Showing papers on "PID controller published in 1991"

A simple PD controller for robots with elastic joints

Abstract: The point-to-point control of manipulators having elastic joints is considered. It is shown that a simple PD (proportional plus derivative) controller, similar to that used for rigid robots, suffices to globally stabilize the elastic joint robots about a reference position. A robustness analysis is also given with respect to uncertainties on the robot parameters. The results of numerical simulation tests of a manipulator with three revolute elastic joints are presented. >

Adaptive PD controller for robot manipulators

Abstract: Referring to the point-to-point control problem, a proportional and derivative (PD) control algorithm is presented that is adaptive with respect to the gravity parameters of robot manipulators. The proposed controller is shown to be globally convergent. Following the same approach, an application to the tracking problem is also presented. Simulation tests are included, with reference to a robot having three degrees of freedom. These tests show that the performances of the adaptive PD controller are scarcely influenced by the initial error. >

Vision and control techniques for robotic visual tracking

Abstract: Algorithms for robotic real-time visual tracking of arbitrary 3-D objects traveling at unknown velocities in a 2-D space are presented. The problem of visual tracking is formulated as a problem of combining control with computer vision. A mathematical formulation that is general enough to be extended to the problem of tracking 3-D objects in 3-D space is presented. The authors propose the use of sum-of-squared differences optical flow for the computation of the vector of discrete displacements each instant of time. These displacements can be fed either directly to a PI controller, a pole assignment controller, or a discrete steady-state Kalman filter. In the latter case, the Kalman filter calculates the estimated values of the system's states and exogenous disturbances, and a discrete LQG controller computes the desired motion of the robotic system. The outputs of the controllers are sent to a Cartesian robotic controller that drives the robot. >

An iterative learning control of robot manipulators

Abstract: An iterative learning scheme comprising a unique feedforward learning controller and a linear feedback controller is presented. In the feedback loop, the fixed-gain PD controller provides a stable open neighborhood along a desired trajectory. In the feedforward path, on the other hand, a learning control strategy is exploited to predict the desired actuator torques. It is shown that the predicted actuator torque converges to the desired one as the iteration number increases. The convergence is established based on the Lyapunov stability theory. The proposed learning scheme is structurally simple and computationally efficient. Moreover, it possesses two major advantages: the ability to reject unknown deterministic disturbances and the ability to adapt itself to the unknown system parameters. >

An adaptive control scheme for speed control of diesel driven power-plants

Abstract: The performance of an incremental Clarke-Gawthrop adaptive control scheme, suitable for a diesel-engine prime mover, is described. The controller uses a predictor that is derived from explicit estimates of the plant deadtime and time constants. Its performance under speed reference changes and load disturbances has been compared to that of a fixed, tuned proportional-integral (PI) controller. The algorithm is found to operate satisfactorily under different values of droop without any additional complexity of computation being incurred. However, the improvement in plant response due to the adaptive algorithm is somewhat reduced at high droops. The effective improvement due to adaptation is also seen to be reduced under 'cold oil' conditions. However, even under such conditions, it is possible to obtain improved response as compared to the PI controller. >

Design of a fuzzy controller using input and output mapping factors

Abstract: A complete design procedure for a fuzzy three-term PID controller is presented. A plant model is not required to achieve this design. A reduced look-up table containing the rules along with the quantization and tuning procedures by means of input and output mapping factors are introduced. The scaling factors of the output error time sequences are preselected arbitrarily and the search for an optimal input-to-output mapping factors ratio is performed through a phase diagram analysis. the applicability of the design procedure is demonstrated through computer simulations. >

Application of fuzzy logic control to a manipulator

Abstract: The authors describe a control strategy for robotic manipulators that incorporates a proportional-plus-integral (PI) controller with a simple fuzzy logic (FL) controller. In the proposed strategy, the PI controller is used to ensure fast transient response and zero steady-state error for step inputs, or end-point control, whereas the FL controller is used to enhance the damping characteristics of the overall system. The main advantage of the proposed control energy is that only the current and previous measurements and a set of simple control rules are required; as such, it can be readily implemented. The proposed FL controller is described, and its effectiveness is demonstrated through simulations involving the control of a two-arm two-link manipulator. >

Application of superconducting magnetic energy storage unit to improve the damping of synchronous generator

Abstract: A systematic approach to the design of a controller for superconducting magnetic energy storage (SMES) units to improve the dynamic stability of a power system is presented. The scheme employs a proportional-integral (PI) controller to enhance the damping of the electromechanical mode oscillation of synchronous generators. The parameters of the PI controller are determined by the pole assignment method based on modal control theory. Eigenvalue analysis and nonlinear computer simulations show that SMES with the PI controller can greatly improve the damping of the system under various operating conditions. Although the PI controller is designed for a special load condition, it can also provide good damping under other load conditions. >

