Showing papers on "Smith predictor published in 2011"

Variable Time-Delay Estimation for Anesthesia Control During Intensive Care

Abstract: The presence of artifacts plays a crucial role in automatic sedation systems and may introduce variable time delays (TDs) in the closed-loop-control structures. This paper presents a successful procedure to estimate the varying TD of the bispectral index (BIS) monitor used in closed-loop control during intensive care. The TD estimation (TDE) is based on the cross-correlation analysis technique and the method is validated with real measured signals of propofol and BIS. Extended prediction self-adaptive control is used in combination with a Smith predictor to reduce the computational burden imposed by the variable TD. The conclusion is that an online TDE of the BIS monitor improves the performance of the closed-loop system for reference tracking, disturbance rejection, and overall stability.

Modified Smith predictor and controller for time delay processes

Abstract: A modified Smith predictor control scheme is proposed for controlling stable, integrating and unstable processes with time delay. The two-degrees-of-freedom control structure along with simple tuning rules result in improved servo and regulatory performances by independently tuning a single control parameter. A convenient property of the proposed control scheme is that it decouples the setpoint response from the load response. The H 2 optimal control method is used to design the setpoint tracking controller and an optimal IMC filter is proposed to design a PID controller that produces good disturbance rejection performances. Simulation results show the simplicity and superiority of the proposed method compared with some reported methods.

Dead-Time Compensation for Systems With Multiple I/O Delays: A Loop-Shifting Approach

Abstract: This paper studies the standard problem for a class of multiple-delay systems, where different input/output channels have different dead times. We present a procedure of converting the original problem to an equivalent delay-free problem via loop-shifting arguments. This brings about and, for the first time, explains an unorthodox form of the dead-time compensator, called the feedforward action Smith predictor (FASP), in which an interchannel feedforward term is present alongside the conventional internal feedback. Our developments lead to a qualitative conclusion that the structure of the dead-time compensator should rely upon the structure of the regulated output and/or the way in which exogenous signals affect the measurement.

Decentralized Fuzzy Control of Nonlinear Interconnected Dynamic Delay Systems via Mixed $H_2/\!H_\infty$ Optimization With Smith Predictor

Abstract: Each subsystem of a nonlinear interconnected dynamic delayed system is approximated by a weighted combination of L transfer function delayed systems (TFDSs). The H2-norm of the difference between the transfer function of a reference model and the closed-loop transfer function of the kth TFDS of subsystem i is then minimized to obtain a suitable frequency response without incurring oscillating and sluggish phenomena. Because of the existence of the disturbance at the output of the kth TFDS, which is not only large but also contains various frequency components, the H∞-norm of the weighted sensitivity function between the output disturbance and its corresponding output of the kth TFDS is simultaneously minimized to reduce its effect. Furthermore, with proper selection of weighted sensitivity functions, certain specific modes of the output disturbance can be eliminated. Finally, two simulations are performed; one is the simulation of our designed TFDSs with different delays or nonminimum phases, and the other is the simulation of an internet-based intelligent space for the trajectory tracking of a car-like wheeled robot system. We demonstrate the effectiveness and efficiency of the proposed control. The main contributions of this paper are twofold. First, the control can simultaneously attain robust performance through the mixed H2/H∞ optimization with a Smith predictor and achieve the robust stability via L2N stable with finite gain. Second, fuzzy observer is not needed.

Disturbance attenuation in time-delay systems — A case study on engine air-fuel ratio control

Abstract: In this paper we analyze relative performance of several approaches to disturbance attenuation for systems with time delay including the conventional Proportional-Integral controller, the Smith Predictor, and the Model Reduction controller. The paper proposes a measure of disturbance attenuation capability and computes it analytically for each of the controllers considered. The results are applied to the air-fuel ratio regulation in automotive engines. To meet strict emission regulations, gasoline engines must operate at stoichiometric air-fuel ratio over most of its operating range. A major component towards accomplishing this goal is the closed loop fuel controller. The feedback uses an exhaust-gas oxygen sensor which introduces a long transport delay. This paper discusses the air-fuel ratio regulation problem, explores options in control design for disturbance attenuation in system with time-delay, and shows simulation and experimental, in-vehicle validations.

