Showing papers on "PID controller published in 2009"

From PID to Active Disturbance Rejection Control

Abstract: Active disturbance rejection control (ADRC) can be summarized as follows: it inherits from proportional-integral-derivative (PID) the quality that makes it such a success: the error driven, rather than model-based, control law; it takes from modern control theory its best offering: the state observer; it embraces the power of nonlinear feedback and puts it to full use; it is a useful digital control technology developed out of an experimental platform rooted in computer simulations ADRC is made possible only when control is taken as an experimental science, instead of a mathematical one It is motivated by the ever increasing demands from industry that requires the control technology to move beyond PID, which has dominated the practice for over 80 years Specifically, there are four areas of weakness in PID that we strive to address: 1) the error computation; 2) noise degradation in the derivative control; 3) oversimplification and the loss of performance in the control law in the form of a linear weighted sum; and 4) complications brought by the integral control Correspondingly, we propose four distinct measures: 1) a simple differential equation as a transient trajectory generator; 2) a noise-tolerant tracking differentiator; 3) the nonlinear control laws; and 4) the concept and method of total disturbance estimation and rejection Together, they form a new set of tools and a new way of control design Times and again in experiments and on factory floors, ADRC proves to be a capable replacement of PID with unmistakable advantage in performance and practicality, providing solutions to pressing engineering problems of today With the new outlook and possibilities that ADRC represents, we further believe that control engineering may very well break the hold of classical PID and enter a new era, an era that brings back the spirit of innovations

Evaluation of DSP-Based PID and Fuzzy Controllers for DC–DC Converters

Abstract: In this paper, digital proportional-integral-derivative (PID)-type and fuzzy-type controllers are compared for application to the buck and boost dc-dc converters. Comparison between the two controllers is made with regard to design methodology, implementation issues, and experimentally measured performance. Design of fuzzy controllers is based on heuristic knowledge of converter behavior, and tuning requires some expertise to minimize unproductive trial and error. The design of PID control is based on the frequency response of the dc-dc converter. Implementation of linear controllers on a digital signal processor is straightforward, but realization of fuzzy controllers increases computational burden and memory requirements. For the boost converter, the performance of the fuzzy controller was superior in some respects to that of the PID controllers. The fuzzy controller was able to achieve faster transient response in most tests, had a more stable steady-state response, and was more robust under some operating conditions. In the case of the buck converter, the fuzzy controller and PID controller yielded comparable performances.

A model of postural control in quiet standing: robust compensation of delay-induced instability using intermittent activation of feedback control.

Abstract: The main purpose of this study is to compare two different feedback controllers for the stabilization of quiet standing in humans, taking into account that the intrinsic ankle stiffness is insufficient and that there is a large delay inducing instability in the feedback loop: 1) a standard linear, continuous-time PD controller and 2) an intermittent PD controller characterized by a switching function defined in the phase plane, with or without a dead zone around the nominal equilibrium state. The stability analysis of the first controller is carried out by using the standard tools of linear control systems, whereas the analysis of the intermittent controllers is based on the use of Poincare maps defined in the phase plane. When the PD-control is off, the dynamics of the system is characterized by a saddle-like equilibrium, with a stable and an unstable manifold. The switching function of the intermittent controller is implemented in such a way that PD-control is ‘off’ when the state vector is near the stable manifold of the saddle and is ‘on’ otherwise. A theoretical analysis and a related simulation study show that the intermittent control model is much more robust than the standard model because the size of the region in the parameter space of the feedback control gains (P vs. D) that characterizes stable behavior is much larger in the latter case than in the former one. Moreover, the intermittent controller can use feedback parameters that are much smaller than the standard model. Typical sway patterns generated by the intermittent controller are the result of an alternation between slow motion along the stable manifold of the saddle, when the PD-control is off, and spiral motion away from the upright equilibrium determined by the activation of the PD-control with low feedback gains. Remarkably, overall dynamic stability can be achieved by combining in a smart way two unstable regimes: a saddle and an unstable spiral. The intermittent controller exploits the stabilizing effect of one part of the saddle, letting the system evolve by alone when it slides on or near the stable manifold; when the state vector enters the strongly unstable part of the saddle it switches on a mild feedback which is not supposed to impose a strict stable regime but rather to mitigate the impending fall. The presence of a dead zone in the intermittent controller does not alter the stability properties but improves the similarity with biological sway patterns. The two types of controllers are also compared in the frequency domain by considering the power spectral density (PSD) of the sway sequences generated by the models with additive noise. Different from the standard continuous model, whose PSD function is similar to an over-damped second order system without a resonance, the intermittent control model is capable to exhibit the two power law scaling regimes that are typical of physiological sway movements in humans.

