NEURAL NETWORK SMITH PREDICTIVE CONTROL FOR TELEROBOTS WITH TIME DELAY

A neural network Smith predictive control strategy is proposed to deal with inpu t and feedback time delays in telerobot systems. The delay time is assumed to b e invariant and unknown. The proposed control structure consists of a slave syst em and a master controller. In the slave system, a recurrent neural network (RNN ) with on-line weight tuning algorithm is employed to approximate the dynamics of the time-delay-free nonlinear plant, which is used to linearize the slave s ystem. The master controller is a Smith predictor for the linearized slave syste m, which provides prediction and maintains the desirable tracking performance. S tability propriety is guaranteed based on the Lyapunov method. A simulation of a two-link robotic manipulator is provided to illustrate the effectiveness of th e proposed control strategy.

Application of Smith Predictor Based on Single Neural Network in Cold Rolling Shape Control

Flatness is one of the most important criterion factors to evaluate the quality of the steel strip. To improve the strip＇ s flatness quality, the most frequently used methodology is to employ the closed-loop automatic shape control system. However, in the shape control system, the shape-meter is always installed at the down way of the exit of the cold rolling mill and can not sense the changes of the strip flatness in the rolling gap directly. This kind of installation results in the delay of the feedback in the control system. Therefore, the stability and response performance of the system are strongly affected by the delay. At present, there is still no mature way to design controllers for systems with time delay. Although the conventional PID controller used in most practical applications has the capability to compensate the delay, the effect of the compensation is limited, especially for the systems with long time delay. Smith predictor, as a compensator for solving this problem, is now widely used in industry systems. However, the request of highly precise model of the system and the poor adaptive performance to the changes of related parameters limit the application of the Smith predictor in practice. In order to overcome the drawbacks of the Smith predictor, a new Smith predictor based on single neural network PID （SNN-PID） is proposed. Because the single neural network is employed into the Smith predictor to improve the controller＇s self-adaptability, the adaptive capability to the varying parameters of the system is improved. Meanwhile, for the purpose of solving the problems such as time-consuming and complicated calculation of the neural networks in real time, the learning coefficient of neural network is divided into several stages as usually done in expert control system. Therefore, the control system can obtain fast response due to the improved calculation speed of the neural networks. In order to validate the performance of the proposed controller, the experiment is conducted on the shape control system in a 300 mm four-high reversing cold rolling mill. The experimental results show that the SNN-PID with Smith predictor controller can effectively compensate the delay effects and achieve better control performance than the conventional PID controller.

Tuning of fuzzy PID controller for Smith predictor

An analytical tuning method was proposed for fuzzy PID controller used in Smith predictor in order to extend its application and improve its robustness. The fuzzy PID controller was expressed as a sliding mode control. Based on Lyapunov theory, Smith predictor was analyzed in time domain. The parameters of the fuzzy PID controller can be obtained using traditional linear control theory and sliding mode control theory. The simulation experiments were implemented. The simulation results show that the control performance, robustness and stability of the fuzzy PID controller are better than those of the PID controller in Smith predictor.

Monitor automatic gauge control strategy with a Smith predictor for steel strip rolling

The simplified transfer function diagram block for a monitor automatic gauge control （Mon-AGC） system of strip steel rolling process was investigated. The new notion of strip sample length was given. In this way, the delay time varying with the rolling speed was evaded. After a Smith predictor was used to monitor the AGC system, the control laws were deduced for both proportional and integral regulators. The control strategies showed that by choosing the controller parameter P=∞ for both control algo- rithms each regulator could compensate the whole strip gage error in the first control step. The result shows that the integral algo- rithm is more controllable for the system regulating process and has a better steady-state precision than the proportional regulator. Compared with the traditional control strategy, the new control laws have a faster response speed and a hieher steadv-state precision.

Improved Smith prediction monitoring AGC system based on feedback-assisted iterative learning control

The performance of Smith prediction monitoring automatic gauge control(AGC) system is influenced by model mismatching greatly in strip rolling process. Aiming at this problem, a feedback-assisted iterative learning control strategy, which learned unknown modeling error by using previous control information repeatedly, was introduced into Smith prediction monitoring AGC system. Firstly, conventional Smith predictor and improved Smith predictor with PI-P controller were analyzed. Secondly, on the basis of establishing of feedback-assisted iterative learning control strategy for improved Smith predictor, process control signal update law and control error were deduced, then convergence condition of this strategy was put forward and proved. Finally, after modeling the automatic position control system, the PI-P Smith prediction monitoring AGC system with feedback-assisted iterative learning control was researched through simulation. Simulation results indicate that this system remains stable during model mismatching. The robustness and response of monitoring AGC is improved by development of feedback-assisted iterative learning control strategy for PI-P Smith predictor.

Robust tuning method for modified smith predictor

A robust tuning method for ο^Astroem＇s two-degree of Freedom Modified Smith Predictor （MSP） is proposed, and it can achieve the fast setpoint and load disturbance responses independently. The tuning rules may meet the requirements within a certain delay margin according to the robustness theory. The simulation results illustrate that the tuning method is efficient compared with other controllers. Finally, the MSP controller is applied to the 15L batch fermentation system for controlling the temperature in bioreactor, and the experiment results further verify that the robust tuning rules may achieve good performance.

