INTELLIGENT INTEGRATION CONTROL OF ROTATING DISK VIBRATION

The rotating disk is a basic machine part that is u sed widely in industry. The motion equation is transformed into the dynamic equa tion in real modal space. The personating intelligent integration is introduced to improve the existing control method. These modes that affect the transverse vibration mainly are included to simulate the vibration of rotating disk, and two methods are applied separately on condition that the sensor and the ac tuator are collocated and non collocated. The results obtained by all sided si mulations show that the new method can obtain better control effect, especially when the sensor and the actuator are non collocated.

Expert S-surface control for autonomous underwater vehicles

S-surface control has proven to be an effective means for motion control of underwater autonomous vehicles(AUV).However there are still problems maintaining steady precision of course due to the constant need to adjust parameters,especially where there are disturbing currents.Thus an intelligent integral was introduced to improve precision.An expert S-surface control was developed to tune the parameters on-line,based on the expert system,it provides S-surface control according to practical experience and control knowledge.To prevent control output over-compensation,a fuzzy neural network was included to adjust the production rules to the knowledge base.Experiments were conducted on an AUV simulation platform,and the results show that the expert S-surface controller performs better than an S-surface controller in environments with currents,producing good steady precision of course in a robust way.

Controlling chaos based on a novel intelligent integral terminal sliding mode control in a rod-type plasma torch

An integral terminal sliding mode controller is proposed in order to control chaos in a rod-type plasma torch system.In this method, a new sliding surface is defined based on a combination of the conventional sliding surface in terminal sliding mode control and a nonlinear function of the integral of the system states. It is assumed that the dynamics of a chaotic system are unknown and also the system is exposed to disturbance and unstructured uncertainty. To achieve a chattering-free and high-speed response for such an unknown system, an adaptive neuro-fuzzy inference system is utilized in the next step to approximate the unknown part of the nonlinear dynamics. Then, the proposed integral terminal sliding mode controller stabilizes the approximated system based on Lyapunov＇s stability theory. In addition, a Bee algorithm is used to select the coefficients of integral terminal sliding mode controller to improve the performance of the proposed method. Simulation results demonstrate the improvement in the response speed, chattering rejection, transient response,and robustness against uncertainties.

Intelligent Integrated Control of Underactuated Mechanical Systems with Second-order Nonholonomic Constraints

This paper describes an intelligent integrated control of an acrobot, which is an underactuated mechanical system with second-order nonholonomic constraints. The control combines a model-free fuzzy control, a fuzzy sliding-mode control and a model-based fuzzy control. The model-free fuzzy controller designed for the upswing ensures that the energy of the acrobot increases with each swing. Then the fuzzy sliding-mode controller is employed to control the movement that the acrobot enters the balance area from the swing-up area. The model-based fuzzy controller, which is based on a Takagi-Sugeno fuzzy model, is used to balance the acrobot. The stability of the fuzzy control system for balance control is guaranteed by a common symmetric positive matrix, which satisfies linear matrix inequalities.

Ontology-Based Semantic Multi-agent Framework for Micro-grids with Cyber Physical Concept

The distributed hierarchical control based on multi-agent system(MAS) is the main control method of micro-grids.By allowing more flexible interactions between computing components and their physical environments,cyber physical system(CPS) presents a new approach for the distributed hierarchical engineering system,with micro-grids included.The object of this paper is to integrate the CPS concept with MAS technology and propose a new control framework for micro-grids.With the analysis of the operating mode and control method of micro-grids,the cyber physical control concepts of ontologybased semantic agent are discussed.Then an MAS-based architecture of cyber physical micro-grid system and an intelligent electronic device(IED) function structure are proposed.Finally,in order to operate and test the cyber physical micro-grid concept,an integrated simulation model is presented.

APPLICATION OF INTEGRATED INTELLIGENT METHODOLOGY TO PREDICT STABILITY AND SUPPORTING DECISION IN UNDERGROUND DRIFT

The present study shows that naturally the enormous engineering structure interaction with medium material, geometry or non linearity hazardous simulation experiment, response analysis and computing theory have been regarded as a high level question in the architecture, bridge, tunnel, hydraulic, etc engineering fields.Approaches an integrated intelligent methodology to predict stability and supporting decision in underground drift based on neural network modelling on coal rock mechanical problem is proposed.By the terms of the non linearity numerical simulation, this paper develops integrated intelligent methodology to research on the structure hazardous response strata soft rock drifts.

A Dependent-Chance Programming Model for Proactive Scheduling

Proactive scheduling based on expected value model is an effective method to develop robust schedules in consideration of minimizing project cost caused by deviations between realized and planed activity starting times.However,these schedules may be realized with low probabilities.In this paper,a novel model based on dependent-chance programming(DCP) is proposed,considering probability as well as solution robustness.A hybrid intelligent algorithm integrating stochastic simulation and genetic algorithm(GA)is designed to solve the proposed model.Moreover,a numerical example is conducted to reveal the effectiveness of the proposed model and the algorithm.

Smart Substation Integration Technology and Its Application in Distribution Power Grid

At present,smart substations use the IEC61850 standard based on the architectural framework of three layers and two networks to realize information digitization and advanced applications.Although the smart substation offers many improvements in design,equipment manufacturing,and construction,the intelligent devices used in smart substations are costly,and are also difficult to maintain since they are dispersed within a single unit.Functionality optimization and device integration,thus,have become important issues in smart substation development.This paper presents an integrated solution and implementation process for a smart substation system.In the process layer,an integrated intelligence component is developed that functions both as an intelligent terminal and a merging unit.In the bay layer,an integrated station-area protection measurement and control master device is designed to achieve such functions as protection,monitoring,control,fault recorder,and power quality monitoring.Finally,in the station control layer,an integrated information platform is established to bring together various system functions and to promote interactive sharing.Integration technology improves the economy and practicality of the smart substation,especially in a distribution power grid.