Initial condition insertion circuit for hybrid multiplexing systems

The accuracy and time required to inseri initial conditions in hybrid computers are important considerations in multiplexing methods. Circuit diagrams are presented that increase the accuracy or reduce the time required to insert the initial conditions in current analog computers. The improvements are accomplished by a high speed track-store amplifier connected to an integrator. The circuit for initial condition insertion for new hybrid systems is also introduced.     

Design optimization of microprocessor-based remote multiplexing systems

A physical model of a microprocessor-based remote multiplexing system is constructed, based on the physical layout of the plant and the distribution of input/output variables. A cost index is generated based on the above model, which when maximized, yields a maximum solution that defines the cost optimal number, location and load of the remote systems. The optimal solution is determined by simulation in a medium-size digital computer.     

Probabilistic quorums for dynamic systems

A quorum system is a set of sets such that every two sets in the quorum system intersect. Quorum systems are well known building blocks for maintaining information in a distributed system while providing high availability and good load balance. Probabilistic Quorum Systems (PQS) are variants of quorum systems that relax the strict intersection requirement. They are particularly attractive for large scale systems due to their simplicity and highly efficient availability—load balance tradeoff. We introduce scalable techniques that maintain a PQS in a highly decentralized and highly dynamic setting. We address two challenges. First we show how PQS can be realized efficiently even when each process maintains knowledge of only a constant number of other members. Second, we provide algorithms that adaptively evolve the quorums to adjust to the changes in the system caused by processes leaving and joining the system over time.     

Stability of networked control systems with multi-step delay based on time-division algorithm

1IntroductionFeedback control systems in which the control loops areclosed through a real_time network are called networkedcontrol systems(NCS)[1,2].Conventional controltheories should be reevaluated before they are applied toNCS because of the existence of sensor_to_controller delayτscand controller_to_actuator delayτca.They may degradethe performance of control systemand even destabilize thesystem.There are two kinds of design methods for NCS:deterministic design methods and stochastic…     

An inclusion principle for dynamic systems

The purpose of this paper is to present a detailed study of the inclusion concept in dynamic systems, which is a suitable mathematical framework for comparing systems with different dimensions. The framework offers immediate results in reduced-order modeling and the overlapping decentralized control of complex systems. The presentation, which is limited to linear constant systems, relies on both the matrix algebra (computations) and the geometric elements (structure) to provide a balanced view of the issues involved in the concept of inclusion. The framework is quite broad, and has been used to consider nonlinear and time-varying systems, as well as systems with hereditary and stochastic effects.     

Error estimates for approximate dynamic systems

Two approaches are investigated for obtaining estimates on the error between approximate and exact solutions of dynamic systems. The first method is primarily useful if the system is non-linear and of low dimension. The second requires construction of a system of u-functions but is useful for higher dimensional systems, either linear or non-linear.     

Convex dynamic programming for hybrid systems

A classical linear programming approach to optimization of flow or transportation in a discrete graph is extended to hybrid systems. The problem is finite dimensional if the state space is discrete and finite, but becomes infinite dimensional for a continuous or hybrid state space. It is shown how strict lower bounds on the optimal loss function can be computed by gridding the continuous state space and restricting the linear program to a finite-dimensional subspace. Upper bounds can be obtained by evaluation of the corresponding control laws.     

Ellipsoidal techniques for dynamic systems: Control synthesis for uncertain systems

This article is a continuation of the work reported in [4], introducing unknown but bounded disturbances into the problem of control synthesis studied there. The technique presented allows an algorithmization with an appropriate graphic simulation. The original theoretical solution scheme taken here comes from the theory introduced by N.N. Krasovski [1], from the notion of the alternated integral of L.S. Pontriagin [2] and the funnel equation in the form given in [3]. For alternative treatment of related problems, see also [5], [6], and [7]. The theory is used as a point of application of constructive schemes generated through ellipsoidal techniques developed by the authors. A concise exposition of the latter is the objective of this article. A particular feature is that the ellipsoidal techniques introduced here do indicate an exact approximation of the original solutions based on set-valued calculus by solutions formulated in terms of ellipsoidal-valued functions only. Editor: J. Skowronski     

Reducing communication latency with path multiplexing in opticallyinterconnected multiprocessor systems

Reducing communication latency, which is a performance bottleneck in optically interconnected multiprocessor systems, is of prominent importance. A conventional approach for establishing connections in multiplexed networks uses a set of independent time slots (or virtual channels) along a path for each connection. This approach requires the use of switching devices capable of interchanging time slots, and thus introduces latency in addition to hardware and control complexity. We propose an approach to all-optical time division multiplexed (TDM) communications in multiprocessor systems. The idea is to establish a connection along a path using a set of time slots (or virtual channels) that are dependent on each other, so that no time slot interchanging is required. We compare the proposed approach with the conventional one in terms of the overall communication latency. We found that, despite the possibility that establishing a connection may take a longer time, the proposed approach will result in lower overall communication latency as it eliminates the delays introduced by the time slot interchanging switching devices     

Robust control techniques for general dynamic systems

Lyapunov techniques are used to design robust controllers for nonlinear systems. The objective is to use the system structure to simplify the controller as far as possible. A general robust control scheme is developed that applies to systems described by a class of second-order nonlinear equations. Applications to a mobile robot and a chemical stirred tank reactor are given.     

