A learning feedforward controller (LFFC) using the Bartlet window function is proposed for a better tracking control of linear system over a finite time interval. LFFC is applied as a feedforward controller to the exi...
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A learning feedforward controller (LFFC) using the Bartlet window function is proposed for a better tracking control of linear system over a finite time interval. LFFC is applied as a feedforward controller to the existing feedback controller. This paper demonstrates that using a simple window function-Bartlet (Fejer or triangular) window in signal processing, the design of a learning feedforward controller reduces to determining only two design parameters: the learning gain and the number of point in the window. Convergence analysis is presented together with a design procedure.
This paper examines two classes of algorithms that estimate a continuous time ARX type of models from discrete data: one is based on infinite impulse response (IIR) filters while the other is based on finite impulse r...
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This paper examines two classes of algorithms that estimate a continuous time ARX type of models from discrete data: one is based on infinite impulse response (IIR) filters while the other is based on finite impulse response (FIR) filters. The IIR filters use continuous time state variable filters, and discretisation is performed on the filtered derivatives. In contrast, the FIR filters are in a discrete form with carefully chosen coefficients to approximate the derivatives of the continuous time variables. The strength and weakness of each approach are discussed and demonstrated by a set of simulation examples.
automatic acquisition of an object using model appearance from an environment is proposed in this paper. Robots directly interact with a defined environment in order to extract object shape from its scene. The robot e...
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ISBN:
(纸本)4907764197
automatic acquisition of an object using model appearance from an environment is proposed in this paper. Robots directly interact with a defined environment in order to extract object shape from its scene. The robot extracts the targeted object's appearance, creating an eigenspace, and stores it into the memory server (or intelligent data carrier). Eigenspace is constructed every time a new object appears, and various appearances are accumulated gradually. A closed sequence of appearances is generated from the accumulated shapes, which is used for object recognition. Experimental results of object accumulation and recognition show the effectiveness of the proposed method.
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.
Many fundamental problems in the max-plus-algebraic system theory for discrete event systems - among which the minimal state space realization problem - can be solved using an Extended Linear Complementarity Problem (...
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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 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.
The paper discusses the usefulness of Gröbner bases methods in a variety of control problems for a class of polynomial systems. Polynomial systems are described by difference or differential equations in which th...
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The paper discusses the usefulness of Gröbner bases methods in a variety of control problems for a class of polynomial systems. Polynomial systems are described by difference or differential equations in which the transition map or vectorfield are polynomials. Gröbner bases methods are useful in both the analysis and the design of polynomial control systems.
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.
Many fundamental problems in the max-plus-algebraic system theory for discrete event systems — among which the minimal state space realization problem — can be solved using an Extended Linear Complementarity Problem...
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Many fundamental problems in the max-plus-algebraic system theory for discrete event systems — among which the minimal state space realization problem — can be solved using an Extended Linear Complementarity Problem (ELCP). We present some new, more efficient methods to solve the ELCP. We show that an ELCP with a bounded feasible set can be recast as a standard Linear Complementarity Problem (LCP). Our proof results in three possible numerical solution methods for a given ELCP: regular ELCP algorithms, mixed integer linear programming algorithms, and regular LCP algorithms. We also apply these three methods to a basic max-plus-algebraic benchmark problem.
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.
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