A paper deals with application of stochastic methods for dynamic neural network training. The considered network is composed of dynamic neurons, which contain inner feedbacks. This network can be used as a part of a f...
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A paper deals with application of stochastic methods for dynamic neural network training. The considered network is composed of dynamic neurons, which contain inner feedbacks. This network can be used as a part of a fault diagnosis system to generate residuals. Up-to-date training algorithms, based on the classical back propagation, suffer from entrapment in local minima of an error function. Two stochastic algorithms are tested as training algorithms to overcome these difficulties. Efficiency of the proposed learning methods is checked using data recorded at Lublin Sugar Factory, Poland.
This paper addresses the problem of implementing predictive controllers for supervisory level control systems. In this configuration the manipulated variables calculated by the Predictive controller are used as comman...
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This paper addresses the problem of implementing predictive controllers for supervisory level control systems. In this configuration the manipulated variables calculated by the Predictive controller are used as command signals for the Distributed control Systems, which provide references to the operator-tuned local PID controllers that act on the physical system. This structure introduces the problem of loosing of performance if the inner-loop controllers are re-tuned. The paper discusses the solution to this problem based on the use of a two-degrees-of-freedom structure in the inner loop, that separates open and closed-loop properties. Both design guidelines and robustness issues are discussed.
Substantial progress has been made recently towards designing, building and test-flying remotely piloted Micro Air Vehicles (MAVs) and small UAVs. We seek to complement this progress in overcoming the aerodynamic obst...
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Substantial progress has been made recently towards designing, building and test-flying remotely piloted Micro Air Vehicles (MAVs) and small UAVs. We seek to complement this progress in overcoming the aerodynamic obstacles to flight at very small scales with a vision-guided flight stability and autonomy system, based on a robust horizon detection algorithm. In this paper, we first motivate the use of computer vision for MAV autonomy, arguing that given current sensor technology, vision may be the only practical approach to the problem. We then describe our statistical vision-based horizon detection algorithm, which has been demonstrated at 30 Hz with over 99.9% correct horizon identification. Next, we develop robust schemes for the detection of extreme MAV attitudes, where no horizon is visible, and for the detection of horizon estimation errors, due to external factors such as video transmission noise. Finally, we discuss our feedback controller for self-stabilized flight, and report results on vision-based autonomous flights of duration exceeding ten minutes.
It is concluded from the results of testing the frequency characteristics of the sub micron precision machine tool servo control system, that the existence of several oscillating modalities is the main factor that aff...
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It is concluded from the results of testing the frequency characteristics of the sub micron precision machine tool servo control system, that the existence of several oscillating modalities is the main factor that affects the performance of the control system. To compensate for this effect,several concave filters are utilized in the system to improve the control accuracy. The feasibility of compensating for several oscillating modalities with a single concave filter is also studied. By applying a modified Butterworth concave filter to the practical system, the maximum stable state output error remains under ±10 nm in the closed loop positioning system.
This paper shows design & implementation of adaptive neural networks controller for DC Motor Speed control System. DC Motor is actuated by Pulse Width Modulation (PWM)-based H-Bridge actuator. By using certain lea...
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This paper shows design & implementation of adaptive neural networks controller for DC Motor Speed control System. DC Motor is actuated by Pulse Width Modulation (PWM)-based H-Bridge actuator. By using certain learning methods to the networks, changing plant's parameter can be estimated and used to produce appropriate control action. The experiment shows that the controller conforms the adaptive control scheme, although there are flaws which related to feedback resolution. The most interesting result is that the implementation circuit is based on very simple 8-bit microcontroller system.
The formation of a convoy of cars (platoon) by linking these electronically (soft platooning) or mechanically (hard platooning) are two of the most researched methods in highway transportation systems, particularly th...
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The formation of a convoy of cars (platoon) by linking these electronically (soft platooning) or mechanically (hard platooning) are two of the most researched methods in highway transportation systems, particularly the first one that is the base of the Automated Highway Systems. This paper focuses on the advantages and disadvantages of both systems and introduces the main technical problems of them. The need for new traffic rules is examined in the case of truck train travels on a multi-lane highway. The kingpin sliding technique is also proposed to face the off-tracking phenomenon of multi-articulated vehicles. Some conclusions from the comparison of the two systems are also given
The motion of a multi-body autonomous robot as well as of a train-like multi-articulated transportation vehicle is characterized by the deviation of the path of each intermediate vehicle from that of the leading one (...
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The motion of a multi-body autonomous robot as well as of a train-like multi-articulated transportation vehicle is characterized by the deviation of the path of each intermediate vehicle from that of the leading one (off-tracking). This paper proposes an intelligent controller for the elimination of the off-tracking phenomenon, in both robotic and transportation multi- articulated vehicles. By using a sliding kingpin technique that allows articulated semi-trailers to follow closely the tractor's path, and taking into consideration the heuristic knowledge that stems from the driving practice and the tests' experience, a fuzzy rule-based controller has been developed to determine the sliding distance and the sliding rate of the kingpin mechanism. Simulation results for various cases, without and with the sliding kingpin system showed that off-tracking elimination is achieved to a significant degree through the use of intelligent controller.
Deals with the use of object oriented technologies in the modeling of industrial plants that have to be remotely monitored and/or controlled. The main goal is to propose a design methodology for obtaining the model of...
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ISBN:
(纸本)0780372417
Deals with the use of object oriented technologies in the modeling of industrial plants that have to be remotely monitored and/or controlled. The main goal is to propose a design methodology for obtaining the model of the so-called Virtual Plant, that a remote and certified user will use to access the real plant for performing command actions and/or monitoring. The type of applications and systems targeted must have autonomous behavior and be interconnected and accessible. Reliability, maintainability and flexibility are also required goals, as well as a high rate of reusability of the applications. The methodology has been applied to the remote process monitoring and control of manufacturing processes. The Virtual Plant Model is, in fact, the part of the plant that can be accessed by a certified remote client and thus it can be constituted by a set of sub-models, as many as different types of clients. The Virtual Plant resides inside the Application Server who is responsible of communicating with the cell controller and sends the image of the actual plant state (the Virtual Plant) as required by the remote client (monitoring) or sends the client commands to the cell controller.
This paper presents a feasible open-canal water-distribution control system based on the dynamic regulation principle and the theory of Kalman optimal controller. The existing nonlinear phenomena, as well as the trans...
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This paper presents a feasible open-canal water-distribution control system based on the dynamic regulation principle and the theory of Kalman optimal controller. The existing nonlinear phenomena, as well as the transport delay phenomenon are accounted for. The obtained controller is simulated using the full Saint-Venant partial differential equations
In general, characteristics of classical control theory and properties of real-time scheduling algorithms may cause unexpected control system responses in the implementation of real-time computer-controlled systems. R...
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