Supervisory Control for Real-Time Systems Based on Conflict-Tolerant Controllers

This paper addresses the problem of detecting and resolving conflicts due to timing constraints imposed by features in real-time and hybrid systems. We consider systems composed of a base system with multiple features or controllers, each of which independently advise the system on how to react to input events so as to conform to their individual specifications. We propose a methodology for developing such systems in a modular manner based on the notion of conflict-tolerant features that are designed to continue offering advice even when their advice has been overridden in the past. We give a simple priority-based scheme forcomposing such features. This guarantees the maximal use of each feature. We provide a formal framework for specifying such features, and a compositional technique for verifying systems developed in this framework.

Secure Concurrency Control in Firm Real-Time Database Systems

Many real-time database applications arise in electronic financial services, safety-critical installations and military systems where enforcing security is crucial to the success of the enterprise. For real-time database systems supporting applications with firm deadlines, we investigate here the performance implications, in terms of killed transactions, of guaranteeing multilevel secrecy. In particular, we focus on the concurrency control (CC) aspects of this issue. Our main contributions are the following: First, we identify which among the previously proposed real-time CC protocols are capable of providing covert-channel-free security. Second, using a detailed simulation model, we profile the real-time performance of a representative set of these secure CC protocols for a variety of security-classified workloads and system configurations. Our experiments show that a prioritized optimistic CC protocol, OPT-WAIT, provides the best overall performance. Third, we propose and evaluate a novel "dual-CC" approach that allows the real-time database system to simultaneously use different CC mechanisms for guaranteeing security and for improving real-time performance. By appropriately choosing these different mechanisms, concurrency control protocols that provide even better performance than OPT-WAIT are designed. Finally, we propose and evaluate GUARD, an adaptive admission-control policy designed to provide fairness with respect to the distribution of killed transactions across security levels. Our experiments show that GUARD efficiently provides close to ideal fairness for real-time applications that can tolerate covert channel bandwidths of upto one bit per second.

Dual-trap optical tweezers with real-time force clamp control

Single molecule force clamp experiments are widely used to investigate how enzymes, molecular motors, and other molecular mechanisms work. We developed a dual-trap optical tweezers instrument with real-time (200 kHz update rate) force clamp control that can exert 0–100 pN forces on trapped beads. A model for force clamp experiments in the dumbbell-geometry is presented. We observe good agreement between predicted and observed power spectra of bead position and force fluctuations. The model can be used to predict and optimize the dynamics of real-time force clamp optical tweezers instruments. The results from a proof-of-principle experiment in which lambda exonuclease converts a double-stranded DNA tether, held at constant tension, into its single-stranded form, show that the developed instrument is suitable for experiments in single molecule biology.

Diesel smoke transient control using a real-time smoke sensor

A novel real time smoke sensor is described, which is mounted in the exhaust manifold and detects the smoke by virtue of the natural electrical charge which is carried on the smoke. The somewhat obscure origin of the charge on the smoke is briefly considered, as well as the operation of the sensor itself. The use of the sensor as part of a feedback control shows that it can be very effective in reducing smoke puffs. Copyright © 1987 Society of Automotive Engineers, Inc.

Real-time far distance micro-vibration measurement using an external cavity semiconductor laser interferometer with a feedback control system

An external cavity semiconductor laser interferometer used to measure far distance micro-vibration in real time is proposed. In the interferometer, a single longitudinal mode and excellent coherent characteristic grating external cavity semiconductor laser is constructed and acted as a light source and a phase compensator. Its coherent length exceeds 200 meters. The angle between normal and incidence beam of the far object is allowed to change in definite range during the measurement with this interferometer, and this makes the far distance interference measurement easier and more convenient. Also, it is not required to keep the amplitudes of the first and second harmonic components equal, and then the dynamic range is increased. A feedback control system is used to compensate the phase disturbance between the two interference beams introduced by environmental vibration.

