28 research outputs found

    Stability Control Structure of Hovercraft Prototype Utilising PID Controller

    Get PDF
    Hovercraft is a method of transportation as an option for clients who remain on the waterway and swamp surface. The issue with hovercraft is when dubious climate and natural condition, e.g. wind speed and wave tallness exasperate solidness of hovercraft to jeopardise the driver. We propose an approach to keep up adjust of the hovercraft by controlling the focal point of gravity (PG) to be determined position. The controller monitors the position of load to change the position. A 6-DOF IMU Sensor MPU 6050 was utilised to create information as an examination with setpoint. PID control strategy was employed. The test outcome demonstrates that the model of air cushion vehicle could keep its adjust the axis orientation of the roll in spite of the fact that it was less compelling in the pitch pivot direction

    Intelligent methods for complex systems control engineering

    Get PDF
    This thesis proposes an intelligent multiple-controller framework for complex systems that incorporates a fuzzy logic based switching and tuning supervisor along with a neural network based generalized learning model (GLM). The framework is designed for adaptive control of both Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) complex systems. The proposed methodology provides the designer with an automated choice of using either: a conventional Proportional-Integral-Derivative (PID) controller, or a PID structure based (simultaneous) Pole and Zero Placement controller. The switching decisions between the two nonlinear fixed structure controllers is made on the basis of the required performance measure using the fuzzy logic based supervisor operating at the highest level of the system. The fuzzy supervisor is also employed to tune the parameters of the multiple-controller online in order to achieve the desired system performance. The GLM for modelling complex systems assumes that the plant is represented by an equivalent model consisting of a linear time-varying sub-model plus a learning nonlinear sub-model based on Radial Basis Function (RBF) neural network. The proposed control design brings together the dominant advantages of PID controllers (such as simplicity in structure and implementation) and the desirable attributes of Pole and Zero Placement controllers (such as stable set-point tracking and ease of parameters’ tuning). Simulation experiments using real-world nonlinear SISO and MIMO plant models, including realistic nonlinear vehicle models, demonstrate the effectiveness of the intelligent multiple-controller with respect to tracking set-point changes, achieve desired speed of response, prevent system output overshooting and maintain minimum variance input and output signals, whilst penalising excessive control actions

    Intelligent methods for complex systems control engineering

    Get PDF
    This thesis proposes an intelligent multiple-controller framework for complex systems that incorporates a fuzzy logic based switching and tuning supervisor along with a neural network based generalized learning model (GLM). The framework is designed for adaptive control of both Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) complex systems. The proposed methodology provides the designer with an automated choice of using either: a conventional Proportional-Integral-Derivative (PID) controller, or a PID structure based (simultaneous) Pole and Zero Placement controller. The switching decisions between the two nonlinear fixed structure controllers is made on the basis of the required performance measure using the fuzzy logic based supervisor operating at the highest level of the system. The fuzzy supervisor is also employed to tune the parameters of the multiple-controller online in order to achieve the desired system performance. The GLM for modelling complex systems assumes that the plant is represented by an equivalent model consisting of a linear time-varying sub-model plus a learning nonlinear sub-model based on Radial Basis Function (RBF) neural network. The proposed control design brings together the dominant advantages of PID controllers (such as simplicity in structure and implementation) and the desirable attributes of Pole and Zero Placement controllers (such as stable set-point tracking and ease of parameters’ tuning). Simulation experiments using real-world nonlinear SISO and MIMO plant models, including realistic nonlinear vehicle models, demonstrate the effectiveness of the intelligent multiple-controller with respect to tracking set-point changes, achieve desired speed of response, prevent system output overshooting and maintain minimum variance input and output signals, whilst penalising excessive control actions.EThOS - Electronic Theses Online ServiceBiruni Remote Sensing Centre, LibyaGBUnited Kingdo

    Sliding Mode Control

    Get PDF
    The main objective of this monograph is to present a broad range of well worked out, recent application studies as well as theoretical contributions in the field of sliding mode control system analysis and design. The contributions presented here include new theoretical developments as well as successful applications of variable structure controllers primarily in the field of power electronics, electric drives and motion steering systems. They enrich the current state of the art, and motivate and encourage new ideas and solutions in the sliding mode control area

    Aeronautical engineering: A continuing bibliography with indexes (supplement 286)

    Get PDF
    This bibliography lists 845 reports, articles, and other documents introduced into the NASA scientific and technical information system in Dec. 1992. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

    10th EASN International Conference on Innovation in Aviation & Space to the Satisfaction of the European Citizens

    Get PDF
    This Special Issue book contains selected papers from works presented at the 10th EASN (European Aeronautics Science Network) International Conference on Innovation in Aviation & Space, which was held from the 2nd until the 4th of September, 2020. About 350 remote participants contributed to a high-level scientific gathering providing some of the latest research results on the topic, as well as some of the latest relevant technological advancements. Eleven interesting articles, which cover a wide range of topics including characterization, analysis and design, as well as numerical simulation, are contained in this Special Issue

    Management: A continuing bibliography with indexes

    Get PDF
    This biliography lists 919 reports, articles, and other documents introduced into the NASA scientific and technical information system in 1981
    corecore