Showing papers on "Smith predictor published in 2022"

A modified Smith predictor based – Sliding mode control approach for integrating processes with dead time

Abstract: This paper proposes a modified hybrid robust Smith predictor controller design for integrating processes with long dead time. The proposal results in a dynamic sliding mode controller for integrating systems on blending sliding mode control and Smith Predictor modification concepts. The design part of the controller corresponding to the sliding mode arises from an approximate model of the high-order nonlinear integrating process to characterize the non-self-regulating processes. The approximation to a First Order Integrating System Plus Dead Time is obtained from an experimental method that adopts identification procedures and avoids complex analytical resources. The model contributes to designing the dynamic sliding mode controller and tuning parameters. The resulting controller is a hybrid scheme that combines the sliding mode methodology, a smith predictor structure, and a PD compensator. The hybrid control topology is used for the first time for integrating systems with dead time. The proposed approach is applied to a high order linear integrating system with long-dead time and a coupled tanks system using hardware in the loop (HIL) simulation. The hybrid control topology provides enhanced controller performance, guarantees proven robustness to parameter modeling uncertainties, and attenuates high-frequency oscillations, counteracting the adverse effects of chattering. Integral of Squared Error (ISE), Total Variation of control effort (TVu), Maximum overshoot, and Settling Time are used for quantitative comparative performance analysis.

Simple internal model control based modified Smith predictor for integrating time delayed processes with real-time verification

Abstract: Internal model control (IMC) tuned simple modified Smith predictor structure for integrating time delayed processes (IPTD) is reported here. Pole position at origin implies its non-self-regulating behaviour. Processes like distillation column, liquid supply to large storage tank, superheated steam flow to turbine etc. are usually found IPTD processes. Reported modified Smith predictor (MSP) design with multiple controllers is adequate to exhibit anticipated closed loop performance for IPTD processes. Tuning complexity of the reported multi-controller based structure is mitigated by the sole tuning parameter (closed loop time constant) obtained from IMC design. Proposed scheme shows considerable performance improvement during set point tracing by zero overshoot. Additionally, smooth as well as reasonably fast load recovery is ensured. Eminence of the reported scheme is established in terms of performance indices along with stability margins in assessment through recently reported modified Smith predictor techniques. Real-time evaluation of the proposed design is demonstrated on an indigenous set up of level control loop considered as IPTD process.

A comparative experimental evaluation of various Smith predictor approaches for a thermal process with large dead time

Abstract: This paper emphasizes a comparative experimental evaluation of three Smith predictor configurations. The three control schemes are tuned using different optimization algorithms; then, they are applied to an Arduino Temperature Control Lab used to test and evaluate their performance. The three deadtime compensators are compared using radial graphs. They were assessed under different conditions using various performance indices: the Integral Square Error, the Total Variations of Control Efforts, the Maximum Overshoot, and the Settling Time for tracking and disturbances changes. The Mejia et al. approach presented a better overall performance than the other two. Finally, the results showed that Smith Predictor is suitable for thermal processes with elevated dead time.

Hybrid dual-loop control method for dead-time second-order unstable inverse response plants with a case study on CSTR

Abstract: Abstract Unstable processes are hard to stabilize as they contain one or more positive poles which result in unbounded dynamic behavior. The occurrence of the delay and positive zeros often creates more difficulty in controlling such unstable plants. Most control strategies meant for first-order unstable processes fail to stabilize and control the higher-order unstable processes. Hence, a new dual-loop hybrid control structure is suggested for dead-time unbounded second-order processes with positive/negative zeros. Inner-loop has a stabilizing PID controller. The PID controller parameters are derived by comparing the numerator and characteristic polynomial coefficients in the transfer function for internal-loop servo action. A fractional-order internal model controller (FOIMC) is used in the external-loop. Methods for the selection of outer-loop tuning parameter and fractional-order are also discussed. By comparing the simulation results with a contemporary single-loop scheme, the usefulness of the suggested scheme is proved. The suggested scheme is capable of minimizing the overshoot and improving the overall dynamic performance. Finally, the usefulness of the suggested scheme is also demonstrated by a case study on temperature control of a continuous stirred tank reactor (CSTR) during a first-order irrevocable exothermic reaction.

