Research Article | Open Access

Fucheng Liao, Yonglong Liao, Jiamei Deng, "The Application of Predictor Feedback in Designing a Preview Controller for Discrete-Time Systems with Input Delay", *Mathematical Problems in Engineering*, vol. 2016, Article ID 3023915, 10 pages, 2016. https://doi.org/10.1155/2016/3023915

# The Application of Predictor Feedback in Designing a Preview Controller for Discrete-Time Systems with Input Delay

**Academic Editor:**Jean J. Loiseau

#### Abstract

This paper presents a method for designing a type one servomechanism for a discrete-time linear system with input delay subject to a previewable desired output and a nonmeasurable constant disturbance. The tracking problem of a delay system is transformed into a regulation problem of a delay-free system via constructing an augmented error system and a variable substitution. A controller is obtained with delay compensation and preview compensation based on preview control theory and the predictor method. When the state vector is not directly measurable, a full-dimensional observer is offered. The effectiveness of the design method is demonstrated by numerical simulations.

#### 1. Introduction

Preview control is one of the approaches available for producing a good performance by utilizing future information of the reference signal in the controller. Lots of work on the preview control problem have already been done. One of the early contributions was delineated in [1], in which a state-feedback controller with preview compensation is derived. Furthermore, Katayama et al. used the linear quadratic integral method to study preview control in both discrete-time and continuous-time systems [2, 3]. Servomechanisms with integral of tracking error and preview compensation are derived. Liao et al. presented a design method of an optimal preview servomechanism for discrete-time systems in multirate sampled systems [4]. Liao et al. studied the preview control problem of discrete-time descriptor systems and produced a preview controller for the systems [5]. Recently, infinite-horizon state-feedback preview tracking control of retarded state-multiplicative stochastic systems was investigated [6]. In many practical designs, preview control draws considerable favor from engineering researchers, for example, robots walking [7–9], motorcycle performance [10, 11], and protection against earthquakes [12].

During the past several decades, there have been very rich research achievements in the area of control systems with time delay. An early control method for systems with time delay is the Smith predictor [13], which overcomes the dead time effectively by adding a predictor and a compensator in the controller. Furukawa and Shimemura improved the Smith predictor and offered a new control strategy called “predictive control” [14]. The control module consists of a predictor, an observer, and a controller. Thus, the range of the controller’s application is expanded. Manitius and Olbrot studied the problems of finite spectrum assignment (FSA) of delay systems [15]. The resulting controllers involve integral compensation of the input delay and stabilize the closed-loop systems successfully. The FSA method has been a popular tool in dealing with delay systems. Stable conditions and numerical integral rules were given in [16–18] because the introduction of integral compensation in the controller might lead to closed-loop systems becoming unstable in numerical calculation [19]. Léonard and Abba studied FSA integral control robustness with respect to prediction time uncertainty for an unstable system [20]. The optimal regulation problem was studied for systems with input delay and designed optimal feedback controllers by using the duality principle and the maximum principle [21–23]. The design process was simplified by introducing a quadratic performance index with corresponding input delay in [24]. A nested predictor was established to effectively compensate for the time delay for linear systems with both state and input delays [25, 26]. Robust control and function control strategies were given, respectively, for discrete-time delay systems in [27, 28]. More recently, the optimal control problem was studied for systems with both state and input delays based on the method of letting the preview length go to zero [29]. Optimal tracking controllers for the delay systems are obtained.

For discrete-time linear systems, if the input vector has a time delay, then it is necessary to reconsider the design of the preview controller. The input delay system was transformed into a delay-free system by using the discrete lifting technique in [30, 31]. The researchers then obtained a preview controller based on preview control theory. However, it was pointed out that the discrete lifting technique may lead to “dimension disaster,” especially for systems with large delays [23, 32]. Therefore, this paper further studies the preview control problem of linear systems with input delay. A controller with delay compensation and preview compensation will be developed by using the method of predictor feedback.

This paper is organized as follows. An introduction is given in Section 1. Section 2 is a formulation of the problem and gives some basic assumptions. Section 3 uses the preview control method to construct an augmented error system. Based on Section 3, Section 4 derives a preview controller for the original system. Section 5 constructs a full-dimensional observer. And a brief conclusion is drawn in Section 6.

#### 2. Problem Formulation and Basic Assumptions

Consider a discrete-time system with input delay as follows: where is the state vector, is the input vector, is the output vector, and is the nonmeasurable constant disturbance. The positive integer represents a constant input delay of the system. , , , and are constant matrices. The vectors are initial inputs, and the vector is the initial state. All the initial vectors are known.

