Fuzzy control has revealed as a practical alternative to several conventional control schemes since it has shown good results in some application areas. However, there are several drawbacks of this approach: (i) the d...
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In this article we are interested in design of a new simple rule-based method of MRAC parameters adaptation aiming to minimize the unmodelled dynamics influence. Firstly, we introduce some recent studies solving the p...
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This paper reports about experience in building control Laboratory with remote access via Internet and in organizing the learning process with the aim to foster an active and creative learning by doing.
This paper reports about experience in building control Laboratory with remote access via Internet and in organizing the learning process with the aim to foster an active and creative learning by doing.
This paper investigates novel sequential learning methods applied on a decomposed form of training algorithms using Radial Basis Function (RBF) network. The dynamic expansion of RBF network by adding neurons to the hi...
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In this paper, the proportional (P) neuron, integral (I) neuron and derivative (D) neuron are introduced and a new neural network: PID neural network (PIDNN) is built. Based on the PID neural network, a strong coupled...
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ISBN:
(纸本)0780388739
In this paper, the proportional (P) neuron, integral (I) neuron and derivative (D) neuron are introduced and a new neural network: PID neural network (PIDNN) is built. Based on the PID neural network, a strong coupled time varying system is decoupled and controlled. The paper displays the perfect performances of the PIDNN in the multivariable time-varying systems.
The computational aspects of the output regulation problem are considered. The standard solution of the output regulation problem uses the explicit solution of the so-called regulator equation being a highly complex P...
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In this article we are interested in design of a new simple rule-based method of MRAC parameters adaptation aiming to minimize the unmodelled dynamics influence. Firstly, we introduce some recent studies solving the p...
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In this article we are interested in design of a new simple rule-based method of MRAC parameters adaptation aiming to minimize the unmodelled dynamics influence. Firstly, we introduce some recent studies solving the problem of using an adaptive system to control a system with unmodelled dynamic. Secondly, the new method of parameters adaptation based on abs ( sgn ( e ) + sgn ( d 2 dt 2 e ) ) signal is discussed. The proposed method seems to set the controller parameters so as to ensure the closed loop aperiodic response.
Fuzzy control has revealed as a practical alternative to several conventional control schemes since it has shown good results in some application areas. However, there are several drawbacks of this approach: (i) the d...
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Fuzzy control has revealed as a practical alternative to several conventional control schemes since it has shown good results in some application areas. However, there are several drawbacks of this approach: (i) the design of fuzzy controllers is usually performed in an ad hoc manner where it is often difficult to choose some of the controller parameters (e.g., the membership functions), and (ii) the fuzzy controller constructed for the nominal plant may later perform inadequately if significant and unpredictable plant parameter variations occur. A “learning system” possesses the capability to improve its performance over time by interacting with its environment. A learning control system is designed so that its “learning controller” has the ability to improve the performance of the closed-loop system by generating command inputs to the plant and utilizing feedback information from the plant. Learning controllers are often designed to mimic the manner in which a human in the control loop would learn how to control a system while it operates. Some characteristics of this human learning process my include: (i) after learning how to control the plant for some operating condition, if the operating conditions change, then the best way to control the system may have to be relearned; (ii) a human with significant amount of experience at controlling the system in one operating region should not forget this experience if the operating condition changes. To mimic these types of human learning behavior, we introduce strategy that can be used to learning controller onto the current operating region of the system.
This paper presents a scheduling technique for a library of arithmetic logarithmic modules for FPGA illustrated on a RLS filter for active noise cancellation. The problem under assumption is to find an optimal periodi...
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This paper presents a scheduling technique for a library of arithmetic logarithmic modules for FPGA illustrated on a RLS filter for active noise cancellation. The problem under assumption is to find an optimal periodic cyclic schedule satisfying the timing constraints. The approach is based on a transformation to monoprocessor cyclic scheduling with precedence delays. We prove that this problem is NP-hard and we suggest a solution based on integer linear programming that allows to minimize completion time. Finally experimental results of optimized RLS filter are shown.
A systems re-engineering technique to integrated control and supervision for applications to industrial multi-zone furnaces has been elaborated by using known theories on generalized predictive control and nonlinear p...
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