Showing papers on "Smith predictor published in 2018"

A New Delay-Compensation Scheme for Networked Control Systems in Controller Area Networks

Abstract: In this work, we aim to study a new delay-compensation algorithm for networked control systems (NCSs) which are connected via the controller area network (CAN) buses. First, we analyze the property of CAN bus and find the main sources of CAN-bus-induced delays. The system controlled through a CAN bus is formulated into the typical framework of NCSs. Different from the traditional state feedback or output feedback control schemes, we propose a feedback control law with the aid of a time-domain Smith predictor. By using the augmentation technique, a closed-loop system with a delayed state is obtained. Then, the asymptotical stability property of the closed-loop system is investigated and a sufficient condition with a bilinear matrix inequality (BMI) is derived. The obtained BMI is converted into a linear matrix inequality (LMI) and the feedback gain in the proposed control law is calculated by solving the LMI condition. Finally, two application examples are given to illustrate the advantages and the effectiveness of the proposed controller design method.

On comparison of modified ADRCs for nonlinear uncertain systems with time delay

Abstract: To tackle systems with both uncertainties and time delays, several modified active disturbance rejection control (ADRC) methods, including delayed designed ADRC (DD-ADRC), polynomial based predictive ADRC (PP-ADRC), Smith predictor based ADRC (SP-ADRC) and predictor observer based ADRC (PO-ADRC), have been proposed in the past years. This paper is aimed at rigorously investigating the performance of these modified ADRCs, such that the improvements of each method can be demonstrated. The capability to tackle time delay, the necessity of stable open loop and the performance of rejecting uncertainties for these methods are fully studied and compared. It is proven that large time delay cannot be tolerated for the stability of the closed-loop systems based on DD-ADRC and PP-ADRC. Moreover, stable open loop is shown to be necessary for stabilizing the closed-loop systems based on SP-ADRC. Furthermore, the performance of rejecting the “total disturbance” at low frequency for these modified ADRCs is evaluated and quantitatively discussed. Finally, the simulations of a boiler turbine system illustrate the theoretical results.

Adaptive Fuzzy Predictive Controller for a Class of Networked Nonlinear Systems With Time-Varying Delay

Abstract: In this paper, an adaptive fuzzy predictive controller (AFPC) is designed and analyzed for a class of networked nonlinear systems with time-varying communication delay. The integration of the communication network in the control loops makes the nonlinear system has forward and feedback time-varying delays. The proposed controller compensates the network-induced delays in the forward and feedback channels. The structure of the AFPC consists of adaptive fuzzy logic control (AFLC) with state predictor located at the controlled plant and a remote adaptive smith predictive controller at the master node. The AFLC and the state predictor are utilized to identify the dynamic of the time-varying delay-free nonlinear plant in order to cancel the nonlinear term for the nonlinear control system in a canonical form. In the remote controller, adaptive smith predictor is employed to compensate the time-varying delay effect to achieve the desired tracking performance. Based on the Lyapunov theory, the stability of the closed-loop system is guaranteed in the presence of bounded external disturbance and time-varying delays. Simulated application of Van der Pol oscillator is provided to demonstrate the feasibility and effectiveness of the proposed scheme based on TrueTime toolbox.

Tracking Control for Linear Discrete-Time Networked Control Systems With Unknown Dynamics and Dropout

Abstract: This paper develops a new method for solving the optimal control tracking problem for networked control systems (NCSs), where network-induced dropout can occur and the system dynamics are unknown. First, a novel dropout Smith predictor is designed to predict the current state based on historical data measurements over the communication network. Then, it is shown that the quadratic form of the performance index is preserved even with dropout, and the optimal tracker solution with dropout is given based on a novel dropout generalized algebraic Riccati equation. New algorithms for off-line policy iteration (PI), online PI, and Q-learning PI are presented for NCS with dropout. The Q-learning algorithm adaptively learns the optimal control online using data measured over the communication network based on reinforcement learning, including dropout, without requiring any knowledge of the system dynamics. Simulation results are provided to show that the proposed approaches give proper optimal tracking performance for the NCS with unknown dynamics and dropout.