Design of decoupling Smith control for multivariable system with time delays

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.

Unified Smith Predictor Based H_∞ Wide-Area Damping Controller to Improve the Control Resiliency to Communication Failure

Inter-area low frequency oscillation in power system is one of the major problems for bulk power transmission through weak tie lines.Use of wide-area signal is more effective than the local area signal in damping out the inter-area oscillations.Wide area measurement system(WAMS)is convenient to transmit the wide area signal through the communication channel to the remote location.Communication failure is one of the disastrous phenomena in a communication channel.In this paper,a dual input single output(DISO)Hm controller is designed to build the control resiliency by employing two highest observability ranking wide area signals with respect to the critical damping inter-area mode.The proposed controller can provide sufficient damping to the system and also the system remains stabilized if one of the wide-area signals is lost.The time delay is an unwanted phenomenon that degrades the performance of the controllers.The unified Smith predictor approach is used to design a Hm controller to handle the time delay.Kundur's two-area and IEEE-39 bus test systems are considered to verify the effectiveness of the proposed controller.From the simulation results,it is verified that,the proposed controller provides excellent damping performance at normal communication and improves the controller resiliency to counteract the communication failure.

A simple anti-windup method for the Modified Smith Predictor

For the first-order integrating processes with long delay, a Modified Smith Predictor (MSP) was analyzed when the control signal saturated. If the MSP controller has no anti-windup scheme, the saturation effectively chops off the control input resulting in performance deterioration. Thus, a simple and effective anti-windup scheme, without an additional parameter, is designed for the MSP. Simulation results illustrate that the proposed method may achieve good performance under the nominal and model uncertainty cases.

Robust Stability Analysis of Smith Predictor Based Interval Fractional-Order Control Systems:A Case Study in Level Control Process

The robust stability study of the classic Smith predictor-based control system for uncertain fractional-order plants with interval time delays and interval coefficients is the emphasis of this work.Interval uncertainties are a type of parametric uncertainties that cannot be avoided when modeling real-world plants.Also,in the considered Smith predictor control structure it is supposed that the controller is a fractional-order proportional integral derivative(FOPID)controller.To the best of the authors'knowledge,no method has been developed until now to analyze the robust stability of a Smith predictor based fractional-order control system in the presence of the simultaneous uncertainties in gain,time-constants,and time delay.The three primary contributions of this study are as follows:ⅰ)a set of necessary and sufficient conditions is constructed using a graphical method to examine the robust stability of a Smith predictor-based fractionalorder control system—the proposed method explicitly determines whether or not the FOPID controller can robustly stabilize the Smith predictor-based fractional-order control system;ⅱ)an auxiliary function as a robust stability testing function is presented to reduce the computational complexity of the robust stability analysis;andⅲ)two auxiliary functions are proposed to achieve the control requirements on the disturbance rejection and the noise reduction.Finally,four numerical examples and an experimental verification are presented in this study to demonstrate the efficacy and significance of the suggested technique.

Sliding Mode Predictive Control of Main Steam Pressure in Coal-fired Power Plant Boiler

Since the combustion system of coal-fired boiler in thermal power plant is characterized as time varying, strongly coupled, and nonlinear, it is hard to achieve a satisfactory performance by the conventional proportional integral derivative (PID) control scheme. For the characteristics of the main steam pressure in coal-fired power plant boiler, the sliding mode control system with Smith predictive structure is proposed to look for performance and robustness improvement. First, internal model control (IMC) and Smith predictor (SP) is used to deal with the time delay, and sliding mode controller (SMCr) is designed to overcome the model mismatch. Simulation results show the effectiveness of the proposed controller compared with conventional ones.

Anti-windup design for the controllers of integrating processes with long delay

For several superior controllers of the first-order integrating processes with long delay, the windup problems are analyzed in detail when the control signal saturates. The results show that these controllers have similar characteristics about the process input limitation. And then, a simple and effective anti-windup scheme, without an additional parameter, is designed for these controllers. Simulations run with three main controllers, and the results illustrate that the proposed method may achieve good performance under the nominal and model uncertainty cases.

Congestion control algorithm in large-delay uncertain networks

Based on Smith-fuzzy controller, a new active queue management （AQM） algorithm adaptable to the large-delay uncertain networks is presented. It can compensate the negative impact on the queue stability caused by the large delay, and it also maintains strong robustness under the condition of dynamic network fluid. Its stability is proven through Lyapunov method. Simulation results demonstrated that this method enables the queue length to converge at a preset value quickly and keeps the queue oscillation small, the simulation results also show that the scheme is very robust to disturbance under various network conditions and large delay and, in particular, the algorithm proposed outperforms the conventional PI control and fuzzy control when the network parameters and network delay change.