Predictor-based control of time-delay systems: a survey

Abstract: With the developments of wireless data communication and network technology, time-delays are widely found in nowadays' control systems, e.g. networked control systems, mobile robot systems, and multi-agent systems. Predictor-based control is an effective method dealing with long time-delays because it can generally lead to a delay-free closed-loop system by introducing a prediction for future states. Recently, various predictor-based control methods have been developed for numerous control systems subject to different time-delays, which motivates this survey. This paper presents a comprehensive review of the up-to-date results on the predictor-based control of time-delay systems. Firstly, the ordinary differential equation-based approaches for designing and analysing predictor-based controllers are summarised. Secondly, one reports an alternative method of predictor-based control, in which the systems/controllers are understood in the sense of partial differential equations. Next, several integration-free predictor-based controllers are introduced: by abandoning the infinite-dimensional integral terms, the control laws become easier to realise in practice. Hereafter, the paper discusses the real-time implementations and the practical applications of predictor-based control methods to several particular control systems. Finally, this paper suggests some new trends of predictor-based control for future research.

Machine-Learning-Based Improved Smith Predictive Control for MIMO Processes

Abstract: Controlling time-delayed processes is one of the challenges in today’s process industries. If the multi-input/multi-output system is dynamically coupled, the delay problem becomes more critical. In this paper, a new method based on Smith’s predictive method, with the help of a type-2 fuzzy system to control the system with the mentioned features, is presented. The variability in the time delay, the existence of disturbances and the existence of structural and parametric uncertainty lead to the poor performance of the traditional Smith predictor. Even if the control system is set up correctly at the beginning of the setup, it will eventually wear out, and the above problems will appear. Therefore, computational intelligence is used here, and by updating the parameters of the control system at the same time as the system changes, the control system adapts itself to achieve the best performance. To evaluate the proposed control system, a complex process system is simulated, the results of which show the good performance of Smith’s prediction method based on a type-2 fuzzy system.

Data-driven Update of Smith Predictor and Models by Using Initial Control Signals

Abstract: For tuning controllers, various methods had been proposed. In this paper, input-type virtual internal model tuning (VIMT) for a smith compensator is proposed. Proposed methods can update smith compensator and a nominal model. The validity of the proposed method is verified via numerical simulations. Compare to the conventional method, the proposed method can realize good controllers and models in the case where the cut-off frequency of the initial sensitivity/ complementary sensitivity function is higher than that of the desired transfer function.

A model predictive control regulation model for radiant air conditioning system based on delay time

Abstract: Radiant air conditioning (RAC) systems are widely used because of the advantage of higher thermal comfort compared to convection systems. However, RAC systems exhibit considerable hysteresis and significant time delays in heat transmission from the terminal to the interior environment. Traditional feedback control methods do not adequately account for the system's delay impact while implementing dynamic control, resulting in a mismatch between supply and demand loads in time series, an inefficient impact of interior temperature control, and energy waste. According to this study, the time-delay characteristics of the RAC system are quantified by the startup-process delay time (SPDT) and operating-phase integrated delay time (IDT). The system startup time is set by the SPDT. Based on the IDT, the prediction interval of the model predictive control (MPC) and the step time of rolling optimization are determined. On this basis, a short-term forecasting model of air conditioning operating load and the regulation model of the system using MPC are established and verified by comparing with the conventional rule-based control of constant water temperature (CRBC) and proportionally-integral-differential (PID) control. The results for the RAC system with a large time delay indicate that the stability of indoor temperature under MPC controlling is 18.8% higher than the PID control and 63.5% higher than the CRBC method. Also, the indoor temperature controlled by the MPC is closest to the set value and shows the minimum fluctuation. Furthermore, the overall energy consumption of the system is estimated for reducing by 14.89% in comparison with the CRBC and by 8.51% in comparison with the PID.

