Showing papers on "PID controller published in 1999"

Dual current control scheme for PWM converter under unbalanced input voltage conditions

Abstract: Voltage unbalance in a three-phase system causes performance deterioration of PWM power converters by producing 120 Hz voltage ripples in the DC link and by increasing the reactive power. To eliminate the DC link voltage ripple and the DC component of the reactive power, both positive- and negative-sequence currents should be controlled simultaneously, according to the paper by Rioual et al (1996). The authors used two synchronous reference frames: a positive-sequence current regulated by a proportional integral (PI) controller in a positive synchronous reference frame (SRF); and a negative-sequence current regulated by a PI controller in a negative SRF. In the positive SRF, which rotates counterclockwise, the positive sequence appears as DC, while the negative sequence appears as 120 Hz. In contrast, in the negative SRF, which rotates clockwise, the negative sequence appears as DC, while the positive sequence appears as 120 Hz. By deleting 120 Hz components using a notch filter in each SRF, one can measure positive- and negative-sequence currents separately, and use them for constructing two feedback controllers. Since the negative-sequence current is also controlled in its own SRF by a DC command, this approach yields better performance without increasing the control gain. Note that, since the controller is implemented by a software routine in the digital signal professor chip, using two SRFs does not require additional hardware. The authors demonstrated the effectiveness of the proposed control scheme by using computer simulation and experiments.

A Simple Event-Based PID Controller

Abstract: A simple event-based PID controller is presented. It is shown that it is possible to obtain large reductions in CPU utilization with only minor control performance degradation. Simulations on a double-tank process are presented.

A robust self-tuning scheme for PI- and PD-type fuzzy controllers

Abstract: Proposes a simple but robust model independent self-tuning scheme for fuzzy logic controllers (FLCs). Here, the output scaling factor (SF) is adjusted online by fuzzy rules according to the current trend of the controlled process. The rule-base for tuning the output SF is defined on error (e) and change of error (/spl Delta/e) of the controlled variable using the most natural and unbiased membership functions (MFs). The proposed self-tuning technique is applied to both PI- and PD-type FLCs to conduct simulation analysis for a wide range of different linear and nonlinear second-order processes including a marginally stable system where even the well known Ziegler-Nichols tuned conventional PI or PID controllers fail to provide an acceptable performance due to excessively large overshoot. Performances of the proposed self-tuning FLCs are compared with those of their corresponding conventional FLCs in terms of several performance measures such as peak overshoot, settling time, rise time, integral absolute error and integral-of-time-multiplied absolute error, in addition to the responses due to step set-point change and load disturbance and, in each case, the proposed scheme shows a remarkably improved performance over its conventional counterpart.

PID tuning for improved performance

Abstract: In this paper, a simple PID controller design method that achieves high performance for a wide range of linear self-regulating processes is proposed. Satisfactory responses can be expected for processes with various dynamics, including those with low- and high-order, small and large dead time, and monotonic and oscillatory responses. The method is developed based on a second-order plus dead time modeling technique and a closed-loop pole allocation strategy through the use of root-locus. Simulation examples and real-time experiments are given to show the effectiveness and flexibility of the controller in handling processes of different characteristics.

Autotuning of PID Controllers: A Relay Feedback Approach

Abstract: Introduction.- Relay Feedback Approach.- Systems with Unstable Zeros or Poles.- Multiloop SISO Control.-. Multivariable Composition.- Load Disturbances.- Process Nonlinearity.- Controller Monitoring.-. Application to Plantwise Control.- Guidelines of Autotune Procedure.- Appendix .

Design of PID controllers based on constrained optimization

Abstract: This paper presents a new design method for PID controllers based on optimization of load disturbance rejection with constraints on robustness to model uncertainties. The design also delivers parameters to deal with measurement noise and set point response. Thus, the formulation of the design problem captures four essential aspects of industrial control problems, leading to a constrained optimization problem which can be solved iteratively.

Tuning of a neuro-fuzzy controller by genetic algorithm

Abstract: Due to their powerful optimization property, genetic algorithms (GAs) are currently being investigated for the development of adaptive or self-tuning fuzzy logic control systems. This paper presents a neuro-fuzzy logic controller (NFLC) where all of its parameters can be tuned simultaneously by GA. The structure of the controller is based on the radial basis function neural network (RBF) with Gaussian membership functions. The NFLC tuned by GA can somewhat eliminate laborious design steps such as manual tuning of the membership functions and selection of the fuzzy rules. The GA implementation incorporates dynamic crossover and mutation probabilistic rates for faster convergence. A flexible position coding strategy of the NFLC parameters is also implemented to obtain near optimal solutions. The performance of the proposed controller is compared with a conventional fuzzy controller and a PID controller tuned by GA. Simulation results show that the proposed controller offers encouraging advantages and has better performance.