A comparative performance study of PID auto-tuners

Abstract: The benchmark testing of the autotuning performance characteristics of three controllers is reported. The controllers are two commercial single-loop proportional integral-derivative (PID) controllers, the SattControl relay feedback autotuner and the Foxboro EXACT self-tuning controller, and a refined Ziegler-Nichols prototype PID controller autotuned by means of the cross-correlation method. A novel microcontroller-based process simulator has been used to simulate several generic processes for the benchmark tests. Quantitative results based on the integral squared error of the transient responses are used to contrast the relative performance of the autotuning controllers in the presence of setpoint change, static load disturbance, and measurement noise. Another performance measure, namely the retuning time, is used to compare performance. >

Thermostat with means for disabling pid control

Abstract: A thermostat is disclosed which includes a Proportional-Integral-Derivative (PID) controller and a means for disabling the PID controller for selected periods. The PID controller is disabled during a temperature recovery period, which can be triggered by the occurrence of one or more of many preselected events. The PID controller is re-enabled when the thermostat setpoint less a void offset temperature is reached. To reduce error in future temperature recovery periods, the void offset temperature is adjusted after a temperature recovery by adding the amount of error to the void offset temperature to create a new void offset temperature for use in a next temperature recovery period.

Refining PID Controllers using Neural Networks

Abstract: The KBANN (Knowledge-Based Artificial Neural Networks) approach uses neural networks to refine knowledge that can be written in the form of simple propositional rules. We extend this idea further by presenting the MANNCON (Multivariable Artificial Neural Network Control) algorithm by which the mathematical equations governing a PID (Proportional-Integral-Derivative) controller determine the topology and initial weights of a network, which is further trained using backpropagation. We apply this method to the task of controlling the outflow and temperature of a water tank, producing statistically significant gains in accuracy over both a standard neural network approach and a nonlearning PID controller. Furthermore, using the PID knowledge to initialize the weights of the network produces statistically less variation in test set accuracy when compared to networks initialized with small random numbers.

A connectionist approach to PID autotuning

Abstract: A connectionist approach to the problem of PID autotuning is proposed. Multilayer perceptrons, based on integral measures of the step response, are used to supply the PID parameters. Tuning can be achieved both in open loop and closed loop. A different formulation of the learning problem for a class of multilayer perceptrons is presented. This approach, besides reducing the size of the problem, gives a major reduction in the number of iterations needed to achieve a local minimum.

Self-tuning predictive PID controller

Abstract: A recursive algorithm for the automatic tuning of PID regulators is described. The tuning strategy is based on the minimisation of a performance index which considers the quadratic deviations of the predicted output, over the set point, as well as the control efforts, over a time horizon. The adaptive version of this algorithm follows an explicit scheme so that the applications are not limited to self-tuning in the commissioning phase. It can also be applied to parameter adaptive control. The method has been successfully tested and some results are presented.

Application of generalised predictive control to a boiler-turbine unit for electricity generation

Abstract: The central task in power station control is to meet the system demand while minimising state and input variations in the plant. In order to achieve good set-point following, the control system must make good use of coupling between the different control loops and if possible use information about future set points to smooth out the control activity. Characteristic generalised predictive control sets out to achieve both these objectives and hence would seem ideally suited to power station control. The presence of some fast and slow dynamics implies that the boiler-turbine system is in essence a stiff problem; the characteristic generalised predictive control (GPC) algorithm is suitably extended to take direct account of this. Simulation results show that the characteristic GPC algorithm (a) provides a systematic means of approaching the boiler-turbine problem and (b) affords some improvements in performance over traditional PID control schemes.

Method and an apparatus for PID controller tuning

Abstract: A method for tuning P-, I- and D-type controller which is used in combination or individually to control a variable y of a process in a feedback system, which comprises making the integrating (I) and derivative (D) unit of the controller inoperative; increasing the proportional control gain K until a desired oscillation is obtained; calculating the ultimate gain Ku and ultimate period Tu in accordance with the amplitude and period measured from the oscillation; and setting the parameters of the PID controller in dependence upon the Ku and Tu values, wherein the control signal U resulting from the controller gain K is restricted to a range from a lower limit Umin to an upper limit Umax to avoid the system being operated in an unstable condition. An apparatus suitable for performing the present method is also disclosed.