Modified smith predictor for slug control with large valve stroke time in unstable systems

Abstract: Slugging as a flow assurance challenge is an upsetting condition to the oil and gas industry due to the instabilities it poses on the system. The negative repercussions associated with slug flow stems from the inlet through to the topside facilities where processing is done. Active control has been established as one of the best techniques to eradicate slug and its accompanying challenges, however the controller robustness and some setbacks make improvement a necessity. Again, the robustness of the controller has been in question. Due to the potential of active control, several other researchers have delved into it. Many outcomes from pilot scale experiments (usually 2–4 inch valves), that shows promising and improved benefits fail to replicate when emulated on real offshore facilities (over 8 inch valve diameters). This is because of the difference in the valve stroke time (time taken for a valve to move from fully open to fully close or vice versa). Comparatively, larger diameter valves are designed to have larger stroke time than smaller diameter. In this paper, an advancement and extension of an active slug control strategy that uses measurement signals from the topside of the riser, will be used to deal with systems with time-delay as a result of large valve stroke time. The Smith predictor model was specially modified not just to deal with time-delay but also to deal with variable time-delay in both stable and unstable systems. Thus, a design of a modified smith predictor where the modification mitigates the direct estimation of the time delay itself. This is supposedly due to the internal structure of the proposed modification which, accounts for plant-model mismatch and makes small changes to the control input based on a reference controller.

Design and Application of Liquid Fertilizer pH Regulation Controller Based on BP-PID-Smith Predictive Compensation Algorithm

Abstract: The pH value of liquid fertilizer is a key factor affecting crop growth, so it is necessary to regulate its pH value. However, the pH regulation system has the characteristics of nonlinearity and time lag, which makes it difficult for the conventional controller to achieve accurate pH control. By analyzing the regulation process, this paper designs a BP-PID-Smith prediction compensator, which compensates for the error between the actual model and the theoretical model and improves the control accuracy. The pH regulation system with STM32F103ZET6 as the control core was also developed, and the performance tests were carried out under different flow rates to compare with the regulation system of PID-Smith and Smith algorithms. The experimental results showed that the maximum overshoot of the BP-PID-Smith prediction compensator was 0.27% on average, and the average adjustment time for pH value reduction from 7.5 to 6.8 was 71.39 s, which had good practicality and robustness to meet the actual control demand.

Optimal LQR and Smith Predictor Based PID Controller Design for NMP System

Abstract: In this paper, an optimal PID (proportional-integral-derivative) controller is designed for controlling the non-minimum phase system with time delay and performed greater than the conventional control approaches. When there is an increment in time delay then complications related to NMP system determines the undershoot response due to presence of zeros in the right half plane. Furthermore, Ziegler-Nichols, Internal Model Control (IMC) and Chien-Hrones & Reswick tuning approaches are developed for the conventional PID controller. The time-domain characteristics obtained are unable to persuade the requirements of the system. In order to improve the performance criteria, Smith’s predictor is used for controlling the NMP system. Smith’s predictor is better than the conventional PID controller techniques for tuning the parameters but has the incapability to achieve all the design requirements. For improving the performance requirements, the optimal PID controller is designed with the employment of Linear Quadratic Regulator (LQR). The tuning parameters of PID controller are optimal values using popular technique that is Linear Quadratic Regulator (LQR). In order to minimize integral time absolute error (ITAE) and integral time square error (ITSE), the tuning parameters are optimal and give precise values of rising time, peak time, % overshoot and settling time. The simulation results are obtained and according to that LQR gives better results than Smith Predictor and other conventional PID controller techniques.

Modified Smith predictor‐based optimal fractional PD‐PD controller for double integrating processes with considerable time delay

Abstract: Modified Smith predictor (MSP)-based fractional propotional derivative (PD)-PD controller (FO [PD-PD]) is presented here for controlling double integrating plus time delay (DIPTD) processes. The proposed scheme comprises of two fractional PD controllers together and a first-order filter to ascertain satisfactory servo as well as regulatory responses. Here, forward path fractional PD controller works towards attaining improved servo response and feedback path fractional PD controller ensures enhanced load regulation. Tuning parameters of both the controllers are obtained through optimization algorithm. The first-order filter present in the feedback path is responsible for providing improved robustness and is designed with single tuning parameter—closed-loop time constant ( λ $$ \uplambda $$ ). Efficacy of the proposed MSP-based fractional order PD-PD controller or MSP-FO (PD-PD) is substantiated through simulation study, and its superiority is established in comparison with others' recent works on DIPTD processes.

