Showing papers on "PID controller published in 2002"

Process Control: Modeling, Design and Simulation

Abstract: Master process control hands on, through practical examples and MATLAB(R) simulationsThis is the first complete introduction to process control that fully integrates software tools-enabling professionals and students to master critical techniques hands on, through computer simulations based on the popular MATLAB environment. Process Control: Modeling, Design, and Simulation teaches the field's most important techniques, behaviors, and control problems through practical examples, supplemented by extensive exercises-with detailed derivations, relevant software files, and additional techniques available on a companion Web site. Coverage includes: Fundamentals of process control and instrumentation, including objectives, variables, and block diagrams Methodologies for developing dynamic models of chemical processes Dynamic behavior of linear systems: state space models, transfer function-based models, and more Feedback control; proportional, integral, and derivative (PID) controllers; and closed-loop stability analysis Frequency response analysis techniques for evaluating the robustness of control systems Improving control loop performance: internal model control (IMC), automatic tuning, gain scheduling, and enhancements to improve disturbance rejection Split-range, selective, and override strategies for switching among inputs or outputs Control loop interactions and multivariable controllers An introduction to model predictive control (MPC)Bequette walks step by step through the development of control instrumentation diagrams for an entire chemical process, reviewing common control strategies for individual unit operations, then discussing strategies for integrated systems. The book also includes 16 learning modules demonstrating how to use MATLAB and SIMULINK to solve several key control problems, ranging from robustness analyses to biochemical reactors, biomedical problems to multivariable control.

PID controllers: recent tuning methods and design to specification

Abstract: PID control is a control strategy that has been successfully used over many years. Simplicity, robustness, a wide range of applicability and near-optimal performance are some of the reasons that have made PID control so popular in the academic and industry sectors. Recently, it has been noticed that PID controllers are often poorly tuned and some efforts have been made to systematically resolve this matter. In this paper, a brief summary of PID theory is given, then some of the most-used PID tuning methods are discussed and some of the more recent promising techniques are explored.

System and method for highly phased power regulation using adaptive compensation control

Abstract: A highly phased power regulation (converter) system having an improved control feature is provided. A controller, such as a digital signal processor or microprocessor, receives digital information from a plurality of power conversion blocks and transmits control commands in response to the information. The controller is able to change the mode of operation of the system and/or re-phase the power blocks to accommodate a dynamic load requirement, occasions of high transient response or detection of a fault. A compensation block within the controller is used to regulate the output voltage and provide stability to the system. In one embodiment, the controller is implemented as a PID compensator controller. In another embodiment, a microprocessor is able to receive feedback on its own operation thus providing enabling the controller to anticipate and predict conditions by analyzing precursor data.

New results on the synthesis of PID controllers

Abstract: This paper considers the problem of stabilizing a first-order plant with dead time using a proportional-integral-derivative (PID) controller. Using a version of the Hermite-Biehler theorem that is applicable to quasi-polynomials, the complete set of stabilizing PID parameters is determined for both open-loop stable and unstable plants. The range of admissible proportional gains is first determined in closed form. For each proportional gain in this range, the stabilizing set in the space of the integral and derivative gains is shown to be either a trapezoid, a triangle or a quadrilateral. For the case of an open-loop unstable plant, a necessary and sufficient condition on the time delay is determined for the existence of stabilizing PID controllers.

PI/PID controller design based on direct synthesis and disturbance rejection

Abstract: A design method for PID controllers based on the direct synthesis approach and specification of the desired closed-loop transfer function for disturbances is proposed. Analytical expressions for PID controllers are derived for several common types of process models, including first-order and second-order plus time delay models and an integrator plus time delay model. Although the controllers are designed for disturbance rejection, the set-point responses are usually satisfactory and can be tuned independently via a set-point weighting factor. Nine simulation examples demonstrate that the proposed design method results in very good control for a wide variety of processes including those with integrating and/or nonminimum phase characteristics. The simulations show that the proposed design method provides better disturbance rejection than the standard direct synthesis and internal model control methods when the controllers are tuned to have the same degree of robustness.

Fuzzy logic controlled shunt active power filter for power quality improvement

Abstract: The simulation and experimental study of a fuzzy logic controlled, three-phase shunt active power filter to improve power quality by compensating harmonics and reactive power required by a nonlinear load is presented. The advantage of fuzzy control is that it is based on a linguistic description and does not require a mathematical model of the system. The fuzzy control scheme is realised on an inexpensive dedicated micro-controller (INTEL 8031) based system. The compensation process is based on sensing line currents only, an approach different from conventional methods, which require harmonics or reactive volt-ampere requirement of the load. The performance of the fuzzy logic controller is compared with a conventional PI controller. The dynamic behavior of the fuzzy controller is found to be better than the conventional PI controller. PWM pattern generation is based on carrierless hysteresis based current control to obtain the switching signals. Various simulation and experimental results are presented under steady state and transient conditions.

