Showing papers on "PID controller published in 1992"
TL;DR: A survey of the different adaptive techniques, the underlying process models and control designs and an overview of industrial adaptive single-loop controllers are given.
641 citations
TL;DR: In this article, the authors proposed an alternative approach that avoids this problem by using classical frequency response methods and showed that there is a minimum reset time for the integrator/dead time process below which reasonable closed loop damping coefficients cannot be achieved.
Abstract: Chien and Fruehauf proposed an internal model control (IMC) approach to selecting the tuning constants for a PI controller in a process consisting of a pure integrator and a dead time. The only tuning parameter to be specified was the closed loop time constant. We point out that the IMC approach can lead to poor control unless care is taken in selecting the closed loop time constant. An alternative approach that avoids this problem is suggested. The proposed method uses classical frequency response methods. We show that there is a minimum reset time for the integrator/dead time process below which reasonable closed loop damping coefficients cannot be achieved. We also show that, for a given reset time, there is an optimum controller gain that minimizes the maximum closed loop log modulus. Equations for the calculation of the optimum reset time and the optimum gain of a PI controller for the control of an integrator/dead time process are developed
401 citations
TL;DR: This paper describes some features that may be included in the next generation of PID controllers, which seem technically feasible with the increased computing power that is now available in single-loop controllers.
381 citations
TL;DR: In this paper, a nonlinear internal model control (NIMC) strategy based on neural network models is proposed for SISO processes, which includes time delay compensation in the form of a Smith predictor and ensures offset-free performance.
286 citations
TL;DR: The techniques of genetic algorithms are proposed as an alternative means of tuning digital PID controllers for complex multivariable plants with highly interactive dynamics.
Abstract: The techniques of genetic algorithms are proposed as an alternative means of tuning digital PID controllers. This use of genetic algorithms is particularly attractive because the same basic approach can always be readily used, even in the case of digital PID controllers for complex multivariable plants with highly interactive dynamics.
164 citations
TL;DR: The experimental results show the excellent servo and regulatory performance of the nonlinear controller in the presence of modeling and observer initialization errors and active manipulated input constraints and its tuning is much easier.
Abstract: This work studies the experimental application of the globally linearizing control (GLC) method to a batch polymerization reactor. The nonlinear controller is implemented on a microcomputer to start up the reactor and then track a precalculated optimal temperature profile. The reactor temperature is controlled by manipulating two coordinated inputs: power to an electrical heat and cooling water flow rate. A reduced-order observer is used to estimate the concentration of initiator and monomer. Systematic tuning guidelines are proposed for the nonlinear control method. The experimental results show the excellent servo and regulatory performance of the nonlinear controller in the presence of modeling and observer initialization errors and active manipulated input constraints. Furthermore, in comparison to a conventional PID controller, the performance of the nonlinear controller is significantly superior, and its tuning is much easier.
156 citations
TL;DR: In this paper, a predictive PI (proportional integral) controller with dead-time compensation is described, which can be considered as a special case of the Smith predictor or the Morari-Zafiriou IMC.
Abstract: A predictive PI (proportional-integral) controller with dead-time compensation is described. Its advantage compared with previous dead-time compensating controllers is that although it also contains five parameters, only three are adjusted by the operator, namely, the gain, the integral time and the dead time. The controller is also suited for processes with varying dead times. Conceptually, the new controller can be considered as a special case of the Smith predictor or the Morari-Zafiriou IMC. >
121 citations
TL;DR: Designs of both open- and closed-loop controllers of electrically stimulated muscle that explicitly depend on a nonlinear mathematical model of muscle input-output properties are presented and evaluated and an open-loop nonlinear compensator was tested in an animal model.
Abstract: Designs of both open- and closed-loop controllers of electrically stimulated muscle that explicitly depend on a nonlinear mathematical model of muscle input-output properties are presented and evaluated. The muscle model consists of three factors: a muscle activation dynamics factor, an angle-torque relationship factor, and an angular velocity torque relationship factor. These factors are multiplied to relate output torque to input simulation and joint angle. An experimental method for the determination of the parameters of this model was designed, implemented, and evaluated. An open-loop nonlinear compensator, based upon this model, was tested in an animal model. Its performance in the control of joint angle in the presence of a known load was compared with a PID (proportional-integral-derivative) controller, and with a combination of the PID controller and the nonlinear compensator. The results are presented. >
109 citations
TL;DR: A network architecture for process control is described, and quantitatively how the weights on the connections in the network can be adjusted to yield the desired control action is explained.