New methodology for analytical and optimal design of fuzzy PID controllers

Abstract: Describes a methodology for the systematic design of fuzzy PID controllers based on theoretical fuzzy analysis and, genetic-based optimization. An important feature of the proposed controller is its simple structure. It uses a one-input fuzzy inference with three rules and at most six tuning parameters. A closed-form solution for the control action is defined in terms of the nonlinear tuning parameters. The nonlinear proportional gain is explicitly derived in the error domain. A conservative design strategy is proposed for realizing a guaranteed-PID-performance (GPP) fuzzy controller. This strategy suggests that a fuzzy PID controller should be able to produce a linear function from its nonlinearity tuning of the system. The proposed PID system is able to produce a close approximation of a linear function for approximating the GPP system. This GPP system, incorporated with a genetic solver for the optimization, will provide the performance no worse than the corresponding linear controller with respect to the specific performance criteria. Two indexes, linearity approximation index (LAI) and nonlinearity variation index (NVI), are suggested for evaluating the nonlinear design of fuzzy controllers. The proposed control system has been applied to several first-order, second-order, and fifth-order processes. Simulation results show that the proposed fuzzy PID controller produces superior control performance to the conventional PID controllers, particularly in handling nonlinearities due to time delay and saturation.

Autotuning of PID Controllers

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Fuzzy logic based set-point weight tuning of PID controllers

Abstract: A methodology, based on fuzzy logic, for the tuning of proportional-integral-derivative (PID) controllers is presented. A fuzzy inference system is adopted to determine the value of the weight that multiplies the set-point for the proportional action, based on the current output error and its time derivative. In this way, both the overshoot and the rise time in set-point following can be reduced. The values of the proportional gain and the integral and derivative time constant are determined according to the well-known Ziegler-Nichols formula so that a good load disturbance attenuation is also assured. The methodology is shown to be effective for a large range of processes and is valuable for industrial settings since it is intuitive, it requires only a small extra computational effort, and it is robust with regard to parameter variations. The tuning of the parameters of the fuzzy module can be easily done by hand or by means of an autotuning procedure based on genetic algorithms.

Intelligent control of a class of wind energy conversion systems

Abstract: This paper discusses the control problem for a class of wind energy conversion systems (WECS). It first develops a detailed model and then compares four control algorithms based on conventional and intelligent control theories. A simple PI conventional controller for the exciter loop is carried out by using a first order model. When the system operating points change, the PI controller fails to provide sufficient damping or acceptable performance. Therefore both fuzzy voltage and fuzzy power regulators are introduced. Also a conventional adaptive pitch controller is proposed to adjust the pitch angle of the rotor blades in order to maximize the energy capture and reduce the mechanical loads. As an alternative to this controller, a neural network controller is also designed. Using the existing nonlinear wind model and the different control algorithms, the dynamic behavior of the controlled (WECS) is simulated. By selecting convenient wind data, the system characteristics such as its tracking performance, its robustness and its ability to recover from large disturbances are studied and discussed.

Nonlinear PID predictive controller

Abstract: A class of nonlinear PID controllers is derived for nonlinear systems using a nonlinear generalised predictive control (NGPC) approach. First, the disturbance decoupling ability of the NGPC is discussed. For a nonlinear system where the disturbance cannot be decoupled, a nonlinear observer is designed to estimate the offset. By selecting the nonlinear gain function in the observer, it is shown that the closed-loop system under optimal generalised predictive control with the nonlinear observer is asymptotically stable. It is pointed out that this composite controller is equivalent to a nonlinear controller with integral action. As a special case, for a nonlinear system with a low relative degree, the proposed nonlinear controller reduces to a nonlinear PI or PID predictive controller, which consists of a nonlinear PI or PID controller and a prediction controller. The design method is illustrated by an example nonlinear mechanical system.