Gain-scheduled smith proportional-integral derivative controllers for linear parameter varying first-order plus time-varying delay systems

Abstract: Practical control problems often deal with parameter-varying uncertain systems that can be described by a first-order-plus-delay (FOPD) model. In this paper, a new approach to design gain-scheduled robust linear parameter varying (LPV) propotional-intergral derivative controllers with pole placement constraints through linear matrix inequalities (LMI) regions is proposed. The controller structure includes a Smith Predictor (SP) to deal with the delays. System parameter variations are measured online and used to schedule the controller and the SP. Although the known part of the delay is compensated with the -delay scheduling- SP, the proposed approach allows to consider uncertainty in the delay estimation. This uncertainty is taken into account in the controller design as an unstructured dynamic uncertainty. Finally, two applications are used to assess the proposed methodology: a simulated artificial example and a simulated physical system based on an open canal system used for irrigation purposes. Both applications are represented by FOPD models with large and variable delays as well as parameters that depend on the operating conditions.

Predictive PID Control of Non-Minimum Phase Systems

Abstract: Control engineers have been aware of non-minimum phase systems showing either undershoot or time-delay characteristics for some considerable time (Linoya & Altpeter, 1962; Mita & Yoshida, 1981; Vidyasagar, 1986; Waller & Nygardas, 1975) A number of researchers that addressed this problem from a predictive control point of view mainly followed one of two approaches: a classical (non-optimal) predictive approach or a modern optimisation based predictive approach (Johnson & Moradi, 2005) The common characteristic of all these approaches is that they are model-based Predictive control allows the controller to predict future changes in the output signal and to use this prediction to generate a desirable control variable The classical predictive controllers that are most widely considered include the Smith predictor structure and the internal model control (IMC) structure (Katebi & Moradi, 2001; Morari & Zafiriou, 1989; Tan et al, 2001) Modern predictive controllers consider generalised predictive control (GPC) or model-based predictive control (MPC) structures (Johnson & Moradi, 2005; Miller et al, 1999; Moradi et al, 2001; Sato, 2010) The performance of a PID controller degrades for plants exhibiting non-minimum phase characteristics In order for a PID controller to deal with non-minimumphase behaviour, some kind of predictive control is required (Hagglund, 1992) Normally the derivative component of the PID controller can be considered as a predictive mechanism, however this kind of prediction is not appropriate when addressing non-minimum phase systems In such a case the PI control part is retained and the prediction is performed by an internal simulation of plant inside the controller This chapter starts with a quick review of the system-theoretic concept of a pole and zero and then draws the relationship to non-minimum phase behaviour The relationship between the undershoot response and time-delay response will be discussed using Pade approximations Classical and modern predictive PID control approaches are considered with accompanying examples The main contribution of the chapter is to illustrate the context and categories of predictive PID control strategies applied to non-minimum phase systems by:

PI control of first order time-delay systems via eigenvalue assignment

Abstract: A new approach to design PI controllers for time-delay systems is presented. A time-delay can limit and degrade the achievable performance of the controlled system, and even induce instability. This paper presents a new method, based on the Lambert W function [20], for design of PI feedback controllers as an alternative to the well-known Smith predictor. PI controllers for first-order plants with time-delays are designed by obtaining the rightmost (i.e., dominant) eigenvalues in the infinite eigenspectrum of time-delay systems, and assigning them to desired positions in the complex plane. The process is possible due to a novel property of the Lambert W function. Using the controllers designed by using the presented approach, system performance can be improved as well as successfully stabilized. Also, sensitivity analysis of the rightmost eigenvalues is conducted to show that robustness compares favorably to the Smith predictor.

Fractional Control With a Smith Predictor

Abstract: The advantageous use of fractional calculus (FC) in the modeling and control of many dynamical systems has been recognized. In this paper, we study the control of a heat diffusion system based on the application of the FC concepts. Several algorithms are investigated and compared, when integrated within a Smith predictor control structure. Simulations are presented assessing the performance of the proposed fractional algorithms.

Design and Simulation Verification of Self- tuning Smith Predictors

Abstract: This paper deals with a design of algorithms for self- tuning digital control of processes with time-delay. The algorithms are based on the some modifications of the Smith Predictor (SP). One modification of the SP based on the digital PID controller was applied and it was compared with two new designed modifications based on polynomial approach (pole assignment and minimization of the quadratic criterion). The program system MATLAB/SIMULINK was used for simulation verification of these algorithms. Some of designed algorithms are suitable for implementation in real time conditions.