An expert system to perform on-line controller tuning

Abstract: An expert system that tunes a proportional-integral-derivative (PID) controller online for a single-input-single-output multiple-lag process with dead time is described. The expert system examines features of each transient response and the corresponding controller parameters. It determines a new set of controller gains to obtain a more desirable time response. This technique can be used to determine and implement a different set of PID gains for each operating regime, and once in steady state, the system can be used to find optimal parameters for load disturbance rejection. The expert system can be applied to any system of the specified form (aerospace, industrial, etc.) and can be expanded to include additional process models. >

Tuning PID controllers with integral performance criteria

Abstract: Gives some new results on integral performance criteria and describes how these have been incorporated within a menu driven software package in MATLAB. A disadvantage of the integral squared error (ISE) criterion is the fact that its minimization often results in a relatively oscillatory step response since the large errors which must occur for small time contribute significantly to the performance index. The paper also examines the time weighted squared error criterion and shows how analytical results can be obtained for the performance integral. New theoretical results are given for a simple plant with time delay and they are used to check the numerical computations which are achieved using a Pade approximation. A menu driven software package is developed to implement the computation algorithms using the integral performance criteria.< >

Adaptive control of dissolved oxygen concentration in a bioreactor

Abstract: A new adaptive DO (dissolved oxygen) concentration control algorithm considering DO electrode dynamics with response time delay has been developed. A system model with two time-varying parameters was used to relate the DO concentration with two control variables: air flow rate and agitation speed. Parameters of this model were estimated on-line using a regularized constant trace recursive least-squares method. An extended Kalman filter was used to remove the effect of noises from the DO concentration measurements and thus to improve control performance. A discrete one-step ahead control scheme was adopted to determine control actions based on the parameter estimation results. Experimental results showed that the new adaptive DO concentration control algorithm performed better than other algorithms tested, a PID controller and adaptive algorithms without the DO electrode dynamics.

On-line auto tuning of PID controllers based on the cross-correlation technique

Abstract: The development of an online version of an autotuning algorithm for proportional-integral-derivative (PID) controllers based on the cross-correlation technique is described. The autotuner causes only minor perturbation on the normal operation of the process, needs little prior information, and is robust to noise. The design rules for automatic selection of the length and bit interval of the pseudorandom binary-sequence (PRBS) probing signal used by this autotuner are also discussed. The accuracy and performance of this autotuning method have been substantiated by extensive simulations. >

An Experimental Study On Lateral Control Of A Vehicle

Abstract: Addresses issues regarding the implementation of an integration of several specific technologies involved in achieving lateral guidance of an experimental automotive vehicle on an automated highway. Results demonstrate the feasibility of the proposed discrete magnetic marker reference/sensing system. In addition, the performance and limitations of a PID/feedforward controller is investigated with respect to tracking accuracy of straight and curved sections as well as robustness to changes in load, longitudinal velocity, and cornering stiffness.

Facility management system with improved return to automatic control

Abstract: There is disclosed a control system for use, for example, in facility management which controls an environmental parameter to maintain the parameter at a given set point. A PID Controller is coupled to a remote sensor for generating a feedback signal responsive to the parameter level sensed by the remote sensor. The PID Controller is responsive to being coupled to a field device for providing the field device with an automatic control signal having a level derived from the sum of integral, derivative, and proportional actions to the feedback or error signal to place the field device under automatic control, and is responsive to being decoupled from the field device when the field device is under manual control for either terminating the generation of the automatic control signal or providing an estimate of a manual control signal. When recoupled to the field device, the PID Controller provides the field device with a control signal at an initial level based upon the level of a manually selected control signal, the last level of the automatic control signal provided to the field device prior to being decoupled from the field device or the last estimate of the manual control signal.

A predictive controller for the Mach number in a transonic wind tunnel

Abstract: The use of the unified predictive controller in controlling the Mach number of a transonic wind tunnel is examined. It is shown, by means of simulations and experiments, that the unified predictive controller yields an overall performance improvement of 30-60% in comparison with the proportional-integral-derivative (PID) controller that is normally used to control the Mach number. The rejection by the unified predictive controller of disturbances caused by changing the angle of attack is a factor of four better than that for the PID controller. This makes it possible to change the angle of attack faster, so that the efficiency of the wind tunnel operation can be improved. It is believed that this is mainly due to the fact that knowledge about the disturbances can be incorporated into the predictive controller design. Simulations have shown that even better results can be expected; the results have not yet been verified by experiments. >

Self-tuning controller apparatus and process control system

Abstract: A self-tuning controller apparatus which comprises: a control response pattern recognition portion for receiving a set-point and a controlled variable of a process and for obtaining three performance indexes from a controlled variable response pattern generated in response to a change in the set-point or a disturbance; a control parameter correction portion for qualitatively evaluating the three performance indexes and for inferring a correction value of a PID control parameter on the basis of the result of evaluation; and a control performance dissatisfaction degree evaluation portion for evaluating the inferred correction value of the PID control parameter in accordance with the dissatisfaction degrees of the two performance indexes for the respective target specifications of the two of the three performance indexes. The control performance dissatisfaction degree evaluation portion acts to make the PID control parameter converge stably. In a process control system including a plurality of vertically distributed control elements each capable of self-tuning its control parameter, the control performance dissatisfaction degree evaluation portion contributes to autonomous functioning of each of the control elements.