Electromechanical Systems, Electric Machines, And Applied Mechatronics

Abstract: Introduction Mechatronics and Emerging Trends in Engineering Basic Foundations Engineering Computations Using MATLAB Analysis and Modeling of Dynamic Systems Using MATLAB: An Introduction Electromechanical System Dynamics, Energy Conversion, and Electromechanical Analogies Mathematical Models and System Dynamics Energy Conversion Electromechanical Analogies Introduction to Feedback Control of Electromechanical Systems Continuous-Time Electromechanical Systems and Analog PID Controllers Analog Control of Permanent-Magnet Direct Current Motors Electromechanical Systems with Digital PID Controllers Control of Permanent-Magnet Direct Current Motor using Digital Controller Introduction to Microelectronic Circuits, Power Electronic Devices, and Power Converters Operational Amplifiers Circuit Elements Power Amplifiers and Power Converters Direct-Current Machines Introduction Doubly Exited Transducer and Introduction to Fundamental of Alternating-Current and Direct-Current Electric Machines Separately Exited Direct-Current Machines Shunt-Connected Direct-Current Machines Series-Connected Direct-Current Machines Compound-Connected Direct-Current Electric Machines Permanent-Magnet Direct-Current Machines Modeling and Analysis of Permanent Magnet DC Generators Model Development and Analysis of Ward-Leonard Systems with DC Electric Machines Induction Machines Introduction Voltage, Flux Linkages, and Torque Equations for Two-Phase Induction Machines: Dynamics in the Machine Variables Mathematical Models of Two-Phase Induction Machines in the Arbitrary, Stationary, Rotor, and Synchronous Reference Frames Voltage, Flux Linkages, and Torque Equations for Three-Phase Induction Machines: Dynamics in the Machine Variables Mathematical Models of Three-Phase Induction Machnies in the Arbitrary, Stationary, Rotor, and Synchronous Reference Frames Power Converters and Control of Induction Machines Synchronous Machines Introduction Synchronous Reluctance Motors Permanent-Magnet Synchronous Machines Conventional Three-Phase Synchronous Machines: Dynamics in the Machine Variables and in the Rotor and Synchronous Reference Frames Stepper Motors Sensors Mechatronic Systems Introduction Mechatronic Systems with Permanent-Magnet DC Motors Analysis and Design of an Electric Drive with Experimental Verification Mechatronic Systems with DC Motors Mechatronic Systems with Induction Motors Mechatronic Systems with Permanent-Magnet Synchronous Motors Digital Control of Mechatronic Systems

Application of a multivariable feedback linearization scheme for rotor angle stability and voltage regulation of power systems

Abstract: This paper investigates the application of a nonlinear controller to the multi-input multi-output model of a system consisting of a hydraulic turbine and a synchronous generator. The controller proposed is based on a feedback linearization scheme. Its main goal is to control the rotor angle as well as the terminal voltage, to improve the system's stability and damping properties under large disturbances and to obtain good post-fault voltage regulation. The response of the system is simulated in the presence of a short-circuit at the terminal of the machine in two different configurations and compared to the performance of a standard IEEE type 1 voltage regulator, PSS and a PID speed regulator.

Autotuning and controller design for processes with small time delays

Abstract: A set of general expressions is derived from a single asymmetrical relay feedback test for online plant identification. The expressions also remain valid for an odd symmetrical limit cycle test method. Using the expressions, the exact parameters of open-loop stable and unstable first-order plus time delay (FOPDT) and second-order plus time delay (SOPDT) transfer function models may be obtained from simple measurements made on the limit cycle. The approach can also be used to identify transfer functions of integrating processes. Conditions for the existence of limit cycles in unstable FOPDT and SOPDT processes are derived. The design of controllers for these processes is then considered and a simple, but very effective, approach using standard forms with a variable zero is presented. The advantages of using PI-PD control, compared with conventional PID or PI-D control, particularly for unstable and integrating processes is clearly shown. Examples are given to illustrate the value of the proposed general identification method and the improved system performance provided by the proposed controllers.

Friction modeling, identification and compensation

Abstract: High-precision tracking requires excellent control of slow motion and positioning. Recent advances have provided dynamic friction models that represent almost all experimentally observed properties of friction. The state space formulation of these new mathematical descriptions has the property that the state derivatives are continuous functions. This enables the application of established theories for nonlinear systems. The existence of locally stable fixed points does not imply for nonlinear systems the absence of limit cycles (periodic orbits) or unstable solutions. Therefore, global properties of PI velocity and PID position control are analyzed using a passivity and Lyapunov based approach. These linear control laws are then extended by nonlinear components based on the friction model considered. The applications presented in this work are in the domains of mechatronics and machine-tools.

Application of Wiener model predictive control (WMPC) to a pH neutralization experiment

Abstract: pH control is recognized as an industrially important, yet notoriously difficult control problem. Wiener models, consisting of a linear dynamic element followed in series by a static nonlinear element, are considered to be ideal for representing this and several other nonlinear processes. Wiener models require little more effort in development than a standard linear step-response model, yet offer superior characterization of systems with highly nonlinear gains. These models may be incorporated into model predictive control (MPC) schemes in a unique way which effectively removes the nonlinearity from the control problem, preserving many of the favorable properties of linear MPC. In this paper, Wiener model predictive control (WMPC) is evaluated experimentally, and also compared with benchmark proportional integral derivative (PID) and linear MPC strategies, considering the effects of output constraints and modeling error.