Active queue management: First steps toward a new control-theoretic viewpoint

Abstract: Active Queue Management (AQM) for mitigating Internet congestion has been addressed via various feedback control syntheses, among which P, PI, and PID regulators are quite popular and often associated to a Smith predictor. Here, to better account for the many uncertainties, like the round trip time or the number of TCP sessions, the above controllers are replaced by an intelligent proportional controller associated to Model-Free Control (MFC) and by forecasting techniques derived from a new approach to time series. Several computer simulations via a well accepted linear modeling, where the delay is assumed to be constant, are presented and discussed.

Fuzzy Smith Predictor vs Smith Predictor: An experimental evaluation for a thermal process with dead time

Abstract: This paper reviews two practical implementations of a Smith Predictor scheme applied to a thermal process using a TCLab device. The findings are presented on a qualitative comparison with ISE and ISU quantitative performance values, as well as the settling time measurement. An acceptable response was obtained with the controllers of both proposed models. However, the Fuzzy Smith Predictor has a significant advantage over the Smith Predictor in terms of the time required for the response curve to reach and stay within a range of 5% of the reference value.

Switched-Delay Smith Predictor for the Control of Plants with Response-Delay Asymmetry

Abstract: The modification of a Smith predictor for the control of plants with response-delay asymmetry has been proposed. It was developed for application in frequency converters for the control of the speed of the AC induction motor drives of pumps used in water- and liquefied-petroleum-gas-supply systems. Such plants are characterized by long response delays, and often these delays are asymmetric, i.e., the response delay to the rising and falling plant-control signal is different. A distinctive feature of the proposed modification is that the value of the response delay in the model of the plant used for the realization of the Smith predictor is switched. The operation of the proposed switched-delay Smith predictor, which was used with the proportional-integral controller, was analyzed using a simulation and experimentally in a real water-supply system. The obtained results prove an advantage of the suggested solution.

Design of robust controller for liquid level system using disturbance rejection control based on prediction

Abstract: The prime design objective of control system is to reject disturbances, to track set-point and ensure stable of closed loop response. The delay in input and slowness of process operation is observed in the many process applications. These issues create problems in control of processes. The intention of work is to develop a functional design that keeps the process status within admissible limits of delay. An approach of controller to reject disturbance on the basis of prediction is implemented in discrete time control system. An observer with extended state is used to estimate plant state and also the output without delay is obtained using filtered Smith predictor. The controller is designed for control of liquid level system. Simulation study is presented and the performance of designed controller is far better than conventional controller.

Research on precise injection control algorithm of lithium battery based on improved Smith predictor

Abstract: Aiming at the problems of large overshoot and poor robustness of valve control in the battery during liquid injection, this paper proposes an improved Smith prognosticator model based on BP network. This paper firstly analyzes the influence of lithium battery electrolyte permeability on the liquid injection accuracy, secondly studies the key factors affecting the liquid injection valve time delay problem, and then constructs the battery liquid injection system model. The fuzzy PID in this system model is to ensure the accuracy of valve flow by accumulating the output variables of fuzzy control to make them infinitely close to the desired PID parameters. In the paper, the feedback link of the Smith prognosticator is improved by using BP neural network to fit the valve, and the fitted model is applied to the Smith prognosticator to solve the problems of delay error and robustness of the traditional Smith model. The test results show that compared with the traditional Smith predictor, the Smith predictor with BP network has the advantages of short adjustment time and small tracking error, which is suitable for complex and changing working conditions and has strong robustness, and can be well applied in the lithium battery injection system.