Parity relations for linear uncertain dynamic systems

A new approach for the design of parity relations for linear dynamic systems with additive and multiplicative uncertainties is presented. Instead of cancelling uncertainties following the example of the so-called robust approaches, uncertain parity relations take uncertainties into account as bounded variables. The method is based on the analysis of zonotopes representing the uncertainties. It leads both to Boolean detection results and to an indicator representing the distance to the opposite decision.     

Static and dynamic adaptations for service-based systems

Context

In service-oriented computing (SOC), service providers publish reusable services, and service consumers subscribe them. However, there exist potential problems in reusing services. Mismatch is a problem that occurs when a candidate service does not fully match to the feature expected. Fault is a problem that occurs when an invocation of services results in some abnormality at runtime. Without remedying mismatch problems, services would not be reusable. Without remedying fault problems, service invocations at runtime would result in failures. Static and dynamic adaptations are practical approaches to remedying the problems.

Objective

Our objective is to define a comprehensive framework which includes a design of service adaptation framework (SAF), and design of static and dynamic adapters.

Method

We design the SAF which governs dynamic adaptations, and define a service life-cycle with adaptation-related activities. Based on causal–effect relationships among mismatch, fault, cause, and adapter, we derive mismatches and faults, from which their relevant causes are identified. For the causes, we define six static adapters and five dynamic adapters. We specify instructions for designing static adapters, and provide step-wise algorithms for designing dynamic adapters based on enterprise service bus (ESB). And, we show a proof-of-concept (POC) of implementation to show applicability of the methods.

Results

The paper presents service life-cycle with adaptation-related activities, SAF design, and design of static and dynamic adapters.

Conclusion

Mismatch and fault problems in utilizing services present threats to high reusability of services. Static adaptations can remedy mismatch problems, and dynamic adaptations can remedy fault problems. In this paper, we presented technical insights of service adaption, SAF design, and definitions of static and dynamic adapters. By utilizing the proposed SAF and service adapters, reusability of services can be greatly enhanced.     

An algorithm for inverting linear dynamic systems

An algorithm is presented for inverting transformations associated with linear dynamic systems. The induced inverse system, when it exists, operates on outputs and generates the corresponding inputs of the system to which it is inverse. The applications for inverse systems are found in such diverse areas as control, coding, filtering, and sensitivity analysis.     

Non-linear smoothing algorithm for multi-dimensional dynamic systems

A new sub-optimum smoothing algorithm is presented for multi-dimensional dynamic systems. This algorithm is based upon quantization, multiple hypothesis testing, and the Viterbi decoding algorithm. The estimation of state vectors is carried out sequentially, component-by-component, and in parallel. A considerable memory reduction is achieved for state estimation implementation with the proposed algorithm. Simulation results, some of which are presented, show that the sub-optimum algorithm performs better than the extended Kalman filter algorithm for some non-linear multi-dimensional models with white gaussian disturbance and observation noises. In addition, the performance of the sub-optimum algorithm is almost as good as the Kalman filter algorithm for linear multi-dimensional models with white gaussian noise.     

Adaptive dynamic programming for linear impulse systems

We investigate the optimization of linear impulse systems with the reinforcement learning based adaptive dynamic programming （ADP） method. For linear impulse systems, the optimal objective function is shown to be a quadric form of the pre-impulse states. The ADP method provides solutions that iteratively converge to the optimal objective function. If an initial guess of the pre-impulse objective function is selected as a quadratic form of the pre-impulse states, the objective function iteratively converges to the optimal one through ADP. Though direct use of the quadratic objective function of the states within the ADP method is theoretically possible, the numerical singularity problem may occur due to the matrix inversion therein when the system dimensionality increases. A neural network based ADP method can circumvent this problem. A neural network with polynomial activation functions is selected to approximate the pr~impulse objective function and trained iteratively using the ADP method to achieve optimal control. After a successful training, optimal impulse control can be derived. Simulations are presented for illustrative purposes.     

Software for dynamic reconfigurable order picking systems

This paper describes an approach, conceptual framework, and software architecture for dynamic reconfiguration of the order picking system. The research and development project was sponsored by the Material Handling Research Center (MHRC), a National Science Foundation sponsored Cooperative Industry/University Research Center. The storage configuration is assumed to be an in-the-aisle order picking system in which stockkeeping units (SKUs) can occupy variable capacity storage locations and stock-splitting is allowed among zones (clusters). The product mix may include multiple product families with different life cycles, correlated demand within families and commonality of demand across families.     

Fiber categories for describing dynamic production systems

It is shown that in the extension of the category-theoretical approach to the domain of dynamic systems based on knowledge, specific structures called fiber categories arise. Morphisms of this category are sets of morphisms, and in each inference process in this category one and only one morphism of this set takes part. It is determined by the external conditions, formally given by a certain algebraic lattice what this morphism is precisely. In other words, the category for describing an expert system in the dynamic case is a superposition of similar categories discriminated only by morphisms employed.