GA-based fuzzy PI/PD controller for automotive active suspension system

Abstract: A genetic-algorithm (GA)-based fuzzy proportional-plus-integral-proportional-plus-derivative (PI/PD) controller is proposed for an automotive active suspension system (AASS). The fuzzy PI- and PD-type controllers are combined to cope with the different road conditions. By using the merit of GAs, the optimal decision-making rules for both types of controllers are constructed. The real-time simulation results demonstrate that the fusion of GAs and fuzzy controller for an AASS can provide passengers much more ride comfort.

A Simple Multiloop Tuning Method for PID Controllers with No Proportional Kick

Abstract: A simple tuning method for multiloop PID controllers will be presented in this article. The method is suited for PID algorithms with no proportional and derivative kick. This tuning method is derived from a controller synthesis method with a control performance specification of 5% overshoot on servo response. Depending on the interaction natures of the multiloop systems, tuning based on the diagonal elements of the model or further detuning may be necessary. For systems with a relative gain array [RGA(λii)] < 1, a detuning factor based on this information is proposed. The information needed for controller tuning purposes is the dynamic model parameters of the diagonal elements and the process gain information of the off-diagonal elements. The tuning method procedure is very simple and straightforward, utilizing only nth identification tests with n as the number of the interacting control loops. The tuning method can easily be applied to various industrial situations with almost no need for a priori proces...

A study on the robustness of a PID-type iterative learning controller against initial state error

Abstract: In this paper, the effect of initial state error in the iterative learning control (ILC) system is studied. First, the previous result that the performance of D-type ILC algorithm can be improved by adding a P-term of error in the algorithm is generalized to PID-type algorithm. Then, robustness is investigated against the initial state error of the generalized ILC algorithm. It is also shown that the trend of error reduction can be effectively controlled by tuning gains of the proposed controller. In order to confirm validity of the proposed ILC algorithm, several examples are presented.

A design of self-tuning PID controllers using a genetic algorithm

Abstract: A self-tuning PID controller design scheme is proposed, which is able to deal with systems with unknown or time-varying parameters. The proposed scheme is derived based on the relationship between PID control and generalized minimum variance control (GMVC) laws. Furthermore, a suitable set of some user-specified parameters included in the GMVC criterion is sought by using a genetic algorithm recursively. A numerical simulation example shows the effectiveness of the newly proposed control scheme.

Speed control of two-inertia system by PI/PID control

Abstract: Our purpose is to develop systematic analysis and design methods for a two-inertia system. A conventional PI speed control system with a torsional load is redesigned, and the damping characteristic of the system is derived and analyzed. It is shown that the dynamic characteristic of the system strongly depends on the inertia ratio of load to motor. Three kinds of typical pole assignments with identical radius/damping coefficient/real-part are applied and compared, and the merits of each pole assignment design are concluded. Furthermore, for small inertia ratio, we show how to improve the damping by a derivative feedback of motor speed.

Performance optimization of a fast tool servo for single-point diamond turning machines

Abstract: This paper describes a new, fast tool servo system designed for fabrication of nonrotationally symmetric components using single-point diamond turning machines. A prototype device, designed for flexible interfacing to typical machine tool controllers, is described, along with performance testing data of tilted flat and off-axis conic sections. Techniques for controlling the piezoelectric actuator to less than 1% error are discussed. The performance of a standard integral controller shows a significant error due to hysteresis in the actuator. The effects of the hysteresis were reduced by implementing two control schemes, an optimized PID controller and a technique that utilizes a dynamic compensator module in conjunction with the linear controller. The compensator samples the hysteretic voltage/displacement relationship in real time and modifies the effective gain accordingly. Experimental implementation results in an 80% reduction in the motion error caused by hysteresis, but peak-to-valley errors are limited by side effects from the compensation.

Theory and Applications of the Robust Cross-Coupled Control Design

Abstract: The cross-coupled control (CCC) has been recognized as an efficient motion controller that reduces contouring errors, but theoretical analysis of it is lacking, and there is no systematic design approach for obtaining a CCC system with guaranteed control performance. Consequently, the compensators C in CCC are commonly implemented in a PID structure and their contouring accuracy is usually degraded in real applications under different operating conditions. In an attempt to overcome the CCC design limitations described above, this paper introduces a robust CCC design based on a novel formulation: the contouring error transfer function (CETF), leading to an equivalent formulation as in the feedback control design problem. Then, methods in robust control design can be readily employed to achieve robust CCC with specified stability margins and guaranteed contouring performance. Furthermore, the proposed design has been verified as being internally stable. All provided experimental results indicate that the proposed robust CCC design consistently renders satisfactory contouring accuracy under different operating conditions.