Temperature Control System of Thermoelectric Cooler Based on Improved ADRC

Abstract: Aiming at the problems containing complex working conditions, modeling difficulties and long-time delay of thermoelectric cooler temperature control system, an improved ADRC control method combining ADRC and Smith predictor is proposed in this paper. ADRC deals with the disturbances and uncertain dynamics in the system, SP compensates the time delay to improve the control performance. Compared with the traditional PID controller, the proposed control method has faster response speed and stronger anti-disturbance ability, meanwhile, overcomes the dependence of Smith predictor on object parameters to a certain extent. Through simulation and experimental verification, a good control effect is obtained, which provides a positive guidance of the related application of thermoelectric cooler.

Two-harmonic Periodic Disturbance Compensation for Dead-Time Processes with Online Identification of Input Delay

Abstract: As in the case of the Smith predictor, when applied to dynamical systems with delay in the input, the stability of the internal model control (IMC) system can be very sensitive to the mismatch that can occur between the plant delay and the identified delay. In this paper, we propose an online identification technique for the plant with input delay, which is used to adapt an IMC controller designed to reject periodic disturbances consisting of two harmonics. The proposed method is based on wavelet analysis and cross-correlation of the measured output. Moreover, the proposed controller structure introduces a novel analytical approach which makes it suitable for the adaptive application. The practical motivation of the study is to address the delay mismatch that can be caused by approximating time-varying high-order systems by first-order models with input delay. The approach is numerically validated.

Prediction schemes for disturbance attenuation of discrete‐time linear systems with delayed input and delay‐free input

Abstract: In this article, a predictor is developed for discrete‐time linear systems with delayed input and delay‐free input to attenuate external disturbances. This predictor is designed to estimate a quantity related to the future state and input. The ultimate bounds of the state of the closed‐loop system are derived when the predictor‐based state feedback control laws are utilized to this class of delayed systems. Based on the expressions of the ultimate bounds, the disturbance attenuation performance is analyzed for the proposed prediction scheme. Moreover, the robustness to model uncertainties is analyzed when the systems are controlled by the traditional predictor‐based and the proposed predictor‐based control laws. Finally, three numerical examples are employed to show the effectiveness and the robustness of the proposed predictor.

Control of dead-time process: From the Smith predictor to general multi-input multi-output dead-time compensators

Abstract: This review paper deals with the analysis, design, and tuning of dead-time compensators for stable and unstable multi-input multi-output (MIMO) processes with multiple time delays. It is well known that, even in the single-input single-output case, processes with significant dead times are difficult to control using standard feedback controllers. For MIMO systems, the study of processes with dead time is more involved, particularly when the process behavior exhibits different dead times in the different input-output relationships. Because of this, much research has been conducted in the last 50 years on this subject, with different approaches and proposals of controllers for covering a variety of objectives. Thus, this paper gives an overview of this important topic, focusing on the solutions derived from the Smith Predictor. First, a historical perspective of the different controllers proposed in the literature is presented. Then, the general solution of the problem is developed, paying particular attention to robustness and disturbance rejection properties, because of their importance and usefulness in industrial processes. All the development is done in the discrete-time case, which allows direct digital implementation. Two simulation case studies are presented to illustrate some of the ideas discussed in the paper, and an experimental case study is used to discuss aspects of practical implementation.

LAMDA Sliding-Mode Control based on Smith Predictor applied to a pH Neutralization Reactor

Abstract: This document presents a LAMDA Sliding-Mode Control LSMC applied to a pH neutralization reactor with dominant dead time. Due to the non-linearity generated by the dead time, the application of an additional Smith Predictor structure is proposed to improve the system's response when reference changes and disturbances occur around the operating point in which the system works. The controller is validated through different simulations in which it is evident that the proposed approach is stable controlling the pH neutralization reactor.

Alleviation of Delay in Tele-Surgical Operations using Markov Approach based Smith Predictor

Abstract: The acceptance of tele-robotics and teleoperations through networked control system (NCS) is increasing day-by-day. NCS involves the feedback control loop system wherein the control components such as actuators and sensors are controlled and allowed to share their feedback over real time network with distributed users spread geographically. The performance and surgical complications majorly depend upon time delay, packet dropout and jitter induced in the system. The delay of data packet to the receiving side not only causes instability but also affect the performance of the system. In this article, author designed and simulate the functionality of a model-based Smith predictive controller. The model and randomized error estimations are employed through Markov approach and Kalman techniques. The simulation results show a delay of 49.926ms from master controller to slave controller and 79.497ms of delay from sensor to controller results to a total delay of 129.423ms. This reduced delay improve the surgical accuracy and eliminate the risk factors to criticality of patients’ health.

