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Three-motor variable-freqency speed-regulation synchronous system is a multi-input multi-output(MIMO), nonlinear, and coupling system. The mathematic model of the system is established in the way of analytical expression. Self-tuning PID controllers based on DRNN neural network and neuron decoupling compensator are adopted to realize the adaptive decoupling control of speed and tension. The experiment...
The pinning control problem of complex networks has been widely investigated recent years. However, there does not exist a widely accepted pinning scheme which can be applied to the synchronization of complex networks. This contribution gives a novel pinning scheme which based on the famous PageRank algorithm to make the network realize synchronization as fast as possible. Numerical simulation indicates...
The Organic Network Control (ONC) system has been developed to adapt the parameters of network protocols dynamically to changes in the environment in order to increase the protocol's performance. In order to apply the system to new environments without the need of providing knowledge it is equipped with a simulation-based rule-generation and evaluation component on top of an on-line rule selection...
The increasing complexity of large-scale distributed applications motivates the study and development of self-organising systems. However, engineering self-organising systems is still a challenge. Despite their benefits, self-organising systems suffer from a lack of control and stability, so that methods and tools are needed for improving their understanding and control. In this paper, we consider...
In this paper we revisit our earlier proposed domain model based approach to requirements management from a situational method engineering perspective. The approach has originally been developed dedicatedly for a small- and medium-sized enterprise (SME) in the field of control system development. Broadening the perspective by considering situational method engineering helps to generalize the approach...
In the design of plants and machines the complexity is permanently increasing. Model-driven design methodologies in the field of Industrial Automation and Control Systems, as proposed by the MEDEIA project, help to cope with current requirements like limited budget and reduced ramp-up time. Concurrent development in all involved domains is facilitated by the introduction of simulation in the development...
This paper presents an Adaptive Predictive Control strategy based on Neural Networks for nonlinear systems. In order to train the Neural Network controller, an identification of the system is carried out by the Neural Network Identifier. This second Neural Network provides the training terms related to the nonlinear system dynamics. In this way it is possible to train the Neural Network controller...
That the high technology is applied in modern fire control system makes its performance improve greatly. Meanwhile the complexion of system structure and signal relationship increases the difficulty when testing it. Distributed testing network is presented for designing a set of simulation fire control system based on CAN bus in paper. All imitations of equipment units are linked by CAN bus, which...
This paper deals with a repetitive control problem for the cases where the period of periodic disturbances to be rejected is uncertain but is within known lower and upper bound. A new adaptive repetitive control system with on-line estimation of the period is proposed not only to guarantee stability of the overall system but also both to reject any periodic disturbances with the uncertain period and...
Plug-in adaptive controller (Plug-in AC) can reject the periodic disturbance in adaptive manner at selected frequencies independently, and its design method is based on external model principle which the controller for rejecting disturbance is placed outside the original feedback loop. In this paper, we propose Plug-in AC for discrete-time systems. Discrete-time Plug-in AC can be designed by using...
In this paper, the reconstruction error between the real system to be controlled and its T-S fuzzy model is considered in the context of control system design. As a result, an H∞ approach to adaptive controller that consists of two parts: one is obtained by solving certain linear matrix inequalities (LMIs) (fixed part) and another one is acquired by the fuzzy approximator in which the related parameters...
Evaluating the performance (timing behavior, throughput, and resource utilization) of a software system becomes more and more challenging as today's enterprise applications are built on a large basis of existing software (e.g. middleware, legacy applications, and third party services). As the performance of a system is affected by multiple factors on each layer of the system, performance analysts...
This paper studies the problem of fault detection in networked control systems. In the residual generation, the effect of the networked induced bounded delays as well as the noise is reduced. The minimization of false alarm rate caused from unknown inputs as well as the variation of control inputs is achieved in the residual evaluation stage. This includes the design of an adaptive threshold. An illustrating...
In the paper an on-line secondary path model identification problem for feedforward as well as feedback adaptive active noise control systems working with a deterministic constant or random sampling interval is discussed. A focus on almost sure convergence of identified model to true plant in the case of information about secondary path hidden in between single multiplicities of the quant of A/D converter...
The new method of the synthesis of multidimensional adaptive control system with reference model self-adjustment for the centralized control of the spatial motion of autonomous underwater vehicles is developed in this paper. The conditions of the self-adjustment process stability with the presence of essential dynamic reciprocal effect between all control channels are obtained and strictly proved...
In this paper, an adaptive neural sliding mode controller (ANSMC) is proposed as an asymptotically stable robust controller for a class of Control Affine Nonlinear Systems (CANSs) with unknown dynamics. In the proposed method a Control Affine Radial Basis function Network (CARBFN) is developed for online identification of CANSs. A recursive algorithm based on Extended Kalman Filter (EKF) is used for...
Inverter control is to enable the inverter output sinusoidal voltage stability, dynamic response, robustness. Uses the current SPWM to control the inverter and design the closed-loop transfer function of system based on ITAE optimal model, get the controller parameters. To control the inverter with the optimized parameters, simulation results show the current inverter SPWM control system can adapt...
Fuzzy control has recently found extensive application for a wide variety of industrial systems and consumer products and has attracted the attention of many control researchers due to its model-free approach. In this paper, a reinforcement adaptive fuzzy control system based on Matlab's graphical user interface(GUI) is developed. In addition the reinforcement algorithm is presented, the binary reinforcement...
Fuzzy logic based control systems provide a simple and efficient method to control highly complex and imprecise systems. However, the lack of a simple hardware design that is capable of modifying the fuzzy controller's parameters to adapt for any changes in the operation environment, or behavior of the plant system limits the applicability of fuzzy based control systems in the automotive and industrial...
A fuzzy modeling approach based on on-line potential clustering is presented for a family of complex MIMO systems with severe nonlinearity and strong coupling such as a hovering submarine. The structure of the fuzzy model is defined as special group of If-Then rules with real constant consequents which is expressed as a feed-forward fuzzy neural network identified by on-line clustering and first order...
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