New Smith predictive fuzzy immune PID control algorithm for MIMO networked control systems

Abstract: Aiming at the problem of network-induced delays for multi-input multi-output networked control systems (MIMO NCS), a new Smith predictive fuzzy immune PID algorithm is introduced to effectively reduce the adverse effect of network-induced delays about stability in MIMO NCS, firstly, by using the v-norm type to decouple the coupling plant Based on the generalized plant after decoupling, the new Smith predictor is designed Then, an modified fuzzy immune feedback control algorithm is used to tune PID controller parameters online When there is a model mismatch or parameter perturbation, the set-point tracking performance and robustness of output response can be significantly optimized The proposed algorithm does not contain the network delay prediction model and does not need to measure, estimate, or identify the network delay It can be used in MIMO NCS where the network bandwidth is constrained and the network-induced delays are large Numerical examples with Ethernet protocol are built to illustrate the correctness and effectiveness of this new algorithm

Smith predictor based fractional-order control design for time-delay integer-order systems

Abstract: The development of fractional-order controller design methods having a few tuning parameters in the time/frequency-domain is an attractive research topic. There are a few design methods using time-domain specifications. Considering a Smith predictor structure, a simple and efficient analytical method to design a fractional-order controller for time-delay integer-order systems is proposed, in this paper. The design procedure is based on time-domain specifications. The design requirements are the percentage of overshoot and settling time. To achieve these requirements, several tuning formulas are derived based on ideal closed-loop transfer function. The main advantage of the proposed method is that it has only two tuning parameters, which can be obtained using an explicit set of tuning formulas. To demonstrate the performance of the proposed controller and to compare it with those provided by several well-known design techniques, the proposed design method is applied to two simulation examples. Finally, a robustness test is carried out considering plant uncertainties.

Stabilization Control of Electro-Optical Tracking System With Fiber-Optic Gyroscope Based on Modified Smith Predictor Control Scheme

Abstract: The electro-optical tracking system with speedability and maneuverability based on stationary platform is confronted with some problems such as external physical disturbance and detector delay. To obtain better stability, which is the key to achieving high tracking precision, a modified Smith predictor method for inertia stabilization loop control is introduced. This method proposes the Smith predictor control scheme based to compensate delay time caused by the signal filtering of fiber gyroscope sensor in the velocity feedback control, and it utilizes disturbance feedforward control to improve the stability of stabilization platform simultaneously. The design of control structure and analysis of the theory are reported. The experiment results indicate convincingly that the proposed method can effectively improve the bandwidth of velocity closed-loop. Moreover, it can drastically enhance the disturbance suppression performance of tracking platform.

Fuzzy Sliding‐mode Strategy for Air–fuel Ratio Control of Lean‐burn Spark Ignition Engines

Abstract: Minimization of emissions of carbon dioxide and harmful pollutants and maximization of fuel economy for lean-burn spark ignition (SI) engines relies to a large extent on precise air–fuel ratio (AFR) control. However, the main challenge of AFR control is the large time-varying delay in lean-burn engines. Since the system is usually subject to external disturbances and uncertainties, a high level of robustness in AFR control design must be considered. We propose a fuzzy sliding-mode control (FSMC) to track the desired AFR in the presence of periodic disturbances. The proposed method is model free and does not need any system characteristics. Based on the fuzzy system input–output data, two scaling factors are first employed to normalize the sliding surface and its derivative. According to the concept of the if-then rule, an appropriate rule table for the logic system is designed. Then, based on Lyapunov stability criteria, the output scaling factor is determined such that the closed-loop stability of the internal dynamics with uniformly ultimately bounded (UUB) performance is guaranteed. Finally, the feasibility and effectiveness of the proposed control scheme are evaluated under various operating conditions. The baseline controllers, namely, a PI controller with Smith predictor and sliding-mode controller, are also used to compare with the proposed FSMC. It is shown that the proposed FSMC has superior regulation performance compared to the baseline controllers.

