Showing papers on "PID controller published in 2000"
TL;DR: The state of the art of PID control is presented and its future is reflected on, including specifications, stability, design, applications, and performance.
1,167 citations
TL;DR: It is demonstrated that a very simple closed-loop control model of upright stance can generate realistic stabilogram diffusion function (SDF) that summarizes the mean square COP displacement as a function of the time interval between COP comparisons.
Abstract: Collins and De Luca [Collins JJ. De Luca CJ (1993) Exp Brain Res 95: 308-318] introduced a new method known as stabilogram diffusion analysis that provides a quantitative statistical measure of the apparently random variations of center-of-pressure (COP) trajectories recorded during quiet upright stance in humans. This analysis generates a stabilogram diffusion function (SDF) that summarizes the mean square COP displacement as a function of the time interval between COP comparisons. SDFs have a characteristic two-part form that suggests the presence of two different control regimes: a short-term open-loop control behavior and a longer-term closed-loop behavior. This paper demonstrates that a very simple closed-loop control model of upright stance can generate realistic SDFs. The model consists of an inverted pendulum body with torque applied at the ankle joint. This torque includes a random disturbance torque and a control torque. The control torque is a function of the deviation (error signal) between the desired upright body position and the actual body position, and is generated in proportion to the error signal, the derivative of the error signal, and the integral of the error signal [i.e. a proportional, integral and derivative (PID) neural controller]. The control torque is applied with a time delay representing conduction, processing, and muscle activation delays. Variations in the PID parameters and the time delay generate variations in SDFs that mimic real experimental SDFs. This model analysis allows one to interpret experimentally observed changes in SDFs in terms of variations in neural controller and time delay parameters rather than in terms of open-loop versus closed-loop behavior.
380 citations
Book•
01 Jan 2000
TL;DR: This chapter discusses the stabilization of Linear Time-invariant Plants Using PID Controllers using Hermite-Biehler Theorem, and some current techniques for PID Controller Design.
Abstract: 1 Overview of Control Systems- 2 Some Current Techniques for PID Controller Design- 3 The Hermite-Biehler Theorem and Its Generalization- 4 Stabilization of Linear Time-invariant Plants Using PID Controllers- 5 Optimal Design Using PID Controllers- 6 Robust and Non-fragile PID Controller Design- 7 Stabilization of First-order Systems with Time Delay- 8 Constant Gain Stabilization with Desired Damping- 9 Constant Gain Stabilization of Discrete-time Plants- References
366 citations
TL;DR: Simulation of the PID type fuzzy controller with the self-tuning scaling factors shows a better performance in the transient and steady state response.
344 citations
TL;DR: The main motivation for this design was to control some known nonlinear systems, such as robotic manipulators, which violate the conventional assumption of the linear PID controller.
293 citations
TL;DR: A digital signal processor (DSP)-based robust nonlinear speed control of a permanent magnet synchronous motor (PMSM) is presented and a boundary layer integral sliding mode controller is designed and compared to a feedback linearization-based controller.
Abstract: A digital signal processor (DSP)-based robust nonlinear speed control of a permanent magnet synchronous motor (PMSM) is presented. A quasi-linearized and decoupled model including the influence of parameter variations and speed measurement error on the input-output feedback linearization of a PMSM is derived. Based on this model, a boundary layer integral sliding mode controller is designed and compared to a feedback linearization-based controller that uses proportional plus derivative (PD) controller in the outer loop. To show the validity of the proposed control scheme, DSP-based experimental works are carried out and compared with the conventional control scheme.
291 citations
TL;DR: This paper presents how to improve the damping of the system by a derivative feedback of motor speed, and three kinds of typical pole assignments with identical radius/damping coefficient/real part are applied and compared.
Abstract: The purpose of this paper is to develop systematic analysis and design methods for a two-inertia system. A conventional proportional-integral 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 present how to improve the damping of the system by a derivative feedback of motor speed.
282 citations
08 Oct 2000
TL;DR: In this paper, a fuzzy logic speed controller is employed in the outer loop of an IM drive for speed control of an induction motor using indirect vector control, and the performance of the proposed FLC based IM drive is compared to those obtained from the conventional proportional integral (PI) controller based drive both theoretically and experimentally at different dynamic operating conditions such as sudden change in command speed, step change in load, etc.
Abstract: This paper presents a novel speed control scheme of an induction motor (IM) using fuzzy logic control. The fuzzy logic controller (FLC) is based on the indirect vector control. The fuzzy logic speed controller is employed in the outer loop. The complete vector control scheme of the IM drive incorporating the FLC is experimentally implemented using a digital signal processor board DS-1102 for the laboratory 1 hp squirrel cage induction motor. The performances of the proposed FLC based IM drive are investigated and compared to those obtained from the conventional proportional integral (PI) controller based drive both theoretically and experimentally at different dynamic operating conditions such as sudden change in command speed, step change in load, etc. The comparative experimental results show that the FLC is more robust and hence found to be a suitable replacement of the conventional PI controller for the high performance industrial drive applications.