Design of PI and PID controllers with transient performance specification

Abstract: Proportional-integral-derivative (PID) controllers are widely used in industrial control systems because of the reduced number of parameters to be tuned. The most popular design technique is the Ziegler-Nichols method, which relies solely on parameters obtained from the plant step response. However, besides being suitable only for systems with monotonic step response, the compensated systems whose controllers are tuned in accordance with the Ziegler-Nichols method have generally a step response with a high-percent overshoot. In this paper, tuning methods for proportional-integral (PI) and PID controllers are proposed that, like the Ziegler-Nichols method, need only parameters obtained from the plant step response. The methodology also encompasses the design of PID controllers for plants with underdamped step response and provides the means for a systematic adjustment of the controller gain in order to meet transient performance specifications. In addition, since all the development of the methodology relies solely on concepts introduced in a frequency-domain-based control course, the paper has also a didactic contribution.

Techniques of model-based control

Abstract: Preface. Acknowledgements. 1. Introduction. 2. Continuous-Time Models. 3. One-Degree of Freedom Internal Model Control. 4. Two-Degree of Freedom Internal Model Control. 5. Model State Feedback Implementations of IMC. 6. PI and PID Parameters From IMC Designs. 7. Tuning and Synthesis of 1DF IMC for Uncertain Processes. 8 Tuning and Synthesis of 2DF IMC for Uncertain Processes. 9. Feedforward Control. 10. Cascade Control. 11. Output Constraint Control (Override Control). 12. Single Variable Inferential Control (IC). 13. Inferential Estimation Using Multiple Measurements. 14. Discrete-Time Models. 15. Identification: Basic Concepts. 16. Identification: Advanced Concepts. 17. Basic Model-Predictive Control. 18. Advanced Model-Predictive Control. 19. Inferential Model-Predictive Control. Appendix A. Review of Basic Concepts. Appendix B. Review of Frequency Response Analysis. Appendix C: Review of Linear Least-Squares Regression. Appendix D: Review of Random Variables and Random Processes. Appendix E: MATLAB and Control Toolbox Tutorial. Appendix F: SIMULINK Tutorial. Appendix G: Tutorial on IMCTUNE Software. Appendix H: Identification Software. Appendix I: SIMULINK Models for Projects. Index.

Modeling and robust control of winding systems for elastic webs

Abstract: The objective is to control a web transport system with winder and unwinder for elastic material. A physical modeling of this plant is made based on the general laws of physics. For this type of control problem, it is extremely important to prevent the occurrence of web break or fold by decoupling the web tension and the web velocity. Due to the wide-range variation of the radius and inertia of the rollers the system dynamics change considerably during the winding/unwinding process. Different strategies for web tension control and linear transport velocity control are presented. First, an H/sub /spl infin// robust control strategy which reduces the coupling between tension and velocity, is compared to the decentralized control strategy with proportional integral derivative (PID) controllers commonly used in the industry. Second, an H/sub /spl infin// robust control strategy with varying gains is shown to render the control more robust to the radius variations. Then, a linear parameter varying (LPV) control strategy with smooth scheduling of controllers is synthesized for different operating points and compared to the previous methods. Finally, this LPV control and the H/sub /spl infin// robust control strategy with varying gains are combined to give the best results on an experimental setup, for the rejection of the disturbances introduced by velocity variations and for the robustness to radius and inertia changes.

Robust adaptive numerical compensation for friction and force ripple in permanent-magnet linear motors

Abstract: This paper describes a robust adaptive compensation method for friction and force ripple present in the dynamics of permanent-magnet linear motors The method is used in ultraprecise positioning applications The compensation algorithm consists of a PID component and an adaptive component for estimating friction and force ripple The adaptive component is continuously refined on the basis of just prevailing input and output signals Computer simulations and real-time experimental results verify the effectiveness of the proposed scheme for high-precision motion trajectory tracking

From PID Technique to Active Disturbances Rejection Control Technique

Abstract: In this paper, advantages and disadvantages of classical PID are investigated from its basic principles. A new type controller Active Disturbances Rejection Controller(ADRC) with excellent characters is constructed via some links with especial functions,such as Tracking Differentiator(TD),Extended States Observer(ESO)and Nonlinear PID(NPID),which are based on the nonlinear control mechanisms. Furthermore, the new active disturbances rejection control technique is formed. The new controller possesses the following characteristics:the algorithm is simple; the adjustment of the parameters is easier.