Hybrid Modulation for Dual-Active-Bridge Bidirectional Converter With Extended Power Range for Ultracapacitor Application

Abstract: In order to actively control the power flow between the load and ultracapacitor, a dual-active-bridge converter can be utilized. Conventional phase-shift modulation (PSM) has difficulties in working with a wide range of source voltage levels and load power levels. In addition, a traditional PI controller does not provide satisfactory behavior as the relation between the control variable and output voltage is nonlinear. In this paper, a hybrid modulation scheme is proposed to extend the power range of operation from 100% to 16.67% instead of 100% to 58.33% that is achieved by conventional PSM. A feedback-linearized controller is also designed to achieve a better dynamic response under various load conditions. The details of the modulation principle and controller design are given, and the experimental results verify the proposed modulation and control scheme.

Model-free control and intelligent PID controllers: towards a possible trivialization of nonlinear control?

Abstract: We are introducing a model-free control and a control with a restricted model for finite-dimensional complex systems. This control design may be viewed as a contribution to "intelligent" PID controllers, the tuning of which becomes quite straightforward, even with highly nonlinear and/or time-varying systems. Our main tool is a newly developed numerical differentiation. Differential algebra provides the theoretical framework. Our approach is validated by several numerical experiments.

Delay-dependent stability for load frequency control with constant and time-varying delays

Abstract: Load frequency control (LFC) requires transmission of remote measurements to the control center and of control signals from the control center to the plant. Constant delays exist in the dedicated communication channel and an open communication network introduces time-varying delays. Those delays would degrade the dynamic performance of LFC and even cause instability. This paper investigates the delay-dependent stability of the LFC scheme by adopting a delay-dependent criterion and linear matrix inequalities (LMIs). The maximal delay time which allows a power system with a LFC scheme embedded to retain stable is defined as the delay margin for stability analysis. A proportional-integral (PI) controller using the area control error (ACE) as input signal is employed in the LFC scheme. Special attention is paid to the relationship between the gains of PI controller and the delay margin. Case studies are carried out based on one-area and two-area LFC schemes to demonstrate the effectiveness of the criterion. Both constant and time-varying delays are considered. Moreover, the accuracy of the criterion used is also verified by simulation studies.

Design and simulation of self-tuning PID-type fuzzy adaptive control for an expert HVAC system

Abstract: The modelling, numerical simulation and intelligent control of an expert HVAC (heating, ventilating and air-conditioning) system having two different zones with variable flow-rate were performed by considering the ambient temperature in this study. The sub-models of the system were obtained by deriving heat transfer equations of heat loss of two zones by conduction and convection, cooling unit and fan. All models of the variable flow-rate HVAC system were generated by using MATLAB/SIMULINK, and proportional-integral-derivative (PID) parameters were obtained by using Fuzzy sets. For comfortable of people the temperatures of the two different zones were decreased to 5^oC from the ambient temperature. The successful results were obtained by applying self-tuning proportional-integral-derivative (PID)-type fuzzy adaptive controller if comparing with the fuzzy PD-type and the classical PID controller. The obtained results were presented in a graphical form.

Inertia-Free Spacecraft Attitude Tracking with Disturbance Rejection and Almost Global Stabilization

Abstract: We derive a continuous nonlinear control law for spacecraft attitude tracking of arbitrary continuously differentiable attitude trajectories based on rotation matrices. This formulation provides almost global stabilizability, that is, Lyapunov stability of the desired equilibrium of the error system as well as convergence from all initial states except for a subset for which the complement is open and dense. This controller thus overcomes the unwinding phenomenon associated with continuous controllers based on attitude representations, such as quaternions, that are not bijective and without resorting to discontinuous switching. The controller requires no inertiainformation,noinformation onconstant-disturbance torques,andonlyfrequencyinformation forsinusoidal disturbance torques. For slew maneuvers (that is, maneuvers with a setpoint command in the absence of disturbances), the controller specializes to a continuous, nonlinear, proportional–derivative-type, almost globally stabilizing controller, in which casethe torque inputs can be arbitrarily bounded a priori. For arbitrary maneuvers, we present an approximate saturation technique for bounding the control torques.