272 citations
TL;DR: In this article, a new method for PID controller tuning based on process models for integrating and unstable processes with time delay is proposed, which gives better closed-loop performance than the existing methods.
248 citations
TL;DR: Particle impact damping (PID) is a means for achieving high structural damping by the use of a particle-filled enclosure attached to the structure in a region of high displacements.
225 citations
TL;DR: A collection of systems that are suitable for testing PID controllers and are collected from a wide range of sources are described.
TL;DR: By virtue of using the simplest structure of fuzzy logic control, the stability of the nonlinear control system can be analyzed and a sufficient BIBO stability condition is given.
27 Nov 2000
TL;DR: This work proposes a framework based on control theory for designing adaptive, real-time software systems based on specifications of desired dynamic behavior and develops a new algorithm based on two PID controllers that meet both the transient and steady-state performance requirements.
Abstract: While early research on real-time computing was concerned with guaranteeing avoidance of undesirable effects, such as overload and deadline misses, adaptive real-time systems are designed to handle such effects dynamically. Various research efforts have addressed the characterization and improvement of the dynamic behavior of real-time systems. However, to the authors' knowledge, no unified framework exists for designing adaptive, real-time software systems based on specifications of desired dynamic behavior. We propose such a framework based on control theory. Using control theory, a designer can (i) specify the desired behavior in terms of a set of performance metrics that can be mapped to a dynamic response of the control system, (ii) establish an underlying control model of the real-time systems, and (iii) design a resource scheduler using feedback control design methods to guarantee runtime satisfaction of the specifications. This is in contrast to more ad-hoc techniques. We also show that simply using long-term average performance metrics is not sufficient in designing controllers. We then develop a new algorithm based on two PID controllers that meet both the transient and steady-state performance requirements.
TL;DR: The paper is not intended to develop a mathematical theory, but to give some practical recommendations on replacing control by a human operator control with fuzzy control, and an on-line parameter tuning of FC parameters.
TL;DR: In this paper, a more general structure for the classical PID controller is proposed by using fractional integral and differential operators, and a frequency domain approach is used to show the advantages of using these fractional PID controllers, which can be sumarized in the possibility of dealing with more general class of control problems.
TL;DR: It is concluded that a systems approach to control was important in the development of PID controllers as was a close relationship between instrument companies, plant designers and plant operators.
TL;DR: This work designs an output feedback integral controller that asymptotically regulates the output to a bounded time-varying reference signal with a constant limit and shows that, for relative degree one and two systems, the proposed integral controller reduces to the classical PI and PID controllers.
Abstract: We consider a single-input-single-output (SISO) nonlinear system that has a well-defined normal form with asymptotically stable zero dynamics. Using only knowledge of the relative degree and the sign of the high-frequency gain, we design an output feedback integral controller that asymptotically regulates the output to a bounded time-varying reference signal with a constant limit. We give regional as well as semi-global results. We also show that, for relative degree one and two systems, the proposed integral controller reduces to the classical PI and PID controllers, respectively.
TL;DR: In this paper, an optimal-tuning nonlinear PID controller design strategy for hydraulic systems is proposed, where an analytic physical dynamical model with dead-zone nonlinearity is derived.
TL;DR: An advanced PID auto-tuner for both single- and multi-variable processes is described and its application to HVAC systems is presented and Experimental results demonstrate the effectiveness and superior performance of the implemented auto- tuner over the manually tuned PID controller and the standard relay auto- Tuner.
TL;DR: A new criterion for selection of the Q and R matrices is proposed which will lead to the desired natural frequency and damping ratio of the closed-loop system.
TL;DR: A new robust identification method from step tests is presented first for SISO processes and then sequentially applied to TITO processes, resulting in a new 1st-order plus dead-time model for decoupler design and the 2nd-order one for decentralized PID sequential tuning.
Abstract: This paper considers auto-tuning of simple lead-lag decoupler plus decentralized PI/PID controllers for effective control of two-input and two-output (TITO) processes. A new robust identification method from step tests is presented first for SISO processes and then sequentially applied to TITO processes. The resulting 1st-order plus dead-time model is used for decoupler design and the 2nd-order one is used for decentralized PID sequential tuning. The simulation is given for illustration of the proposed tuning.
TL;DR: Three optimal-tuning PID controller design schemes are presented for industrial control systems and can provide optimal PID parameters so that the desired system specifications are satisfied even in case where the system dynamics are time variant or the system operating points change.
TL;DR: In this paper, a two-loop continuous sliding mode controller was designed for the X-33 technology demonstration sub-orbital launch vehicle in the launch mode to provide robust, accurate, de-coupled tracking of the orientation angle command profiles in presence of external disturbances and vehicle inertia uncertainties.