108 citations
TL;DR: A fuzzy control system to provide closed-loop control of mean arterial pressure (MAP) in postsurgical patients in a cardiac surgical intensive care unit setting by regulating sodium nitroprusside (SNP) infusion is discussed.
Abstract: A fuzzy control system to provide closed-loop control of mean arterial pressure (MAP) in postsurgical patients in a cardiac surgical intensive care unit setting by regulating sodium nitroprusside (SNP) infusion is discussed. The fuzzy controller, originally expert-system-based, was analytically converted to ten nonfuzzy control algorithms, which reduced execution time dramatically. The core of the control algorithms was a nonlinear proportional-integral (PI) controller whose proportional gain and integral gain adjusted continuously according to error and rate change of error of the process output. The gains become larger when process output was far from desired setpoint and smaller when process output was close to desired setpoint, resulting in more dynamic and stable control performance than the regular PI controller, especially when a linear process with time-delay or a nonlinear process was involved. The control algorithms, encoded in C programming language, were implemented to control MAP in patients. Preliminary clinical results showed that the average percentage of time in which MAP stayed between 90% and 110% of the MAP setpoint was 89.31%, with a standard deviation of 4.96%. These were calculated based on 12 patient trials, with total trial time of 95 and 13 min. >
105 citations
TL;DR: In this paper, the design and implementation of a new adaptive nonlinear predictive controller is presented using a general nonlinear model and variable transformations. The controller is updated on-line without recalculating the controller gain matrix, which involves a matrix inversion.
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TL;DR: In this paper, the authors describe how to use a neural network which receives PID inputs to be a controller and operate as a PID controller to save on retraining and provide other efficiencies in control.
Abstract: PID controllers form a large proportion of controllers in use in many controlled systems today. This application describes how to use a neural network which receives PID inputs to be a controller and operate as a PID controller to save on retraining and provide other efficiencies in control. Also shown is the user selectability between PID conventional controllers and Neural Network controllers.
TL;DR: A simple method for the automatic tuning of PID controllers in closed loop is proposed, where the amplitude and frequency of the oscillation are estimated and the control parameters are adjusted iteratively such that the closed loop transfer function from the controller reference to the process output attains a specified amplitude at the oscillations frequency.
TL;DR: In this article, the design of a static voltampere reactive (VAr) controller using a novel adaptive scheme is investigated, which makes use of self-tuning proportional-integral-derivative (PID) control, can provide better damping characteristics than a fixed-gain PID control SVC over a wide range of operating conditions.
Abstract: Design of a static voltampere reactive (VAr) controller (SVC) using a novel adaptive scheme is investigated. The proposed controller, which makes use of self-tuning proportional-integral-derivative (PID) control, can provide better damping characteristics than a fixed-gain PID control SVC over a wide range of operating conditions. The system considered is a synchronous generator connected to an infinite bus through a double circuit transmission line. Digital simulations of the system following a three-phase fault under different loading conditions were performed to demonstrate the robustness and effectiveness of the controller. >
08 Mar 1992
TL;DR: A self-tuning fuzzy controller is implemented for a gas-fired water heater using a self- Tuning technique based on fuzzy metarules to replace a proportional-integral-derivative control algorithm with a fuzzy controller.
Abstract: Using a self-tuning technique based on fuzzy metarules, the authors implemented a self-tuning fuzzy controller for a gas-fired water heater. They describe the implementation and its simulation results. The problem was to replace a proportional-integral-derivative (PID) control algorithm with a fuzzy controller, using initial guesses as to the fuzzy membership functions and rules; to tune the fuzzy controller for optimum performance; and to compare the performance results to those from a PID controller. When tuned for a given set of operating conditions, the fuzzy controller matches or exceeds the PID controller performance. >
TL;DR: In this article, a theoretical analysis of active control of nonlinear acoustic instabilities in combustion chambers is developed, where the authors start with a generalized wave equation that describes the dynamic behavior of second-order nonlinear oscillations with distributed feedback actions.