Semisolid Slurry Preparation of Die Steel with High Chromium Content

The control model of laminar cooling system for hot strip, including air-cooling model, water-cooling model, temperature distribution model along thickness direction, feedforward control model, feedback control model and self-learning model, was introduced. PID arithmetic and Smith predictor controller were applied to feedback control. The sample of model parameter classification was given. The calculation process was shown by flow chart. The model has been proved to be simple, effective and of high precision.

Smith Prediction Monitor AGC System Based on Fuzzy Self-Tuning PID Control

In accordance with the feature of pure delay in monitor AGC system for cold rolling mill, a new fuzzy selftuning PID Smith prediction controller is developed. The position control model is deduced based on a single stand cold rolling mill, and the fuzzy controller for monitor AGC system is designed. The analysis of dynamic performance for traditional PID Smith prediction controller and fuzzy self-tuning PID Smith prediction controller is done by MAT- LAB toolbox. The simulation results show that fuzzy self-tuning PID Smith controller has stronger robustness, faster response and higher static accuracy than traditional PID Smith controller.

Simulation of Smith fuzzy PID temperature control in enzymatic detection of pesticide residues

Enzyme activity is easily influenced by temperature,resulting in accuracy decline of enzymatic detection of pesticide residues.In this study,a controller which controls the internal temperature of the pesticide residues detector was simulated and analyzed.The mathematical model of temperature control was established by the application of the heat transfer theory.Against models with characteristics of large inertia and large hysteresis,a Smith fuzzy PID controller was proposed by combining the Smith predictor with the fuzzy PID controller.The PID controller,the fuzzy PID controller,and the Smith fuzzy PID controller were simulated in MATLAB,respectively in the same step signal given with amplitude of 1.The performance indexes(percent overshoot,settling time,and steady-state error)of various controllers were presented as follows:the PID controller(19%,250 s,0.0001),the fuzzy PID controller(11%,450 s,0.0001),and the Smith fuzzy PID controller(0%,140 s,0).From 1180 s to 1230 s,an interference signal with amplitude of 5 was added to test interference immunity.The PID controller and the fuzzy PID controller had greater fluctuations,but the Smith fuzzy PID controller had no fluctuations.The recovery time of each controller was described below:the PID controller(200 s),the fuzzy PID controller(300 s),and the Smith fuzzy PID controller(120 s).Robustness of the controller was tested by adjusting the time constant and the delay time.The performance indexes of the controllers were shown as follows:the PID controller(38%,450 s,0.0001),the fuzzy PID controller(23%,880 s,0.00025),and the Smith fuzzy PID controller(1%,150 s,0).The results of simulation showed that the performance indexes of the Smith fuzzy PID controller were better than that of the other controllers.Besides,the robustness and interference immunity are stronger than other controllers as well.The Smith fuzzy PID controller can accurately control the internal temperature of the pesticide residues detector to provide the best temperature for enzymatic detection.

Design and analysis of a proportional-integral controller based on a Smith predictor for TCP/AQM network systems

Active queue management(AQM)is essential to prevent the degradation of quality of service in TCP/AQM systems with round-trip time(RTT)delay.RTT delays are primarily caused by packet-propagation delays,but they can also be caused by the processing time of queuing operations and dynamically changing network situations.This study focuses on the design and analysis of an AQM digital controller under time-delay uncertainty.The controller is based on the Smith predictor algorithm and is called the SMITHPI controller.This study also demonstrates the stability of the controller and its robustness against network parameter variations such as the number of TCP connections,time delays,and user datagram protocol flows.The performance,robustness,and effectiveness of the proposed SMITHPI controller are evaluated using the NS-2 simulator.Finally,the performance of the SMITHPI controller is compared with that of a well-known queue-based AQM,called the proportional-integral controller.

Algorithm Design and Application of Laminar Cooling Feedback Control in Hot Strip Mill

Feedback control is one of the most important ways to improve coiling temperature control precision during laminar cooling process.Laminar cooling equipments of a hot strip mill and structure of the control system were introduced.Feedback control algorithm based on PI controller and that based on Smith predictor were designed and tested in a hot strip mill respectively.Practical application shows that the feedback control system based on PI controller plays a limited role in improving coiling temperature control precision.The feedback control system based on Smith predictor runs stable and reliable.When the measured coiling temperature deviates from the target value,it can be adjusted to the required range quickly and steadily by Smith predictor feedback control,which improves the coiling temperature control precision greatly,and qualities of hot rolled strips are improved significantly

Robust Buffer Management Mechanism in Quality of Service Routers

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.

A Kind of Plate Laminar Cooling Strategy With High Response and Steady Precision

After Smith Predictor being used to laminar cooling system, the control law for integral regulators is introduced. New notion of plate sample length is given for evading the delay time varying with the roll table speed. It is found that the integral algorithm is more controllable for system regulating process and has better steady state precision. Compared with the traditional control strategies, the new control law has faster response speed and higher steady state precision. The controller can be regulated in shorter time and the response is faster than that of routine controller and it can effectively eliminate the oscillatory instability. Owing to its easy realization and high stability, it has been applied to a plate mill. The accuracy of finish cooling temperature can be controlled within ± 10 ℃.