeting FPGA-based design, an efficient mpNoC low level RTL implementation is proposed taking into account design constraints. The proposed network is designed as an FPGA based Intellectual Property (IP) able to be configured in different communication modes. It can communicate between processors and also perform parallel I/O data transfer which is clearly a key issue in an SIMD system. The mpNoC RTL implementation presents good performances in terms of area, throughput and power consumption which are important metrics targeting an on chip implementation. mpNoC is a flexible architecture that is suitable for use in FPGA-based parallel systems. This paper introduces the basic mppSoC architecture. It mainly focuses on the mpNoC flexible IP based design and its implementation on FPGA. The integration of mpNoC in mppSoC is also described. Implementation results on a Stratix II FPGA device are given for three data-parallel applications ran on mppSoC. The obtained good performances justify the effectiveness of the proposed parallel network. It is shown that the mpNoC is a lightweight parallel network making it suitable for both small as well as large FPGA-based parallel systems.     

SFDIA of consecutive sensor faults using neural networks – demonstrated on a UAV

Neural network based sensor fault detection, isolation and accommodation (NN-SFDIA) is becoming a popular alternative to traditional linear time-invariant model-based sensor fault detection, isolation and accommodation (SFDIA) schemes, such as observer-based methods. Their online training capabilities and ability to model complex nonlinear systems have attracted much research interest in the applications area of neural networks. In this article, we design an NN-SFDIA scheme to detect multiple sensor faults in an unmanned air vehicle (UAV). Model-based SFDIA is a direction of development in particular with UAVs where sensor redundancy may not be an option due to weight, cost and space implications. In this article, a maximum of three consecutive faults are assumed in the pitch gyro, normal accelerometer and angle of attack sensor of a nonlinear UAV model. Furthermore, a novel residual generator which is designed to minimise the false alarm rates and missed faults, is implemented. After 33 separate SFDIA tests implemented on a 1.6?GHz Pentium processor, the NN-SFDIA scheme detected all but three faults with a fast execution time of 0.55?ms per flight data sample.     

Stabilization of multiple independent linear systems with control networks

The problem of stabilizing multiple independent linear systems sharing one conmmon network cable is presented and solved. Both the quanfization and time sequencing are studied in the field of control over networks by providing the formulated stabilizing sufficient condition which illustrates the relationship between the system instability, quanfization and time sequencing, and the data rate is also presented in temps of the quanfization and time sequencing. A numerical example is given to illustrate the result.     

Bond graph modelling and simulation of multidisciplinary systems – An introduction

This paper introduces a graphical, computer aided modelling methodology that is particularly suited for the concurrent design of multidisciplinary systems, viz. of engineering systems with mechanical, electrical, hydraulic or pneumatic components, including interactions of physical effects from various energy domains.Following the introduction, bond graph modelling of multibody systems, as an example of an advanced topic, is briefly addressed in order to demonstrate the potential of this powerful approach to modelling multidisciplinary systems. It is shown how models of multibody systems including flexible bodies can be built in a systematic manner.     

Solution of non-linear optimization problems in power systems†

The application of differential dynamic programming or hybrid quasilinearization technique to the solution of non-linear optimization problems in power systems has encountered the problem of computational instability, particularly in higher order systems. This paper describes the application of a continuation procedure to alleviate this difficulty. Sixth order non-linear systems have been optimized with and without constraints on control variables. Both open-loop and, for the first time, closed-loop systems including both exciter and governor dynamics, are analysed. The studies presented show that this technique is quite effective in obtaining accurate solutions for non-linear boundary-value-problems in power systems.     

Operators׳ adaptation to imperfect automation – Impact of miss-prone alarm systems on attention allocation and performance

Operators in complex environments are often supported by alarm systems that indicate when to shift attention to certain tasks. As alarms are not perfectly reliable, operators have to select appropriate strategies of attention allocation to compensate for unreliability and to maintain overall performance. This study explores how humans adapt to differing alarm reliabilities. Within a multi-task simulation consisting of a monitoring task and two other concurrent tasks, participants were assigned to one of five groups. In the manual control group none of the tasks was supported by an alarm system, whereas the four experimental groups were supported in the monitoring task by a miss-prone alarm system differing in reliability, i.e. 68.75%, 75%, 87.5%, 93.75%. Compared to the manual control group, all experimental groups benefited from the support by alarms, with best performance for the highest reliability condition. However, for the lowest reliability group the benefit was associated with an increased attentional effort, a more demanding attention allocation strategy, and a declined relative performance in a concurrent task. Results are discussed in the context of recent automation research.     