A Method for Designing Decoupled Filtered Smith Predictor for Square MIMO Systems With Multiple Time Delays

Abstract: The control of multi-input and multioutput (MIMO) systems with multiple time delays is difficult to be done using classical control techniques, especially if the process is not open-loop stable. Model predictive control (MPC) is the natural choice in industry for this case, but its tuning and implementation are not trivial and, in general, cannot be done in the low level of the process control system. This paper aims to show a method to design MIMO filtered Smith predictors for $n \times n$ processes with multiple time delays based on the decentralized direct decoupling structure. This method allows an easy tuning of the primary controller by simplifying the problem to multiple single loops if the realizability conditions presented in the paper are met. The proposed method can also be used in MPC to remove the interactions between process variables. The effectiveness of the method is illustrated through two case studies.

Full Discrete Modeling, Controller Design, and Sensitivity Analysis for High-Performance Grid-Forming Converters in Islanded Microgrids

Abstract: Recent works have shown that the state-feedback decoupling of capacitor voltage allows for drastic bandwidth enlarging of current controllers for grid-forming converters in islanded microgrids. Furthermore, Smith predictor and lead compensation have been also proved as very effective implementations for compensating the controller delays. These features are key to fulfill demanding requirements in terms of voltage regulation in islanded applications. This work deepens in the discrete-time domain modeling and implementation issues of the above-mentioned techniques. A full discrete-time and sensitivity analyses reveal phenomena not properly modeled in previous works, which limits the performance: the presence of high-frequency oscillations due to discrete poles with negative real part. Subsequently, proper design countermeasures (i.e., limit bandwidth) are proposed. Discrete implementation of the voltage controller is also addressed, and design guidelines are provided. Experimental tests in accordance with the high demanding standards for uninterruptible power supply systems verify the theoretical analysis.

Improving the performance of networked control systems with time delay and data dropouts based on fuzzy model predictive control

Abstract: This paper proposes a fuzzy model predictive control (FMPC) combined with the modified Smith predictor for networked control systems (NCSs). The network delays and data dropouts are problems, which greatly reduce the controller performance. For the proposed controller, the model of the controlled system is identified on-line using the Takagi – Sugeno (T-S) fuzzy models based on the Lyapunov function. There are two internal loops in the proposed structure. The first is the loop around the FMPC, which predicts the future outputs. The other is the loop around the plant to give the error between the system model and the actual plant. The proposed controller is designed for controlling a DC servo system through a wireless network to improve the system response. The practical results based on MATLAB/SIMULINK are established. The practical results are indicated that the proposed controller is able to respond the networked time delay and data dropouts compared to other controllers.

Robust predictive scheme for input delay systems subject to nonlinear disturbances

Abstract: The predictor-based control is known as an effective method to compensate input delays. Yet the traditional predictors, like Smith predictor, have poor robustness with respect to system disturbances. In this paper, with the consideration of future disturbances, a novel robust predictive scheme is developed for input delay systems subject to nonlinear disturbances. The Artstein reduction method is used to provide performance analysis of different predictor-based controllers, which shows that the proposed predictor-based controller can provide better disturbance attenuation than previous approaches in the literature for a wide range of disturbances.

Smith predictor-based multiple periodic disturbance compensation for long dead-time processes

Abstract: Many disturbance rejection methods have been proposed for processes with dead-time, while these existing methods may not work well under multiple periodic disturbances. In this paper, a multiple periodic disturbance rejection is proposed under the Smith predictor configuration for processes with long dead-time. One feedback loop is added to compensate periodic disturbance while retaining the advantage of the Smith predictor. With information of the disturbance spectrum, the added feedback loop can remove multiple periodic disturbances effectively. The robust stability can be easily maintained through the rigorous analysis. Finally, simulation examples demonstrate the effectiveness and robustness of the proposed method for processes with long dead-time.