Rapid Multitarget Acquisition and Pointing Control of Agile Spacecraft

Abstract: This paper describes the study results of developing an attitude control system for agile spacecraft which require rapid retargeting and fast transient settling. In particular, a nonlinear feedback control logic is developed for large-angle, rapid multi-target retargeting maneuvers subject to various physical constraints, including the actuator saturation, slew rate limit, control bandwidth limit, etc. Simulation results for an agile spacecraft equipped with control moment gyros demonstrate the effectiveness and robust performance of the proposed nonlinear feedback control system.

Control of an optical fiber scanner

Abstract: Controls for an optical scanner, such as a single fiber scanning endoscope (SFSE) that includes a resonating optical fiber and a single photodetector to produce large field of view, high-resolution images. A nonlinear control scheme with feedback linearization is employed in one type of control to accurately produce a desired scan. Open loop and closed loops controllers are applied to the nonlinear optical scanner of the SFSE. A closed loop control (no model) uses either phase locked loop and PID controllers, or a dual-phase lock-in amplifier and two PIDs for each axis controlled. Other forms of the control that employ a model use a frequency space tracking control, an error space tracking control, feedback linearizing controls, an adaptive control, and a sliding mode control.

Real-time gain tuning of PI controllers for high-performance PMSM drives

Abstract: In this paper, a new and practical real-time gain-tuning method for proportional plus integral (PI) controllers has been formulated and implemented, using the speed control of a permanent-magnet synchronous motor drive system as a testbed. While the novel strategy enhances the performance of traditional PI controller greatly and proves to be a completely model-free approach, it also preserves the simple structure and features of PI controllers. The essential idea is as follows: (1) according to the system dynamics to step variation, define a performance index to evaluate the system response; (2) based on the monotonous relationship between the performance index and an intermediate PI gain parameter, this latter parameter is estimated with a modified binary search algorithm in order to improve the performance index; and (3) finally, PI gains are calculated and renewed according to the estimated intermediate gain parameter. Experiments have been thoroughly carried out to test the proposed method under different conditions. Besides being simple and easy to implement for real-time applications, the proposed method also possesses features such as versatility, stability, and effectiveness.

PID controller modifications to improve steady-state performance of digital controllers for buck and boost converters

Abstract: The sensitivity of the analog-to-digital converter and inherent time delay in a digital controller can degrade the steady-state performance of a DC-DC power converter. Analog PID controllers were designed for prototype buck and boost converters and then implemented on a TI DSP. Three modifications to the digital PID controllers were investigated to improve their steady-state performance. The modifications were a dead zone, an averaging digital filter and two sets of gains. The digital controller monitors the output voltage error to determine if a modification should be employed to calculate the next duty cycle. Experimental results from both prototype converters indicates that a stable and accurate steady-state response can be obtained while maintaining a good transient response.

Speed control of induction motors using a novel fuzzy sliding-mode structure

Abstract: This paper presents a new approach to indirect vector control of induction motors. Two nonlinear controllers, one of sliding mode type and the other PI-fuzzy logic-based, define a new control structure. Both controllers are combined by means of an expert system based on Takagi-Sugeno fuzzy reasoning. The sliding-mode controller acts mainly in a transient state while the PI-like fuzzy controller acts in the steady state. The new structure embodies the advantages that both nonlinear controllers offer: sliding-mode controllers increasing system stability limits, and PI-like fuzzy logic based controllers reducing the chattering in permanent state. The scheme has been implemented and experimentally validated.

Sliding Mode Control Applied to Reconfigurable Flight Control Design

Abstract: Sliding mode control is applied to the design of a flight control system capable of operating with limited bandwidth actuators and in the presence of significant damage to the airframe and/or control effector actuators. Although inherently robust, sliding mode control algorithms have been hampered by their sensitivity to the effects of parasitic unmodeled dynamics, such as those associated with actuators and structural modes. It is known that asymptotic observers can alleviate this sensitivity while still allowing the system to exhibit significant robustness. This approach is demonstrated. The selection of the sliding manifold as well as the interpretation of the linear design that results after introduction of a boundary layer is accomplished in the frequency domain. The design technique is exercised on a pitch-axis controller for a simple short-period model of the High Angle of Attack F-18 vehicle via computer simulation. Stability and performance is compared to that of a system incorporating a controller designed by classical loop-shaping techniques.