Abstract: A reusable launch vehicle control problem during ascent is addressed via multiple-time scaled continuous sliding mode control. The proposed sliding mode controller utilizes a two-loop structure and provides robust, de-coupled tracking of both orientation angle command profiles and angular rate command profiles in the presence of bounded external disturbances and plant uncertainties. Sliding mode control causes the angular rate and orientation angle tracking error dynamics to be constrained to linear, de-coupled, homogeneous, and vector valued differential equations with desired eigenvalues placement. Overall stability of a two-loop control system is addressed. An optimal control allocation algorithm is designed that allocates torque commands into end-effector deflection commands, which are executed by the actuators. The dual-time scale sliding mode controller was designed for the X-33 technology demonstration sub-orbital launch vehicle in the launch mode. Simulation results show that the designed controller provides robust, accurate, de-coupled tracking of the orientation angle command profiles in presence of external disturbances and vehicle inertia uncertainties. This is a significant advancement in performance over that achieved with linear, gain scheduled control systems currently being used for launch vehicles.
TL;DR: PID neural network is a new kind of networks that consists of three layers and its hidden layer's units are proportional, integral and derivative neurons.
Book•
01 Nov 2000
Abstract: Keynote Papers. New Structures And Design of PID Controllers I. Tuning Rules for PID Controllers. Tuning Methods of PID Controllers. Supervision of PID Controllers. Industrial Control Applications I. Optimal Tuning of PID Controllers. Industrial Control Applications II. Adaptive and Tuning of PID Controllers. Complex Systems and New Structures of PID Controllers. Tuning and Self-Tuning of PID Controllers. Performances of PID Controllers. Learning and Tuning of PID Controllers. General Contributions to PID Control. Author Index.
TL;DR: In this article, continuous action reinforcement learning automata (CARLA) are used to simultaneously tune the parameters of a three term controller on-line to minimise a performance objective, and the algorithm is first applied in simulation on a nominal engine model, and this is followed by a practical study using a Ford Zetec engine in a test cell.
TL;DR: The frictions are identified by a neural net, and the weight adaptation rule, defined as reinforcement adaptive learning, is derived from the Lyapunov stability theory, which can be applicable to a wide class of mechanical systems.
Abstract: There is an increasing number of applications in high-precision motion control systems in manufacturing, i.e., ultra-precision machining, assembly of small components and micro devices. It is very difficult to assure such accuracy due to many factors affecting the precision of motion, such as frictions and disturbances in the drive system. The standard proportional-integral-derivative (PID) type servo control algorithms are not capable of delivering the desired precision under the influence of frictions and disturbances. In this paper, the frictions are identified by a neural net, which has a critic element to measure the system performance. Then, the weight adaptation rule, defined as reinforcement adaptive learning, is derived from the Lyapunov stability theory. Therefore the proposed scheme can be applicable to a wide class of mechanical systems. The simulation results on a 1-degree-of-freedom mechanical system verify the effectiveness of the proposed algorithm.
TL;DR: In this paper, the authors present a comparison of various strategies for a simulated grinding circuit and compare their performance with a benchmark test, involving a sequence of disturbances (grindability, feed size distribution, change of cyclone number…) and setpoint changes, to compare the performances of the controllers.
TL;DR: This controller is designed by using an incremental fuzzy logic controller in place of a proportional term in a conventional PI controller and provides a wide variation of controller gains in a nonlinear manner.
Abstract: The paper presents a simple hybrid fuzzy logic proportional plus conventional integral controller for FACTS devices in a multi-machine power system. This controller is designed by using an incremental fuzzy logic controller in place of a proportional term in a conventional PI controller and provides a wide variation of controller gains in a nonlinear manner. This controller is well suited to series connected FACTS devices like UPFC, TCSC and TCPST, etc., in damping multi-modal oscillations in a multi-machine environment. Digital simulations of a multi-machine power system subjected to a wide variety of disturbances validate the efficiency of the new approach.
28 Jun 2000
TL;DR: A new self-tuning or adaptation algorithm for PID controllers based on a theory of adaptive interaction that achieves the tuning objective by minimizing an error function is proposed.
Abstract: We propose a new self-tuning or adaptation algorithm for PID controllers based on a theory of adaptive interaction. The theory develops a simple and effective way to perform gradient descent in the parameter space. One version of the tuning algorithm requires no knowledge of the plant to be controlled. This makes the algorithm robust to changes in the plant. It also makes the algorithm universally applicable to linear and nonlinear plants. The algorithm achieves the tuning objective by minimizing an error function. Because of its simplicity, the overhead for adding self-tuning is negligible. We applied this algorithm in an automotive product manufactured by Hitachi to satisfy performance requirements for both cold start and normal operation. Simulation results are presented to show the validity of the approach.