Abstract: A theoretical analysis of active control of nonlinear acoustic instabilities in combustion chambers is developed in this article. The formulation starts with a generalized wave equation that describes the dynamic behavior of second-order nonlinear oscillations with distributed feedback actions. Control inputs are provided by the burning of the injected seconday fuel in the chamber, with its instantaneous mass flow rate modulated by a proportionalplus-integral (PI) controller located between the pressure sensor and the fuel injection mechanism. Various nonlinear stability characteristics, including the existence and stability of limit cycles, are studied analytically using the method of time averaging. In addition, an optimization procedure is developed for selecting controller gains. Nomenclature Anij = parameters associated with nonlinear acoustic coupling a = speed of sound in mixture Bnij = parameters associated with nonlinear acoustic coupling b = spatial distribution of burning of control fuel, Eq. (5b), Cv - constant-volume specific heat for two-phase mixture c = amplification factor of sensor output Dni = linear parameters, Eq. (11) Eni = linear parameters, Eq. (11) e - error signal between desired response and actual measurement
01 Jan 1992
TL;DR: The performance of all strategies, large and small, are at the mercy of the sensor and valve systems to which they are connected, and poor valve choices and/or confused sensor information will render ineffective even the best of control systems.
Abstract: Distillation control philosophy and practice vary greatly. Some control systems are designed using simple PID controllers whereas others are designed around sophisticated model based control algorithms. Some strategies are implemented in state-of-the-art distributed control systems (DCS), whereas others use a collection of more conventional electronic and pneumatic control devices. Distillation control strategies vary in cost and complexity, yet the performance of all strategies, large and small, are at the mercy of the sensor and valve systems to which they are connected. Poor valve choices and/or confused sensor information will render ineffective even the best of control systems.
Patent•
16 Sep 1992
TL;DR: In this article, an autotuning procedure for a PID-type controller employs a low frequency sine wave as an exciting input and models the controlled system as a second order linear system.
Abstract: An autotuning procedure for a PID-type controller employs a low frequency sine wave as an exciting input and models the controlled system as a second order linear system. The system is tuned to a desired damping ratio by following an overdamped trajectory, in closed loop gain and phase lag space, to the target closed loop gain and phase lag values on a locus of a desired damping ratio as based on that modeling system.
24 Jun 1992
TL;DR: In this paper, the results of an experimental work on the lateral control of a full-scaled vehicle are reported, and two control algorithms are tested, a simple PID controller to serve as the baseline, and an optimal preview controller, which was developed to improve the tracking performance, ride quality and robustness of the system.
Abstract: The results of an experimental work on the lateral control of a full-scaled vehicle are reported in this paper. Two control algorithms were tested, a simple PID controller to serve as the baseline, and an optimal preview controller, which was developed to improve the tracking performance, ride quality and robustness of the system. The theoretical development and the experimental setup are briefly discussed, followed by some experimental results.
01 May 1992
TL;DR: A connectionist approach to the problem of PID autotuning is proposed, based on integral measures of the step response, which gives a major reduction in the number of iterations needed to achieve a local minimum.
Abstract: A connectionist method for autotuning PID controllers is proposed. This technique, which is applicable both in open and in closed loops, employs multilayer perceptrons to approximate the mappings between the identification measures of the plant and the optimal PID values. The neutral network controller is designed to adapt to changing system structures and parameter values online. To achieve this objective, the network weighting coefficients are determined during an offline training phase. Simulation results are presented to illustrate the properties of the controller. One of the important aspects of neural networks is the convergence characteristic of this training phase. In the proposed approach, multilayer perceptrons are employed for nonlinear function approximation. As a consequence, the neurons have a linear activation function in their output layer. It is shown that a new learning criterion can be defined for this class of multilayer perceptrons, which is commonly found in control systems applications. Comparisons of the standard and the reformulated criteria, using different training algorithms, show that the new formulation achieves a significant reduction in the number of iterations needed to converge to a local minimum.
TL;DR: In this paper, the authors present a new method for tuning PID controllers based on placement of a few dominant poles, which makes it possible to consider specifications on set point response, load disturbance response, measurement noise and plant uncertainty.
TL;DR: In this paper, a self-tuning scheme combined with a parametric control approach can successfully deal with the reactor start-up and the regulatory problem, provided that the adaptive scheme's process model order is adequately selected.
13 Sep 1992
TL;DR: The development of a scheme for fuzzy gain scheduling of PID (proportion-integral-derivative) controllers for process control is described and results demonstrate that better control performance can be achieved in comparison with the controllers of J. Nichols and T. Kitamori's PID controllers.