Friction Compensation of an $XY$ Feed Table Using Friction-Model-Based Feedforward and an Inverse-Model-Based Disturbance Observer

Abstract: Uncompensated friction forces compromise the positioning and tracking accuracy of motion systems. A unique tracking error known as quadrant glitch is the result of complex nonlinear friction behavior at motion reversal or near-zero velocity. Linear-feedback control strategies such as PID, cascade P/PI, or state-feedback control have to be extended with model- and nonmodel-based friction-compensation strategies to acquire sufficiently high path and tracking accuracy. This paper analyzes and validates experimentally three different friction-compensation strategies for a linear motor-based xy feed drive of a high-speed milling machine: (1) friction-model-based feedforward; (2) an inverse-model-based disturbance observer; and (3) the combination of both techniques. The friction models considered are as follows: a simple static-friction model and the recently developed generalized Maxwell-slip (GMS) model. GMS friction-model-based feedforward combined with disturbance observer almost completely eliminates the radial tracking error and quadrant glitches.

PID-Like Neural Network Nonlinear Adaptive Control for Uncertain Multivariable Motion Control Systems

Abstract: A mix locally recurrent neural network was used to create a proportional-integral-derivative (PID)-like neural network nonlinear adaptive controller for uncertain multivariable single-input/multi-output system. It is composed of a neural network with no more than three neural nodes in hidden layer, and there are included an activation feedback and an output feedback, respectively, in a hidden layer. Such a special structure makes the exterior feature of the neural network controller able to become a P, PI, PD, or PID controller as needed. The closed-loop error between directly measured output and expected value of the system is chosen to be the input of the controller. Only a group of initial weights values, which can run the controlled closed-loop system stably, are required to be determined. The proposed controller can update weights of the neural network online according to errors caused by uncertain factors of system such as modeling error and external disturbance, based on stable learning rate. The resilient back-propagation algorithm with sign instead of the gradient is used to update the network weights. The basic ideas, techniques, and system stability proof were presented in detail. Finally, actual experiments both of single and double inverted pendulums were implemented, and the comparison of effectiveness between the proposed controller and the linear optimal regulator were given.

An Autotuning Digital Controller for DC–DC Power Converters Based on Online Frequency-Response Measurement

Abstract: This paper describes a hardware-description-language-coded autotuning algorithm for digital PID-controlled DC-DC power converters based on online frequency-response measurement. The algorithm determines the PID controller parameters required to maximize the closed-loop bandwidth of the feedback control system while maintaining user-specified stability margins and integral-based no-limit-cycling criteria, as well as ensuring single-crossover-frequency operation and sufficiently high loop gain magnitude at low frequencies. Experimental results are provided for five different pulsewidth-modulated DC-DC converters, including a well-damped synchronous buck, a lightly damped synchronous buck with and without a poorly damped input filter, a boost operating in continuous-conduction mode, and a boost operating in discontinuous-conduction mode.

Application of self-tuning fuzzy pid controller on industrial hydraulic actuator using system identification approach

Abstract: In this paper, Self Tuning Fuzzy PID controller is developed to improve the performance of the electro-hydraulic actuator. The controller is designed based on the mathematical model of the system which is estimated by using System Identification technique. The model is performed in a linear discrete model to obtain a discrete transfer function for the system. Model estimation procedures are done by using System Identification Toolbox in Matlab. Data for model estimation is taken from experimental works. Fuzzy logic is used to tune each parameter of PID controller. Through simulation in Matlab by selecting appropriate fuzzy rules are designed to tune the parameters Kp, Ki, and Kd of the PID controller, the performance of the hydraulic system has improved significantly compare to conventional PID controller.

Position Control of DC Motor Using Genetic Algorithm Based PID Controller

Abstract: The aim of this paper is to design a position controller of a DC motor by selection of a PID parameters using genetic algorithm. The model of a DC motor is considered as a third order system. And this paper compares two kinds of tuning methods of parameter for PID controller. One is the controller design by the genetic algorithm, second is the controller design by the Ziegler and Nichols method. It was found that the proposed PID parameters adjustment by the genetic algorithm is better than the Ziegler & Nichols' method. The proposed method could be applied to the higher order system also.