Pinning dynamic systems of networks with Markovian switching couplings and controller–node set

In this paper, we study pinning control problem of coupled dynamical systems with stochastically switching couplings and stochastically selected controller–node set. Here, the coupling matrices and the controller–node sets change with time, induced by a continuous-time Markov chain. By constructing Lyapunov functions, we establish tractable sufficient conditions for exponential stability of the coupled system. Two scenarios are considered here. First, we prove that if each subsystem in the switching system, i.e. with the fixed coupling, can be stabilized by the fixed pinning controller–node set, and in addition, the Markovian switching is sufficiently slow, then the time-varying dynamical system is stabilized. Second, we conclude that if the system with the average coupling and pinning gains can be stabilized and the switching is sufficiently fast, the time-varying system is stabilized. Two numerical examples are provided to demonstrate the validity of these theoretical results, including a switching dynamical system between several stable subsystems, and a dynamical system with mobile nodes and spatial pinning control towards the nodes when these nodes are being in a pre-designed region.     

Synchronization in complex networks and its application – A survey of recent advances and challenges

Complex networks have, in recent years, brought many innovative impacts to large-scale systems. However, great challenges also come forth due to distinct complex situations and imperative requirements in human life nowadays. This paper attempts to present an overview of recent progress of synchronization of complex dynamical networks and its applications. We focus on robustness of synchronization, controllability and observability of complex networks and synchronization of multiplex networks. Then, we review several applications of synchronization in complex networks, especially in neuroscience and power grids. The present limitations are summarized and future trends are explored and tentatively highlighted.     

The changes on synchronizing ability of coupled networks from ring networks to chain networks

In this paper, two different ring networks with unidirectional couplings and with bidirectional couplings were discussed by theoretical analysis. It was found that the effects on synchronizing ability of the two different structures by cutting a link are completely opposite. The synchronizing ability will decrease if the change is from bidirectional ring to bidirectional chain. Moreover, the change on synchro- nizing ability will be four times if the number of N is large enough. However, it will increase obviously from unidirectional ring to unidirectional chain. It will be N 2/(2π2) times if the number of N is large enough. The numerical simulations confirm the conclusion in quality. This paper also discusses the effects on synchronization by adding one link with different length d to these two different structures. It can be seen that the effects are different. Theoretical results are accordant to numerical simulations. Synchronization is an essential physics problem. These results pro- posed in this paper have some important reference meanings on the real world networks, such as the bioecological system networks, the designing of the circuit, etc.     

Boundary variational ‘principles’ for inequality structural analysis problems and numerical applications

The aim of the present paper is the derivation of boundary variational ‘principles’ for inequality problems i.e. for problems having as variational formulations variational or hemivariational inequalities. Using first the principles of minimum potential and complementary energy we derive first saddle point formulations for the problems using appropriate Lagrangians. Then we eliminate by an appropriate elimination technique the internal degrees of freedom and we obtain two minimum ‘principles’ having as unknowns the normal displacements and reactions of the boundary region respectively. Analogously we treat the case of hemivariational inequalities. The theory is applied to the inclusion and inhomogeneity problem and is illustrated by numerical examples solved both by the F.E.M. and the B.E.M.     

Top-down development of layered fault tolerant systems and its problems — a deontic perspective

Although the top-down development paradigm has successfully been applied to master the complexity of large systems, it has not yet been accepted as a useful paradigm for fault tolerant system design. This is mainly due to a problem that is sometimes referred to as the lazy programmers paradox. The lazy programmer paradox was already present and solved in top-down development methods for non-critical systems. However, the problem has re-appeared in an even more serious variant for critical systems. A few toy examples concerning exception handling in an Ada-like language are used to explain and illustrate the paradox. One possible solution to the problem is to use a specification language in which one can express that certain behaviours of a system are preferred over others. This paper proposes deontic logic as such a specification language. Therefore, a short and rather informal introduction to deontic logic is included. A non-trivial example is included to illustrate how deontic logic can be used to solve the lazy programmer paradox.Supported by NWO/SION Project 612-316-022: Fault Tolerance: Paradigms, Models, Logics, Construction.     

Analytical modeling of interconnection networks in heterogeneous multi-cluster systems

The study of interconnection networks is important because the overall performance of a distributed system is often critically hinged on the effectiveness of its interconnection network. This paper addresses the problem of interconnection networks performance modeling of large-scale distributed systems with emphases on heterogeneous multi-cluster computing systems. We present an analytical model to predict message latency in multi-cluster systems in the presence of node, network and system organization heterogeneity. The model is validated through comprehensive simulation, which demonstrates that the proposed model exhibits a good degree of accuracy for various system organizations and under different working conditions.

The variational iteration method for solving systems of equations of Emden–Fowler type

In this paper, the variational iteration method (VIM) is used to study systems of linear and nonlinear equations of Emden–Fowler type arising in astrophysics. The VIM overcomes the singularity at the origin and the nonlinearity phenomenon. The Lagrange multipliers for all cases of the parameter α,α>0, are determined. The work is supported by examining specific systems of two or three Emden–Fowler equations where the convergence of the results is emphasized.