Guang Ren

Optimization design of TS-PID fuzzy controllers based on genetic algorithms

TS-PID fuzzy controllers are a class of Tagagi-Sugeno (TS) fuzzy controllers whose rule consequences employ PID expressions. The analytical model of typical TS-PID fuzzy controllers is proposed in this paper. It can be used to develop a fast and precise control algorithm in both optimal design and practical use. The essential character of a typical TS-PID fuzzy controller is investigated to be a nonlinear PID controller. Based on genetic algorithms (GAs), an optimal design method of TS-PID fuzzy controllers is discussed in detail by means of the analytical model. The simulation results of a marine control system show that a TS-PID fuzzy controller designed via GAs has a good performance.

Design and Stability Analysis of Fuzzy Switching PID Controller

Fuzzy switching PID (FS-PID) controller proposed in this paper consists of a TS-PID controller and a conventional PID controller which switching according to the premise variable in operating regime rules. This technique integrates the advantages of both the fuzzy controller and PID controller but eliminates their disadvantages. FS-PID controller provides good performance during the transient phase and alleviates oscillatory when system approaching equilibrium point. The switching between two controllers is governed through fuzzy rules. It results in smooth switching between two operating regimes. The stability condition of closed-loop systems is derived through passivity theorem. The application to the third-order linear system demonstrates that, by using FS-PID controller, the system performances are improved and the system also exhibits stability and smoothness

Studies on RBF neural-network controller with application to ship control

We propose a radial basis function (RBF) neural network controller for ship control. The main feature of the controller is to combine a fuzzy controller with neural networks. We transform a set of fuzzy inference rules into an RBF neural-network controller, utilizing the nonlinear mapping and learning ability of the neural networks. We present the design method of the controller based on the RBF neural networks and fuzzy rules, and discuss the characteristics of the controller. We use MATLAB as a simulation language. Simulation tests are conducted with different parameters, and the results are given in the paper. We introduce a ship control test bed. The controller is installed on the ship control test bed, and sea trials are conducted in the open sea. The sea trial results are also shown in the paper.

Detecting Community Structures in Networks by Label Propagation with Prediction of Percolation Transition

Though label propagation algorithm (LPA) is one of the fastest algorithms for community detection in complex networks, the problem of trivial solutions frequently occurring in the algorithm affects its performance. We propose a label propagation algorithm with prediction of percolation transition (LPAp). After analyzing the reason for multiple solutions of LPA, by transforming the process of community detection into network construction process, a trivial solution in label propagation is considered as a giant component in the percolation transition. We add a prediction process of percolation transition in label propagation to delay the occurrence of trivial solutions, which makes small communities easier to be found. We also give an incomplete update condition which considers both neighbor purity and the contribution of small degree vertices to community detection to reduce the computation time of LPAp. Numerical tests are conducted. Experimental results on synthetic networks and real-world networks show that the LPAp is more accurate, more sensitive to small community, and has the ability to identify a single community structure. Moreover, LPAp with the incomplete update process can use less computation time than LPA, nearly without modularity loss.

Marine Main Engine Remote Control System with redundancy CAN bus based on distributed processing technology

For middle-speed and four-stroke marine diesel engine, a new Main Engine Remote Control System based on distributed processing and dual-redundant CAN network communication technology was presented. It includes engine control unit, indicating panel unit, engine safety unit, main engine interface, digital governor unit and distributed processing unit. System data can be exchanged by dual-redundant CAN network. The distributed processing unit is independent in physics completely, so it has less impact on other units when some units malfunctioned. The communication of system units is designed by open communication protocol of CAN, it can self-test and troubleshoot. The System has function of self-insurance when loss power, and can delay shut-down when loss of air. Its operating mode and man-machine interface are convenient and friendly.

Backstepping Approach to Ship Steering Autopilot based on Fuzzy Adaptive Control

For the nonlinear Norbin ship model, this paper provides a new fuzzy adaptive control algorithm based on the backstepping approach and the approximation capability of the fuzzy system constructed by radial basis function (RBF). Employing the Taylor linearization technique, the algorithm can on-line tune all the parameters of RBF (connection weights, centers and widths), thereby the approximation error can be reduced greatly. Moreover, the robust controller is employed to dispel the effect of the approximation error. The asymptotical stability of the closed-loop control system is proved in the sense of Lyapunov function. At last, the simulating results show that the proposed algorithm has better adaptive ability than traditional PID control algorithm

Generalization of label propagation algorithm in complex networks

We generalize the label propagation algorithm in complex networks to weighted networks by weighting the label propagation rule and the termination condition of label propagation algorithm. Experiments on computer-generated networks and real-world networks are carried out to compare the generalized algorithm with original algorithm. The results show the generalized algorithm is accurate, and the number of iteration is less. The weighed label propagation algorithm is applied to fault classification, and the good classification results are obtained.

Fault Diagnosis for Marine Engine System Based on Complex Network Cluster Method

Fault diagnosis can be achieved by the cluster analysis process. We give a complete similarity measurement method and a cluster criterion function defined by modularity increment in complex network community detection. An agglomerative cluster method is proposed and the diagnosis rules are extracted to fault diagnosis for the marine engine system. Using the samples collected from self-manufactured marine engine room simulator, fault diagnosis simulation experiment is carried out to verify the algorithm performance. The results show that the method is accurate and less time-consuming, and is able to recognize the fault pattern which does not exist in the fault history data.

Stability Analysis of Discrete T-S Fuzzy Systems with Piecewise Fuzzy Lyapunov Approach

For the conservatism problem of stability analysis of fuzzy systems with the common Lyapunov approach and the fuzzy Lyapunov approach, this paper proposes a new sufficient condition to check the stability of open-loop discrete T-S fuzzy systems based on the definition of the discrete piecewise fuzzy Lyapunov function. This condition only needs satisfying the condition of fuzzy Lyapunov approach in each maximal overlapped-rule group. Therefore, the proposed condition not only is less conservative and difficult than former two approaches, but also includes them as special cases. A simulation example shows the approach is effective and advantageous

ANTI-WINDUP SCHEMES FOR NONLINEAR ACTIVE DISTURBANCE REJECTION CONTROL IN MARINE STEAM TURBINE

Nonlinear characteristics are very common in marine steam turbine, such as control input constraints and external disturbances. Based on the active disturbance rejection control (ADRC), an anti-windup scheme is proposed to eliminate the undesired effects of nonlinear characteristics in the control system. In this scheme, firstly, a method of setting parameter is designed for nonlinear active disturbance rejection control (NLADRC). Then, two kinds of anti-windup schemes are proposed in this paper for NLADRC in the presence of control input constraints and external disturbances. Finally, simulation study is carried out for a first order delay object with actuator constraints, simulation results show that both schemes can achieve good anti-windup performance. The method is further extended to marine steam turbine control, with simulation results demonstrating that both methods have their own advantages.