Fuzzy speed and steering control of an AGV

Abstract: The development of techniques for lateral and longitudinal control of vehicles has become an important and active research topic in the face of emerging markets for advanced autonomous guided vehicles (AGVs) and mobile robots. In this respect, there has been much literature published, although not so much on the actual performance of such controllers in a practical setting. The primary focus in this paper is on the development and actual implementation of intelligent and stable fuzzy proportional derivative-proportional integral (PD-PI) controllers for steering and speed control of an AGV. The AGV used in this study is an electrically powered golf car, suitably modified for autonomous navigation and control. The use of fuzzy logic for control law synthesis, among other things, facilitates the incorporation of control heuristics, while guaranteeing stability, uncoupling steering control from speed control and providing for easy incorporation of a braking controller. Through experimentation, the designed controllers are demonstrated to be insensitive to parametric uncertainty, load and parameter fluctuations and, most importantly, amenable to real-time implementation. The performance of the proposed uncoupled direct fuzzy PD/PI control schemes for this particular outdoor AGV is also compared against conventional proportional-integral-derivative (PID) controllers. Experimental results demonstrate that the proposed fuzzy logic controllers, which are synthesized from a variable structure systems viewpoint, also outperform conventional PID schemes, particularly in tracking accuracy, steady-state error, control chatter and robustness.

Derivative filter is an integral part of PID design

Abstract: A PID controller is a second-order controller, and as such involves four parameters. However, many available tuning methods design only three parameters, and then use a default choice for the derivative filter factor. In this paper it is pointed out that for a PID controller of series form a default value for the derivative filter makes some sense, since it corresponds to a lead-lag controller. For PID controllers of ideal (or parallel) form default values are much less natural. The main purpose of the paper is to discuss the importance of model-based design methods, treating the derivative filter as an inherent part of the design. For example, it is illustrated how default choices for the derivative filter may lead to excessive control actions.

Statistical Process Adjustment for Quality Control

Abstract: Preface Process Monitoring versus Process Adjustment Modeling Discrete-Time Dynamical Processes ARIMA Time-Series Models Transfer Function Modeling Optimal Feedback Controllers Discrete-Time PID Controllers EWMA Feedback Controllers and the Run-to-Run Control Problem Recursive Estimation and Adaptive Control Analysis and Adjustment of Multivariate Processes Data Files and Spreadsheets Used in the Book Bibliography Index

Advanced proportional-integral-derivative tuning for integrating and unstable processes with gain and phase margin specifications

Abstract: Proportional−integral−derivative (PID) control is widely used to control stable processes; however, its application to integrating and unstable processes is less common. In the paper, simple formul...

Robust and optimal tuning of PI and PID controllers

Abstract: A general controller evaluation method based on three performance and robustness criteria is presented. It can be used to compare controllers of different structures, but also as a design method to find the optimal parameter setting for a controller of given structure. In this way optimal PI and PID controllers have been designed for a set of different plants. Clear regularities have then been noticed and utilised to formulate sets of tuning rules for non-oscillating stable plants and for plants with integral action. The rules demand very little plant knowledge but the resulting controllers are close to optimum. Furthermore, the user may adjust one or two of the tuning parameters and still get very good results. This means that the user has some freedom to manage the important trade-off between performance, robustness and control activity.

Development and implementation of a hybrid intelligent controller for interior permanent-magnet synchronous motor drives

Abstract: A hybrid neuro-fuzzy scheme for online tuning of a genetic-based proportional-integral (PI) controller for an interior permanent-magnet synchronous motor (IPMSM) drive is presented in this paper. The proposed controller is developed for accurate speed control of the IPMSM drive under various system disturbances. In this work, initially different operating conditions are obtained based on motor dynamics incorporating uncertainties. At each operating condition a genetic algorithm is used to optimize the PI controller parameters in a closed-loop vector control scheme. In the optimization procedure a performance index is developed to reflect the minimum speed deviation, minimum settling time and zero steady-state error. A fuzzy basis function network (FBFN) is utilized for online tuning of the PI controller parameters to ensure optimum drive performance under different disturbances. The proposed FBFN-based PI controller provides a natural framework for combining numerical and linguistic information in a uniform fashion. The proposed controller is successfully implemented in real time using a digital signal processor board DS 1102 for a laboratory 1-hp IPMSM. The effectiveness of the proposed controller is verified by simulation as well as experimental results at different dynamic operating conditions. The proposed controller is found to be robust for applications in an IPMSM drive.

Model reference neural network controller for induction motor speed control

Abstract: This paper proposes a novel robust speed control method for induction motor drives based on a two-layered neural network plant estimator (NNPE) and a two-layered neural network PI controller (NNPIC). The NNPE is used to provide a real-time adaptive estimation of the unknown motor dynamics. The widely used projection algorithm is used as the learning algorithm for these neural networks to automatically adjust the parameters of the NNPIC and to minimize the differences between the motor speed and the speed predicted by the NNPE. The simulation and experimental results demonstrate that the proposed robust control scheme can improve the performance of an induction motor drive and reduce its sensitivity to parameter variations and load disturbances.