Abstract: The development of a scheme for fuzzy gain scheduling of PID (proportion-integral-derivative) controllers for process control is described. Fuzzy rules and reasoning are utilized online to determine the controller's parameters based on the error signal and its first derivative or difference. Simulation results demonstrate that better control performance can be achieved in comparison with the controllers of J. G. Ziegler and N. B. Nichols (1942) controllers and T. Kitamori's (1979) PID controllers. >
Book•
01 Jan 1992
TL;DR: The development and use of building energy management systems the outstation the BEMS central station sensors and their responses basic control PID three term direct digital control building heat loss and heating compensation optimiser control monitoring and targeting.
Abstract: The development and use of building energy management systems the outstation the BEMS central station sensors and their responses basic control PID three term direct digital control building heat loss and heating compensation optimiser control monitoring and targeting
09 Nov 1992
TL;DR: An advanced GA which can rapidly optimize the parameter auto-tuning process of classical PID controllers is designed based on the GA theory, the authors' experience, and different performance indices, including nonlinear or multiple criteria.
Abstract: Advanced genetic algorithms (GAs) are used to automatically carry out the fine-tuning of the parameter settings of classical PID (proportional plus integral plus derivative) controllers. The basic concept and working principle of GAs are introduced and compared with those of traditional optimization techniques. An advanced GA which can rapidly optimize the parameter auto-tuning process of classical PID controllers is designed based on the GA theory, the authors' experience, and different performance indices, including nonlinear or multiple criteria. The computer implementation of this GA has been accomplished and tested against some benchmark examples. Simulation results demonstrate the efficiency and effectiveness of the proposed tuning technique. >
16 Dec 1992
TL;DR: In this paper, a robust higher-order PID (proportional plus integral plus derivative)-type ILC (iterative learning control) algorithm is presented for tracking control of delayed nonlinear time-varying MIMO (multiple-input multiple-output) repetitive systems.
Abstract: A robust higher-order PID (proportional plus integral plus derivative)-type ILC (iterative learning control) algorithm is presented for tracking control of delayed nonlinear time-varying MIMO (multiple-input multiple-output) repetitive systems. A convergence proof is given in a more general case. When initial state bias exists, a repetitive ILC scheme (i.e. forward learning and backward learning) is proposed to make the algorithm more robust with respect to this bias. Simulation results indicate that the proposed method converges faster than previous methods. The effect of system delay (or even multidelays and time-varying delays) on the ILC convergence is very small. Examples are provided to demonstrate the efficiency of the proposed methods. >
09 Nov 1992
TL;DR: An optimization scheme for fuzzy PID controllers is presented using a simple GA which can automatically optimize the whole base or a sufficient set of fuzzy PID control rules under various performance indices including knowledge-based indices.
Abstract: Genetic algorithms (GAs) are utilized to build an optimization mechanism to refine the rule base of fuzzy proportional-integral-derivative (PID) controllers. The essential control law of fuzzy PID controllers is formulated by means of fuzzy set theory and the classical PID principle. An optimization scheme for fuzzy PID controllers is presented using a simple GA which can automatically optimize the whole base or a sufficient set of fuzzy PID control rules under various performance indices including knowledge-based indices. The realization of this optimal fuzzy PID control system is discussed in terms of numerical algorithms. The proposed approach was applied to an experimental heating process and the simulation results are presented. >
TL;DR: In this paper, a model reference non-linear controller with PID actions is proposed for temperature control of process fluid in a fluid-fluid heat exchanger, which is an example of a system with a relative order of two.
TL;DR: In this article, it is shown that adaptive control is less affected by process dynamics than traditional PID controllers. But, adaptive control still requires a long and complicated task, which often provides optimum results within a limited temperature range.
Abstract: Temperature control problems in a rapid thermal processor (RTP) are addressed by using a conventional proportional-integral-derivative (PID) controller and an autoadaptive algorithm. So far, temperature control in most RTP systems has usually been accomplished by using PID controllers. In RTP systems using only classical control schemes, the setting of the control module is a long and complicated task, which often provides optimum results within a limited temperature range. It is shown that adaptive control is less affected by process dynamics. >
TL;DR: In this paper, the adaptive thermal control of different kinds of operation (heating, cooling, exothermic reactions carried out in a semi-batch jacketed pilot reactor) is discussed.