This research proposes a method to eliminate friction effect and reduced tracking error on CNC milling machines. A CNC milling machine has many connected mechanical components which have friction effects such as ball ...
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(纸本)9789746724913
This research proposes a method to eliminate friction effect and reduced tracking error on CNC milling machines. A CNC milling machine has many connected mechanical components which have friction effects such as ball screws and rails. To control servo motors which are used to drive X-Y table in CNC milling machine, the conventional PID controller is widely used. In this research, Panasonic motor driver is set to the torque control mode. To compensate the friction effects, the friction feedforward compensation method is proposed. Moreover, to reduce the position tracking error, position feedforward controller is used. The simulation and implementation of position control in one axis of PID with Friction Feedforward Compensation and Position Feedforward controller (FFC-PFC) are presented.
Many real natural or man-made dynamic systems can be better characterized using a fractional order dynamic model. Since in such a case the order assumes a non-integer value, it is of interest to consider the effect of...
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Many real natural or man-made dynamic systems can be better characterized using a fractional order dynamic model. Since in such a case the order assumes a non-integer value, it is of interest to consider the effect of small perturbation around the nominal value. It is of practical importance to analyze the influence of the order variations on the system behavior. This paper establishes an analytical method for the analysis of the sensitivity function of LTI fractional order dynamic systems with respect to the orders. The continuous dependent condition of the orders of fractional Green's function is derived, which is proved as a necessary and sufficient condition. The singularity of fractional Green's functions is discussed. Several examples are included for illustration.
Auditory perception is one of the most important functions for robotics applications. Microphone arrays are widely used for auditory perception in which the spatial structure of microphones is usually known. In practi...
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Making good operation decisions during abnormal power plant conditions represents in many cases the possibility to avoid a unit trip or having economical losses. This paper introduces AsistO, an intelligent assistant ...
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In this letter, we present a novel approach of valve stiction detection using wavelet technology. A new non-invasive method is developed with the closed-loop normal operating data. The redundant dyadic discrete wavele...
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In this letter, we present a novel approach of valve stiction detection using wavelet technology. A new non-invasive method is developed with the closed-loop normal operating data. The redundant dyadic discrete wavelet transform is used to decompose the data at different resolution scales. Based on the Lipschitz regularity theory, wavelet coefficients analysis across scales is performed to detect the jumps in the controlled variables. Adaptive wavelet de-noising is then applied to the data. Features of the valve stiction patterns are extracted from the de-noised data and the valve stiction probability is calculated.
This paper deals with resource allocation in multi-project manufacturing system design, where more than one shared renewable resource type may be required by the manufacturing operation and the availability of each ty...
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This paper deals with resource allocation in multi-project manufacturing system design, where more than one shared renewable resource type may be required by the manufacturing operation and the availability of each type is time limited. The aim of the paper is to present a knowledge-based and constraint programming-driven approach to resource allocation where that data can be imprecise. The presented design scheme is used as a framework for developing a task oriented decision support tool for project portfolio prototyping (DST4P 3 ). The tool provides a prompt and interactive service to a set of routine queries defined in terms of both direct and inverse resource allocation tasks.
Making good operation decisions during abnormal power plant conditions represents in many cases the possibility to avoid a unit trip or having economical losses. This paper introduces AsistO, an intelligent assistant ...
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Making good operation decisions during abnormal power plant conditions represents in many cases the possibility to avoid a unit trip or having economical losses. This paper introduces AsistO, an intelligent assistant for the decision support based on decision theoretic planning techniques. It provides power plant operators with useful recommendations to (i) maintain a plant running under safe conditions, or (ii) deal with process transients when an unexpected event occurs. We present the formalism of Markov decision processes as the core of the intelligent assistant which uses a factored representation of plant states. We also show a very intutive algorithm to approximate decision models based on training data collected through random exploration routines in a simulated environment. We have tested our system in the steam generation system of a combined power plant to deal with load disturbances.
In the this paper, a CMAC-Q-learning based Dyna agent is presented to relieve the problem of learning speed in reinforcement learning, in order to achieve the goals of shortening training process and increasing the le...
In the this paper, a CMAC-Q-learning based Dyna agent is presented to relieve the problem of learning speed in reinforcement learning, in order to achieve the goals of shortening training process and increasing the learning, speed. We combine CMAC, Q-learning, and prioritized sweeping techniques to construct the Dyna agent in which a Q-learning is trained for policy learning; meanwhile, model approximators, called CMAC-model and CMAC-R-model, are in charge of approximating the environment model. The approximated model provides the Q-learning with virtual interaction experience to further update the policy within the time gap when there is no interplay between the agent and the real environment. The Dyna agent switches seamlessly between the real environment and the virtual environment model for the objective of policy learning. A simulation for controlling a differential-drive mobile robot has been conducted to demonstrate that the proposed method can preliminarily achieve the design goal.
A kind of output-feedback networked control system was addressed to overcome the defect of feedback lag introduced by the network usage in the networked control system. By introducing a plant model and a buffer into t...
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A kind of output-feedback networked control system was addressed to overcome the defect of feedback lag introduced by the network usage in the networked control system. By introducing a plant model and a buffer into this system, when feedback was available, this system could compute the control output and update the plant model with the plant output, otherwise, compute the control output based on the plant model output instead of plant output. On the condition that the plant was SISO and the error between plant and model existed, the necessary and sufficient condition for closed-loop stability of this system was derived. Simulation indicates that the range of model error within which this system is stable is easy to be derived by using this necessary and sufficient condition.
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