Genetic Algorithm Tuning of PID Controller in Smith Predictor for Glucose Concentration Control

Abstract: This paper focuses on design of a glucose concentration control system based on nonlinear model plant of E. coli MC4110 fed-batch cultivation process. Due to significant time delay in real time glucose concentration measurement, a correction is proposed in glucose concentration measurement and a Smith predictor (SP) control structure based on universal PID controller is designed. To reduce the influence of model error in SP structure the estimate of measured glucose concentration is used. For the aim an extended Kalman filter (EKF) is designed. To achieve good closed-loop system performance genetic algorithm (GA) based optimal controller tuning procedure is applied. A standard binary encoding GA is applied. The GA parameters and operators are specified for the considered here problem. As a result the optimal PID controller settings are obtained. The simulation experiments of the control systems based on SP with EKF and without EKF are performed. The results show that the control system based on SP with EKF has a better performance than the one without EKF. For a short time the controller sets the control variable and maintains it at the desired set point during the cultivation process. As a result, a high biomass concentration of 48.3 g⋅l -1 is obtained at the end of the process.

The Smith-PID Control of Three-Tank-System Based on Fuzzy Theory

Abstract: According to the character of the volume-lag of the controlled process of three-tank-system, Smith predictor was adopted to compensate three-tank-system fuzzy adaptive control system. Fuzzy adaptive Smith predictive control system is composed with Smith predictor and fuzzy adaptive controller. The PID parameters were setting on line. This algorithm uses fuzzy adaptive PID control to improve the resistance ability to random disturbance and Smith predictive control to overcome the time-delay character of controlled object. Simulation results showed that this control algorithm has the advantages of strong adaptive ability and noise immunity.

Robust buffer management mechanism in quality of service routers

Abstract: Active queue management (AQM) is essentially a router buffer management strategy supporting TCP congestion control. Since existing AQM schemes exhibit poor performance and even instability in time delay uncertain networks, a robust buffer management (RBM) mechanism is proposed to guarantee the quality of service (QoS). RBM consists of a Smith predictor and two independent controllers. The Smith predictor is used to compensate for the round trip time (RTT) delay and to restrain its negative influence on network performance. The main feedback controller and the disturbance rejection controller are designed as proportional-integral (PI) controller and proportional (P) controller by internal model control (IMC) and frequency-domain analysis respectively. By simulation experiments in Netwrok-Simulator-2 (NS2), it is demonstrated that RBM can effectively manage the buffer occupation around the target value against time delay and system disturbance. Compared with delay compensation-AQM algorithm (DC-AQM), proportional-integral-derivative (PID) algorithm and random exponential marking (REM) algorithm, the RBM scheme exhibits the superiority in terms of stability, responsiveness and robustness.

Control of dead-time systems using derivative free particle swarm optimisation

Abstract: Particle swarm optimisation (PSO), a population-based nature inspired algorithm has mostly been used for solving continuous optimisation problems, discrete variants also exist. It finds application in most of the engineering design problems. This paper introduces two improved forms of PSO algorithm applied to PID controller and Smith predictor design for a class of time delay systems. In this paper, derivative free optimisation methods, namely simplex derivative pattern search and implicit filtering are used to hybridise PSO algorithm with improved convergence than original PSO. The effectiveness of the proposed algorithms namely SDPS-PSO, IMF-PSO are demonstrated using unit step set point response for a class of dead-time systems using PID controller and Smith predictor designed using the proposed hybrid PSO algorithms. The results are compared with earlier controller tunings proposed by Kookos, Syrcos, Chidambaram, Kanthaswamy and Luyben.

Design of decoupling Smith control for multivariable system with time delays

Abstract: In order to solve the decoupling control problem of multivariable system with time delays, a new decoupling Smith control method for multivariable system with time delays was proposed. Firstly, the decoupler based on the adjoint matrix of the multivariable system model with time delays was introduced, and the decoupled models were reduced to first-order plus time delay models by analyzing the amplitude-frequency and phase-frequency characteristics. Secondly, according to the closed-loop characteristic equation of Smith predictor structure, proportion integration (PI) controllers were designed following the principle of pole assignment for Butterworth filter. Finally, using small-gain theorem and Nyquist stability criterion, sufficient and necessary conditions for robust stability were analyzed with multiplicative uncertainties, which could be encountered frequently in practice. The result shows that the method proposed has superiority for response speed and load disturbance rejection performance.

