We consider a problem of designing no-wait cyclic schedules for job-shop manufacturing system with repetitive transportation tasks that are defined by sequences of operations. Each operation is performed in a sector o...
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We consider a problem of designing no-wait cyclic schedules for job-shop manufacturing system with repetitive transportation tasks that are defined by sequences of operations. Each operation is performed in a sector of manufacturing system using its resources, e.g. vehicles, machines, and takes some time for manufacturing and transportation. The sectors and their resources can be shared by several tasks in the exclusive mode. There are no buffers between sectors thus when a transportation car is in a sector it blocks this sector to other cars and cannot leave it until a sector which is required by the following operation in its transportation route is free. The repetitive transportation tasks performed in a manufacturing system are modelled as a system of cyclic processes executing sequences of operations and sharing common resources according to a mutual exclusion protocol. The problem consists in finding no-wait cyclic schedules for which no process (tasks) that started execution will wait for resources (sectors) required to execute its operations and each operation will be started immediately after finishing the previous one. The casade-like structure (C-LS) system of processes is considered. This system is structurally deadlock-free therefore no-buffer (resource blocking) constraint will never lead to deadlock state. The C-LS system of processes can be seen as a composition of subsystems with two cyclic processes sharing a single resource, namely 2-P subsystems. Using our recurrent integer modulus equations model (developed in our previous works) we find for each 2-P subsystem all possible start times of the processes (if exist) that belong to a no-wait schedule and construct all possible no-wait schedules for each component 2-P. Finally, we design cyclic no-wait schedules for the C-LS system by joining the cyclic schedules designed for its component 2-P subsystems.
Artificial Neural Networks (ANNs) implement a specific form of multi-variate extrapolation and will generate an output for any input pattern, even when there is no similar training pattern. Extrapolations are not nece...
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Object control requires the calculation of a regulator. One of the most effective methods for calculating the regulator is the method of numerical optimization of the regulator. This paper discusses the solution of th...
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Signal temporal logic (STL) provides a userfriendly interface for defining complex tasks for robotic systems. Recent efforts aim at designing control laws or using reinforcement learning methods to find policies which...
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Inverter-interfaced microgrids differ from the traditional power systems due to their lack of inertia. Vanishing timescale separation between voltage and frequency dynamics makes it critical that faster-timescale stab...
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ISBN:
(纸本)9781538679012;9781538679265
Inverter-interfaced microgrids differ from the traditional power systems due to their lack of inertia. Vanishing timescale separation between voltage and frequency dynamics makes it critical that faster-timescale stabilizing control laws also guarantee by-construction the satisfaction of voltage limits during transients. In this article, we apply a barrier functions method to compute distributed active and reactive power setpoint control laws that certify satisfaction of voltage limits during transients. Using sum-of-squares optimization tools, we propose an algorithmic construction of these control laws. Numerical simulations are provided to illustrate the proposed method.
With the coming of exascale supercomputing era, power efficiency has become the most important obstacle to build an exascale system. Dataflow architecture has native advantage in achieving high power efficiency for sc...
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With the coming of exascale supercomputing era, power efficiency has become the most important obstacle to build an exascale system. Dataflow architecture has native advantage in achieving high power efficiency for scientific applications. However, the state-of-the-art dataflow architectures fail to exploit high parallelism for loop processing. To address this issue, we propose a pipelining loop optimization method (PLO), which makes iterations in loops flow in the processing element (PE) array of dataflow accelerator. This method consists of two techniques, architecture-assisted hardware iteration and instruction-assisted software iteration. In hardware iteration execution model, an on-chip loop controller is designed to generate loop indexes, reducing the complexity of computing kernel and laying a good f(mndation for pipelining execution. In software iteration execution model, additional loop instructions are presented to solve the iteration dependency problem. Via these two techniques, the average number of instructions ready to execute per cycle is increased to keep floating-point unit busy. Simulation results show that our proposed method outperforms static and dynamic loop execution model in floating-point efficiency by 2.45x and 1.1x on average, respectively, while the hardware cost of these two techniques is acceptable.
A simple and effective colored Petri net (CPN) model is proposed in this paper for a special type of electrical networks that describe local transformer areas, in order to detect and localize illegal loads that may be...
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In this paper, we study the control of dynamical systems under temporal logic task specifications using gradient-based methods relying on quantitative measures that express the extent to which the tasks are satisfied....
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Due to the influence of haze in winter, outdoor images usually lose contrast and fidelity. In view of the fact that most de-fog algorithms are not effective for images with large sky areas, an improved dark channel a ...
Due to the influence of haze in winter, outdoor images usually lose contrast and fidelity. In view of the fact that most de-fog algorithms are not effective for images with large sky areas, an improved dark channel a priori de-fog method is proposed. First of all, the sky region is segmented according to the image gradient information, and on the basis of sky segmentation, the atmospheric light value is reasonably estimated by setting the discriminant formula combined with the high brightness and smoothness of atmospheric light reference pixels. Secondly, according to the different dark channel values, the piecewise linear function is used to dynamically modify the adjustable parameters to solve the local shadow caused by excessive defog. Then, the transmittance estimated by the bright channel model and the improved dark channel prior model are fused, and the edge is optimized by guided filtering. Finally, combined with the atmospheric scattering model, the defog image is obtained by brightness compensation and contrast stretching. The experimental results show that the improved method can effectively improve the image distortion, enhance the image contrast and details, especially in maintaining the visual authenticity of the sky region.
Signal temporal logic (STL) provides a user-friendly interface for defining complex tasks for robotic systems. Recent efforts aim at designing control laws or using reinforcement learning methods to find policies whic...
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ISBN:
(纸本)9781538679012;9781538679265
Signal temporal logic (STL) provides a user-friendly interface for defining complex tasks for robotic systems. Recent efforts aim at designing control laws or using reinforcement learning methods to find policies which guarantee satisfaction of these tasks. While the former suffer from the trade-off between task specification and computational complexity, the latter encounter difficulties in exploration as the tasks become more complex and challenging to satisfy. This paper proposes to combine the benefits of the two approaches and use an efficient prescribed performance control (PPC) base law to guide exploration within the reinforcement learning algorithm. The potential of the method is demonstrated in a simulated environment through two sample navigational tasks.
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