Application of adaptive control theory to on-line GTA weld geometry regulation

Abstract: This study addresses the uses of adaptive schemes for on-line control of backbead width in the Gas Tungsten Arc (GTA) welding process. Open-loop tests using a step input current confirm the validity of a nominal first order process model. However, the time constant and gain prove highly dependent upon welding conditions including torch speed, arc length, material thickness, and other material properties. Accordingly, a need exists for adaptive controllers that can compensate for these process nonlinearities. The performance of two adaptive controllers is evaluated: Narendra and Lin’s Model-Referenced Adaptive Control (MRAC/NL), and Self-Tuning Control with Pole Placement (STC/PP). The addition of a quadratic term to the adaption mechanisms of MRAC/NL is proposed and preliminary simulations and experiments clearly demonstrate the stabilizing effect of this added term. The main experiments compare the performance of the modified MRAC/NL controller and the STC/PP controller with each other and with linear PI controller and the STC/PP controller with each other and with linear PI controller under four experimental conditions: first, where welding conditions are nominal; second, when conditions are disturbed by a step-wise increase in the torch velocity, and third, when conditions are disturbed by a step-wise increase in material thickness. In each case the experimental demonstrates the superiority of the adaptive controllers over the linear PI controller. However, the STC/PP controller exhibits high frequency control action in response to severe disturbances of material thickness and the parameter estimates it generates drift during steady-state operations. The MRAC/NL controller proves more robust under these circumstances. Analysis demonstrates that the superior performance of the MRAC/NL is due both to the inherent normalizing effect of the quadratic feedback terms and to the noise filtering properties of the adaptive mechanism.

Multivariable and multirate self-tuning control: a distillation column case study

Abstract: This paper is concerned with the evaluation of self-tuning control algorithms for the multivariable control of distillation columns. Effective distillation control remains a key concern of industry because of the high energy consumption associated with distillation processes. The results presented here are taken from a continuing programme of investigations aimed at improving distillation column control performance. The performance of several multi-variable self-tuning strategies is evaluated by online application to a pilot-scale binary distillation column which is subjected to disturbances of ±25% step changes in feed flow rate. The performance of the multivariable algorithms is compared with that achieved using conventional digital multiloop PI/PID control. The results have demonstrated that use of multivariable self-tuning control, in particular multirate-multivariable self-tuning control, can provide better regulatory performance for feed flow rate disturbances than can be achieved using a multiloop PI/PID strategy.

Application of superconducting magnetic energy storage unit on damping of turbogenerator subsynchronous oscillation

Abstract: A systematic approach is used to design a controller for a superconducting magnetic energy storage (SMES) unit to improve the torsional modes damping of a turbogenerator. To suppress the unstable torsional oscillation, a proportional-integral-derivative (PID) controller is employed to modulate the power input/output of the SMES unit according to generator speed deviation. The gains of the proposed PID controller are determined by the pole assignment method based on modal control theory. Eigenvalue analysis of the studied system shows that the PID controller is quite effective over a wide range of operating conditions. Computer simulations using the nonlinear system model are also performed to demonstrate the damping effort of the proposed controller under disturbance conditions.

A k-step predictive scheme for speed control of diesel driven power-plants

Abstract: An adaptive speed control scheme for diesel prime-movers is presented. Diesel prime-movers are characterized by nonlinear, time-varying parameters, including a nonlinear input dead-time variation that introduces an unknown delay between the injection of fuel and the production of engine torque. Such plants are difficult to control by conventional proportional-integral (PI) controllers. It is shown that by assuming the existence of an additional system time-constant, an explicit estimate of the plant parameters and dead-time can be obtained. The algorithm converges quickly. The resulting predictor can then be used to set up a k-step-ahead predictive controller. Studies are presented to compare the performance of the adaptive scheme to that of a fixed, tuned PI controller. The algorithm is shown to be flexible enough to operate under a wide range of droop settings, and equally applicable to various operating conditions. >