Speculative Concurrency Control for Real-Time Databases

In this paper, we propose a new class of Concurrency Control Algorithms that is especially suited for real-time database applications. Our approach relies on the use of (potentially) redundant computations to ensure that serializable schedules are found and executed as early as possible, thus, increasing the chances of a timely commitment of transactions with strict timing constraints. Due to its nature, we term our concurrency control algorithms Speculative. The aforementioned description encompasses many algorithms that we call collectively Speculative Concurrency Control (SCC) algorithms. SCC algorithms combine the advantages of both Pessimistic and Optimistic Concurrency Control (PCC and OCC) algorithms, while avoiding their disadvantages. On the one hand, SCC resembles PCC in that conflicts are detected as early as possible, thus making alternative schedules available in a timely fashion in case they are needed. On the other hand, SCC resembles OCC in that it allows conflicting transactions to proceed concurrently, thus avoiding unnecessary delays that may jeopardize their timely commitment.

An Admission Control Paradigm for Real-time Databases

We propose and evaluate an admission control paradigm for RTDBS, in which a transaction is submitted to the system as a pair of processes: a primary task, and a recovery block. The execution requirements of the primary task are not known a priori, whereas those of the recovery block are known a priori. Upon the submission of a transaction, an Admission Control Mechanism is employed to decide whether to admit or reject that transaction. Once admitted, a transaction is guaranteed to finish executing before its deadline. A transaction is considered to have finished executing if exactly one of two things occur: Either its primary task is completed (successful commitment), or its recovery block is completed (safe termination). Committed transactions bring a profit to the system, whereas a terminated transaction brings no profit. The goal of the admission control and scheduling protocols (e.g., concurrency control, I/O scheduling, memory management) employed in the system is to maximize system profit. We describe a number of admission control strategies and contrast (through simulations) their relative performance.

Vector Associative Maps: Unsupervised Real-time Error-based Learning and Control of Movement Trajectories

This article describes neural network models for adaptive control of arm movement trajectories during visually guided reaching and, more generally, a framework for unsupervised real-time error-based learning. The models clarify how a child, or untrained robot, can learn to reach for objects that it sees. Piaget has provided basic insights with his concept of a circular reaction: As an infant makes internally generated movements of its hand, the eyes automatically follow this motion. A transformation is learned between the visual representation of hand position and the motor representation of hand position. Learning of this transformation eventually enables the child to accurately reach for visually detected targets. Grossberg and Kuperstein have shown how the eye movement system can use visual error signals to correct movement parameters via cerebellar learning. Here it is shown how endogenously generated arm movements lead to adaptive tuning of arm control parameters. These movements also activate the target position representations that are used to learn the visuo-motor transformation that controls visually guided reaching. The AVITE model presented here is an adaptive neural circuit based on the Vector Integration to Endpoint (VITE) model for arm and speech trajectory generation of Bullock and Grossberg. In the VITE model, a Target Position Command (TPC) represents the location of the desired target. The Present Position Command (PPC) encodes the present hand-arm configuration. The Difference Vector (DV) population continuously.computes the difference between the PPC and the TPC. A speed-controlling GO signal multiplies DV output. The PPC integrates the (DV)·(GO) product and generates an outflow command to the arm. Integration at the PPC continues at a rate dependent on GO signal size until the DV reaches zero, at which time the PPC equals the TPC. The AVITE model explains how self-consistent TPC and PPC coordinates are autonomously generated and learned. Learning of AVITE parameters is regulated by activation of a self-regulating Endogenous Random Generator (ERG) of training vectors. Each vector is integrated at the PPC, giving rise to a movement command. The generation of each vector induces a complementary postural phase during which ERG output stops and learning occurs. Then a new vector is generated and the cycle is repeated. This cyclic, biphasic behavior is controlled by a specialized gated dipole circuit. ERG output autonomously stops in such a way that, across trials, a broad sample of workspace target positions is generated. When the ERG shuts off, a modulator gate opens, copying the PPC into the TPC. Learning of a transformation from TPC to PPC occurs using the DV as an error signal that is zeroed due to learning. This learning scheme is called a Vector Associative Map, or VAM. The VAM model is a general-purpose device for autonomous real-time error-based learning and performance of associative maps. The DV stage serves the dual function of reading out new TPCs during performance and reading in new adaptive weights during learning, without a disruption of real-time operation. YAMs thus provide an on-line unsupervised alternative to the off-line properties of supervised error-correction learning algorithms. YAMs and VAM cascades for learning motor-to-motor and spatial-to-motor maps are described. YAM models and Adaptive Resonance Theory (ART) models exhibit complementary matching, learning, and performance properties that together provide a foundation for designing a total sensory-cognitive and cognitive-motor autonomous system.