Predictive control of the multivariable time delay processes in an isotope separation column

Abstract: The secondary processes in a pilot plant carbon isotope cryogenic separation column are multivariable time delay processes. In general, for these types of processes, Smith Predictor control schemes are frequently used, however they exhibit poor robustness due to the explicit use of the process model in the compensation loop and require additional control techniques to enhance robustness against modeling uncertainties. An alternative solution used in this paper is a predictive controller, with intrinsic time delay compensation. The simulations presented show that the predictive controller is also robust to significant time delay estimation errors, without further need to design additional filters for increasing robustness.

A neuro-fuzzy compensator based Smith predictive control for FOPLDT process

Abstract: This paper discusses a new control approach for a first-order-plus-long-dead-time (FOPLDT) process. A standard Smith predictor has a poor performance in the presence of modelling errors in process gain, time constant or time delay. To improve the system performance a neuro-fuzzy-compensator-based Smith predictor is used to form an advanced controller for the FOPLDT process. This proposed neuro-fuzzy-compensator-based Smith predictor provides good robustness with respect to simultaneous variations in all three process parameters. Furthermore, in order to reduce the steady-state error, a PID controller is integrated into the proposed control system. Simulation results and analysis revealed that this new control scheme for FOPLDT process control presents robustness to modelling errors and superior performance to the standard Smith predictor.

Control of dead-time systems using hybrid ant colony optimization

Abstract: This paper introduces two improved forms of the ant colony optimization (ACO) algorithm applied to a proportional integral derivative (PID) controller and Smith predictor design. Derivative free optimization methods, namely simplex derivative based pattern search (SDPS) and implicit filtering (IMF), are used to intensify the search mechanism in the ACO algorithm with improved convergence over the original ACO. The effectiveness of the controller schemes using the proposed algorithms, namely SDPS-ACO, and IMF-ACO, is demonstrated using unit step set point response for a class of dead-time systems, and the results are compared with some existing methods of controller tuning.

Application of fuzzy logic to reduce modelling errors in PIDSP for FOPDT process control

Abstract: In this paper, a PID controller with a Smith Predictor (PIDSP) for a First Order Plus Dead Time (FOPDT) process is first presented. From simulation evaluation, it was found that there is a significant sensitivity to the process modelling errors (process gain, time constant and dead time). As a result, a Fuzzy Logic compensator has been developed to be used as an internal feedback to compensate for process model parameter variations. This proposed approach reduces considerably the effects of the process modelling errors in gain, time constant or dead time.

Providing quality of service over time delay networks by efficient queue management

Abstract: The TCP/AQM dynamics is modeled as a time-delay congestion control system, in which the round trip time (RTT) has great influence on the system stability and network performance. Most of the existing active queue management (AQM) algorithms suffer from performance degradation, and fail to provide quality of service (QoS) when the RTT delay becomes remarkable. To address the problem, we present an efficient queue management method, which uses an enhanced Smith predictor to compensate for the RTT delay. An adaptation rule is designed for the gain of the estimated model via Lyapunov stability theory to improve the robustness of Smith predictor. Converting the Smith predictor to its equivalent structure, we derive the AQM controller from the internal model control technique and obtain an executable proportional-integral (PI) controller, which can be easily implemented due to its simple form. By simulations, it is demonstrated that our proposed method could improve QoS in large delay networks and outperforms other competitive AQM schemes in terms of stability and robustness.

Hybrid intelligent control scheme of a polymerization kettle for ACR production

Abstract: Polymerization kettle is the key controlled plant in ACR (Acrylate Copolymer Resin) production, which is a nonlinear time-delay system with parametric variance. However, modeling difficulties make the plant dynamic model poorly defined. A hybrid intelligent control scheme including an intelligent predictor is designed for this complex plant based on time-delay compensation theory. It consists of a Smith neural-network predictor and a self-adjusting-scaling-factor fuzzy logic controller. The simulation experiments verified the performance of our proposed system in two scenarios: one with invariant parameters and the other with time-varying parameters. Moreover, the comparison to other three typical control methods including Smith PID, Smith neural-network PID and Smith fuzzy logic control is also presented, which demonstrates that the proposed control scheme has satisfactory effect. Even when the system parameters vary with time, the proposed system still gives superior performance and improved robustness.

Adaptive following of perturbed plants with input and state delays

Abstract: In this paper we develop a state feedback Lyapunov-based design of direct model reference adaptive control (MRAC) for a special class of non-linear systems with input and state delays, based only on the lumped-delays without so-called distributed-delay (DD) blocks are developed. A Smith predictor built on the base of the reference model transfer function is introduced for indirect (implicit) input-delay compensation. Finally, simulation results are given to demonstrate the effectiveness of the proposed method.