Tuning of PID controller for an automatic regulator voltage system using chaotic optimization approach

Abstract: Despite the popularity, the tuning aspect of proportional–integral-derivative (PID) controllers is a challenge for researchers and plant operators. Various controllers tuning methodologies have been proposed in the literature such as auto-tuning, self-tuning, pattern recognition, artificial intelligence, and optimization methods. Chaotic optimization algorithms as an emergent method of global optimization have attracted much attention in engineering applications. Chaotic optimization algorithms, which have the features of easy implementation, short execution time and robust mechanisms of escaping from local optimum, is a promising tool for engineering applications. In this paper, a tuning method for determining the parameters of PID control for an automatic regulator voltage (AVR) system using a chaotic optimization approach based on Lozi map is proposed. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed chaotic optimization introduces chaos mapping using Lozi map chaotic sequences which increases its convergence rate and resulting precision. Simulation results are promising and show the effectiveness of the proposed approach. Numerical simulations based on proposed PID control of an AVR system for nominal system parameters and step reference voltage input demonstrate the good performance of chaotic optimization.

PM Synchronous Motor Speed Control Using Hybrid Fuzzy-PI With Novel Switching Functions

Abstract: Vector control is one of the standard techniques used for the control of a permanent magnet synchronous motor (PMSM). The outer speed loop in vector controlled PMSM drive greatly affects the drive performance. In order to combine the advantages of proportional plus integral (PI) and fuzzy controllers, hybrid fuzzy-PI controllers are used in which the output can either be the outputs of the two, i.e. the PI or fuzzy units being switched as per the predetermined speed errors or be a combination of the two outputs with separate weights assigned to them with online calculations for the weights from the speed errors. The former method based on switching often causes chattering effects, and later method demands larger execution time because of inclusion of separate switching algorithms. This paper reports the vector control of PMSM with hybrid fuzzy-PI speed controller with switching functions calculated based on the weights for both the controller outputs using the output of (a) only the fuzzy controller, (b) only the PI controller and (c) a combination of the outputs of both the controllers. These switching functions are very simple and effective and do not demand any extra computations to arrive at the hybrid fuzzy-PI controller outputs. These control algorithms have been simulated and also implemented on hardware with TMS320F2812 digital signal processor, and it is observed that the performance of the vector controlled PMSM drive with these hybrid fuzzy-PI speed controllers in terms of the response and torque ripples is very promising.

Evolutionary algorithms based design of multivariable PID controller

Abstract: In this paper, performance comparison of evolutionary algorithms (EAs) such as real coded genetic algorithm (RGA), modified particle swarm optimization (MPSO), covariance matrix adaptation evolution strategy (CMAES) and differential evolution (DE) on optimal design of multivariable PID controller design is considered. Decoupled multivariable PI and PID controller structure for Binary distillation column plant described by Wood and Berry, having 2 inputs and 2 outputs is taken. EAs simulations are carried with minimization of IAE as objective using two types of stopping criteria, namely, maximum number of functional evaluations (Fevalmax) and Fevalmax along with tolerance of PID parameters and IAE. To compare the performances of various EAs, statistical measures like best, mean, standard deviation of results and average computation time, over 20 independent trials are considered. Results obtained by various EAs are compared with previously reported results using BLT and GA with multi-crossover approach. Results clearly indicate the better performance of CMAES and MPSO designed PI/PID controller on multivariable system. Simulations also reveal that all the four algorithms considered are suitable for off-line tuning of PID controller. However, only CMAES and MPSO algorithms are suitable for on-line tuning of PID due to their better consistency and minimum computation time.

Design of a Data-Driven PID Controller

Abstract: Since most processes have nonlinearities, controller design schemes to deal with such systems are required. On the other hand, proportional-integral-derivative (PID) controllers have been widely used for process systems. Therefore, in this paper, a new design scheme of PID controllers based on a data-driven (DD) technique is proposed for nonlinear systems. According to the DD technique, a suitable set of PID parameters is automatically generated based on input/output data pairs of the controlled object stored in the database. This scheme can adjust the PID parameters in an online manner even if the system has nonlinear properties and/or time-variant system parameters. Finally, the effectiveness of the newly proposed control scheme is evaluated on some simulation examples, and a pilot-scale temperature control system.