816 research outputs found
PID control system analysis, design, and technology
Designing and tuning a proportional-integral-derivative
(PID) controller appears to be conceptually intuitive, but can
be hard in practice, if multiple (and often conflicting) objectives
such as short transient and high stability are to be achieved.
Usually, initial designs obtained by all means need to be adjusted
repeatedly through computer simulations until the closed-loop
system performs or compromises as desired. This stimulates
the development of "intelligent" tools that can assist engineers
to achieve the best overall PID control for the entire operating
envelope. This development has further led to the incorporation
of some advanced tuning algorithms into PID hardware modules.
Corresponding to these developments, this paper presents a
modern overview of functionalities and tuning methods in patents,
software packages and commercial hardware modules. It is seen
that many PID variants have been developed in order to improve
transient performance, but standardising and modularising PID
control are desired, although challenging. The inclusion of system
identification and "intelligent" techniques in software based PID
systems helps automate the entire design and tuning process to
a useful degree. This should also assist future development of
"plug-and-play" PID controllers that are widely applicable and
can be set up easily and operate optimally for enhanced productivity,
improved quality and reduced maintenance requirements
Fuzzy Inference System in Energy Demand Prediction
No abstract available
An expert system to perform on-line controller tuning
An expert system which tunes a Proportional-Integral-Derivative (PID) controller on-line for a single-input-single-output multiple-lag process with dead time is described. The expert system examines features of the previous transient responses and their corresponding sets of controller parameters. It determines a new set of controller gains to obtain a more desirable time response. This technique can be used to determine and implement a different set of PID gains for each operating regime and, once in steady state, the system can be used to find optimal parameters for load disturbance rejection. The expert system can be applied to any system of the specified form (aerospace, industrial, etc.) and can be expanded to include additional process models
Force reflecting joystick control for applications to bilateral teleoperation in construction machinery
This paper presents a simple and effective force reflecting joystick controller for applications to bilateral teleoperation in construction machinery. First, this controller is a combination of an advanced force reflecting gain tuner and two local adaptive controllers, master and slave. Second, the force reflecting gain tuner is effectively designed using recursive least square method and fuzzy logics to estimate directly and accurately the environmental characteristics and, consequently, to produce properly a force reflection. Third, the local adaptive controllers are simply designed using fuzzy technique and optimized using a smart leaning mechanism to ensure that the slave follows well any given trajectory while the operator is able to achieve truly physical perception of interactions at the remote site. An experimental master-slave manipulator is setup and real-time control tests are carried out under various environmental conditions to evaluate the effectiveness of the proposed controller
Fuzzy-tuned PID anti-swing control of automatic gantry crane
Anti-swing control is a well-known term in gantry crane control. It is designed to move the payload of gantry crane as fast as possible while the payload swing angle should be kept as small as possible at the final position. A number of studies have proposed anti-swing control using the well-known proportional, integral, derivative (PID) control method. However, PID controllers cannot always effectively control systems with changing parameters. Some studies have also proposed intelligent-based control including fuzzy control. However, the designers often have to face the problem of tuning many parameters during the design to obtain optimum performance. Thus, a lot of effort has to be taken in the design stage. In this paper Fuzzy-tuned PID controller design for anti-swing gantry crane control is presented. The objective is to design a practical anti-swing control which is simple in the design and also robust. The proposed Fuzzy-tuned PID utilizes fuzzy system as PID gain tuners to achieve robust performance to parameters variations in the gantry crane. A complex dynamic analysis of the system is not needed. PID controller is firstly optimized in MATLAB using a rough model dynamic of the system which is identified by conducting a simple open-loop experiment. Then, the PID gains are used to guide the range of the fuzzy outputs of the Fuzzy-tuned PID controllers. The experimental results show that the proposed anti-swing controller has satisfactory performance. In addition, the proposed method is straightforward in the design
Development of c-means Clustering Based Adaptive Fuzzy Controller for A Flapping Wing Micro Air Vehicle
Advanced and accurate modelling of a Flapping Wing Micro Air Vehicle (FW MAV)
and its control is one of the recent research topics related to the field of
autonomous Unmanned Aerial Vehicles (UAVs). In this work, a four wing
Natureinspired (NI) FW MAV is modeled and controlled inspiring by its advanced
features like quick flight, vertical take-off and landing, hovering, and fast
turn, and enhanced manoeuvrability when contrasted with comparable-sized fixed
and rotary wing UAVs. The Fuzzy C-Means (FCM) clustering algorithm is utilized
to demonstrate the NIFW MAV model, which has points of interest over first
principle based modelling since it does not depend on the system dynamics,
rather based on data and can incorporate various uncertainties like sensor
error. The same clustering strategy is used to develop an adaptive fuzzy
controller. The controller is then utilized to control the altitude of the NIFW
MAV, that can adapt with environmental disturbances by tuning the antecedent
and consequent parameters of the fuzzy system.Comment: this paper is currently under review in Journal of Artificial
Intelligence and Soft Computing Researc
Robust predictive tracking control for a class of nonlinear systems
A robust predictive tracking control (RPTC) approach is developed in this paper to deal with a class of nonlinear SISO systems. To improve the control performance, the RPTC architecture mainly consists of a robust fuzzy PID (RFPID)-based control module and a robust PI grey model (RPIGM)-based prediction module. The RFPID functions as the main control unit to drive the system to desired goals. The control gains are online optimized by neural network-based fuzzy tuners. Meanwhile using grey and neural network theories, the RPIGM is designed with two tasks: to forecast the future system output which is fed to the RFPID to optimize the controller parameters ahead of time; and to estimate the impacts of noises and disturbances on the system performance in order to create properly a compensating control signal. Furthermore, a fuzzy grey cognitive map (FGCM)-based decision tool is built to regulate the RPIGM prediction step size to maximize the control efforts. Convergences of both the predictor and controller are theoretically guaranteed by Lyapunov stability conditions. The effectiveness of the proposed RPTC approach has been proved through real-time experiments on a nonlinear SISO system
A review and analysis of control techniques in HVAC systems
Heating Ventilating and Air Conditioning (HVAC) systems are the core energy-absorbing equipment in buildings. Building HVAC system with effective control technique can greatly reduce energy consumption. The high demand for HVAC system Placing in buildings, using an effective control technique to decrease the energy absorbing of the equipment while meeting the thermal comfort demands in buildings are the most important goals of control designers. The different control methods for HVAC systems. This paper defines control techniques used in HVAC systems, MATLAB/simulation design and implementation of controller’s technique with the transfer function for the HVAC system.
Keywords-HVAC, PID controller, MPC Controller, Adaptive Controller, Fuzzy Controller
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