Performance Accretion in Delay Compensation of Networked Control System Using Markov Approach-Based Randomness Estimation in Smith Predictor

Abstract: By the second decade of the 21st century, there has been a multi-faceted technological development in the field of networked control system (NCS). This progression in NCS has not only revealed its significant applications in various areas but has also unveiled various difficulties associated with it that hampered the operations of networked control system. Network-induced delays are issues that promote many other issues like packet dropout and brevity in bandwidth utilization. In this research article, network-induced delay has been curtailed by using the harmony between Smith predictor and Markov approach. The error estimation of the Smith predictor controller used for the simulation is carried out through a Markov approach which allows the control of the system to operate smoothly by optimizing the control signal. To implement the proposed method, the authors have simulated a third order system in Matlab/Simulink software.

Optimal Controller Tuning Technique for a First-Order Process with Time Delay

Abstract: We present a controller tuning strategy for first-order plus time delay (FOPTD) processes, where the time delay in the model is approximated using the Pad\'e function. Using Routh-Hurwitz stability analysis, we derive the gain that gives rise to desirable PID controller settings. The resulting PID controller, now correctly tuned, produces satisfactory closed-loop behavior and stabilizes the first-order plant. Our proposed technique eliminates the dead-time component in the model and results in a minimum-phase system with all of its poles and zeros in the left-half $s$-plane. To demonstrate the effectiveness of our approach, we present control simulation results from an in-depth performance comparison between our technique and other established model-based strategies used for the control of time-delayed systems. These results prove that, for the FOPTD model, Pad\'e approximation eliminates the undesirable effects of the time delay and promises a faster tracking performance superior to conventional model-based controllers.

Input delay compensation of distributed time-delay systems via observer–predictors

Abstract: This work is devoted to the stabilization of linear systems with distributed delay. The approach is based on a prediction-observation protocol that allows compensating input time-delay. The proposed control scheme is tuned by optimizing the smoothed spectral abscissa, which is a smooth relaxation of the non-smooth spectral abscissa function, and provides a trade-off between the decay rate and the $mathcal{H}_2$ norm of the system. The proposed controller is applied to the stabilization of combustion in rocket motor chambers.

Robust controller based on Smith predictor for an electric EGR valve control system

Abstract: We provide an experimental proof that the Smith Predictor outperforms the PID under hard robustness constraints. It is well-known that the Smith predictor delivers excellent performance for the nominal system but its robustness is much poorer than of a corresponding PID controller. For this reason, the Smith controller never became popular in typical industrial applications. In this paper we change dramatically this viewpoint; we show that the Smith predictor can be desensitized (robustified) to achieve robust performance and stability over a wide range of parameter variations and can visibly beat the PID controller in terms of performance vs. robustness trade-offs. The basic idea for the 447robustification is to detune the nominal design to allow for less than optimal nominal performance. In particular, we require smaller than optimal rise time. As a result, the Nyquist plot of the nominal system is modified in such a way that large delay variations can be tolerated with moderate only loss of performance in the nominal case. The theoretical considerations are supported by a successful application to an automotive problem: An Exhaust Gas Recirculation (EGR) control system. The EGR system is briefly presented. Robustness is one of the main issues in this system due to nonlinearities, time delays, and the effects of complex exhaust gases dynamics. It was found after extensive measurements, identification and simulation experiments that a good approximation of the system dynamics consists of a first order transfer function with a time delay where both transfer function coefficients and the time delay strongly depend on the operating conditions (load, r.p.m., and the reference signal: desired EGR rate). The Smith predictor, well tuned to the nominal case, was found to have an excellent performance for the nominal system while the robustness was rather poor. The trade-off between the performance and robustness was achieved by relaxing the specifications for the rise time. Simulation results for both nominal and robust designs are presented as well as comparable results for an optimally tuned robust PID controller.