Robustness Improvement Using the Filtered Smith Predictor Based Fractional Integral-Fractional Derivative Controllers: Application to a Pressure Plant

Abstract: This article presents a simple frequency domain control technique to tune the parameters of a filtered Smith predictor based fractional integral-fractional derivative (FSP-FIFD) controller. The proposed method provides a practical approach to compensate stable First Order Plus Dead Time (FOPDT) transfer functions based on a filtered Smith predictor (FSP) control structure. In this control structure, an integer order predictor filter is used to improve the noise reduction of the control system. By benefiting from the proposed FSPFIFD controller, not only the phase margin and the gain crossover frequency of the control system are adjustable by tuning the free controller parameters, but also the robustness of the compensated system is enhanced. Finally, the designed FSPFIFD controller is implemented on a laboratory scale pressure plant and the obtained results are compared with those of applying a filtered Smith predictor based PI (FSPPI) controller in a similar structure. The practical results demonstrate the simplicity of application and the effectiveness of the proposed tuning rules.

Air–fuel ratio control of lean-burn SI engines using the LPV-based fuzzy technique

Abstract: Control of air–fuel ratio (AFR) plays a key role in the minimisation of the carbon dioxide and harmful pollutant emissions and maximisation of fuel economy. An inherent time-varying delay existing in lean-burn spark ignition (SI) engines is a major challenge for the AFR control. Herein an unstable internal dynamics with a parameter dependent system caused by time delay is established to represent a dominating feature of AFR. The proposed control scheme, LPV-based fuzzy control technique, combines the features of LPV and fuzzy control to deal with the unstable internal dynamics of an AFR system with external disturbances and a high level of uncertainty in system parameters. Based on the desired error dynamics, an LPV dynamic error consisting of the unstable state and the AFR tracking error is determined. Subsequently, the proposed fuzzy control algorithm through a look-up table is used to stabilise the LPV dynamic error. Then, the tracking error moves along the desired error dynamics towards zero. The system stability is assured via Lyapunov stability criteria. Finally, the simulation results demonstrate the effectiveness and robustness of the proposed control scheme under different operating conditions. Also, compared with the baseline controller, i.e. proportional–integral controller with Smith predictor, demonstrates its superiority.

Comparison of linear position and velocity control strategies for a direct servodrive

Abstract: Direct servodrives are common in applications demanding high positioning accuracy, tracking precision and motion dynamics. The optimal control structure is the key factor in obtaining the performance desired. The study considers several linear position and velocity control strategies based on either PID position control or nested loop control with P position and PI velocity controllers. For the comparative analysis the two basic control structures were enhanced with additional filters, observers and predictors. The simulation results proved by experiment show that the proposed enhancement of a nested loop control structure with a Smith predictor increases the performance to that of a system with a PID control structure. The analysis shows that PID position control structure having high performance and low computing resource utilization can be recommended for exact tracking servo applications.

A Novel Predictive Control Scheme with an Enhanced Smith Predictor for Networked Control System

Abstract: This paper presents a novel predictive control scheme with an enhanced Smith predictor for a networked control system with random time delays and system uncertainties. In the scheme, time axis is partitioned into equidistant small intervals to limit the continuous time varying delays into several discrete values. The stability of the networked control system is achieved by establishing an offline database and an online update strategy for Smith predictor, which reduces the reliance on the determined model of delay and system uncertainties in comparison with conventional Smith predictor. In this way, a sequence of finite forward predictive control signals of all possible time delays can be generated in advance and the actual delays will be compensated in real time when achieving the real delay information. Illustrative examples are given to demonstrate the effectiveness and robustness of the proposed predictive methods towards the random transmission delays and system uncertainties integrated in the networked control system.

Synthesis of model-free control for system with time-varying communication delay

Abstract: Nowadays, the model-free control scheme has led to numerous convincing applications. However, the applications of model-free control in Networked Control System (NCS) is still limited because of its weakness to process the time-varying delay which usually appears in this type of networks. This paper proposes a new method to adapt model-free controller to improve its use in NCS. This method suggests a new structure of model-free control. The main idea is based on mutual benefit between Smith predictor and the basic model-free controller. The basic model-free control will provide the required information about the plant model which will make Smith predictor free from any model information requirements. On other hand, Smith predictor will move the effect of time delay outside the closed loop of model-free control. The test result of the proposed method shows that the method can significantly help to synthesis of model-free control in NCS.