Let be the reference signal.

First, we give the following two basic assumptions:(A1)Let the pairs be stabilizable, let be detectable, and let the following conditions hold:(A2)Let the reference signal be previewable, and its preview length is . Namely, at the present time , the present value as well as the future values is available. The future values of the reference signal beyond time are approximated by ; namely, (). The reference signal satisfies where is a constant vector. This implies that reaches a steady state.

Furthermore, let be the error signal defined as the subtraction of and ; that is,

The purpose of this paper is to design a controller with preview compensation such that the output of the closed-loop system of (1) tracks the reference signal without any static error in the presence of disturbance ; namely,

The optimal control method is applied to achieve the goal. The performance index of (1) can be defined as where and are positive definite weight matrices. is the first-order backward difference operator; that is,

Notice that, as used in [2], the performance index (6) uses the input vector’s difference rather than . Introducing the input vector’s difference into the performance index can make the closed-loop system contain an integrator, which may help the system to eliminate static error [2, 33].

#### 3. Derivation of the Augmented Error System

The basic method of designing a preview controller for (1) is that an augmented error system is constructed firstly, then a controller is derived for the augmented error system by using optimal preview theory and predictor feedback, and finally the controller for the original system is obtained.

Using on both sides of the first equation of (1), the following will stand:where it is obvious that the disturbance vector’s difference does not appear because the disturbance is a constant.

Using on and noticing , the following will be obtained:Since , it can be seen from (8) and (9) that the error signal satisfies

Combining (8) and (10) yieldswhere

Equation (11) is called the augmented error system of (1). It is appropriate to take as the output of (11), because the output of (1) is and the reference signal is previewable.

Correspondingly, in terms of the augmented state vector , the performance index (6) can be expressed aswhere

If a controller can be derived such that the performance index (13) minimum is subject to the dynamic constraint (11), then it is easy to get , and immediately the conclusion holds. Furthermore, the input can be solved from . And, thus, the purpose is achieved. This is a standard optimal preview control problem.

#### 4. Main Results and Their Proofs

Let us introduce a new input vector Substituting (15) into (11) and (13), respectively, the following stands:

Obviously, (16) is a delay-free system and the performance criterion (17) has a normal form. Furthermore, it is known from (A2) that the reference signal is previewable in the sense that the future value is available at each instant of time . This is a preview control problem in which the system is described as (16), the quadratic performance index is described as (17), and is previewable. The following theorem will stand based on the results of [2].

Theorem 1. *If (A1) and (A2) hold and is positive definite, then the preview controller of (16) that minimizes criterion (17) is given bywherewhere is the positive semidefinite solution of the algebraic Riccati equation:Furthermore, the matrices are given bywhere is the closed-loop matrix defined by *

*Remark 2. *The future reference signal value appearing in acts as a preview compensation in the controller.

The preview controller for the augmented error system (11) can be derived from Theorem 1 by the following method.

Combining (15) and (18), the following equation will be obtained:Replacing with leads to

In (24), the current control input uses the future state vector . It is necessary to predict the future state vector to ensure that the controller is executable. Using the stepwise recurrence technique, we solve the state equation of (11): and obtain the future value of the state vector

The future value is predicted by (26). According to Assumption (A2), for the preview length , the vectors are available at ; for the preview length , the vectors are available at ; and at . Obviously, the values in (26) are all available. Equation (26) indicates that the future state vector is determined by the current state vector , the past control input , and the future reference signal’s difference . The predictor method we used above is a generalization of the predictor feedback method [14].

Substituting (26) into (24), the feedback control law of the augmented error system (11) can be obtained as follows:Considering the last term of in (27), if , let . It is obvious that (27) is an executable controller of (11) since all of the parts in (27) are known.

Let us derive a preview controller of (1). First, let where and ; then, (27) can be rewritten as

It is assumed that the initial values of system (1) and the reference signal are zeros; namely, for , the vectors , , and . Then, the following result from (29) will be obtained:

Thus, a preview control theory for system (1) will be obtained as follows.

Theorem 3. *Let (A1) and (A2) hold, let be positive definite, and let the performance index be defined as (8). Assume that , , and for . Then, the preview controller of (1) is given by where and are determined by (28), and and are given by Theorem 1.*

*Remark 4. *At each time , for the general term in , if , then the real value of is taken; if , then is taken. This is determined by Assumption (A2).

*Remark 5. *It is easy to see that the preview controller (31) is composed of four terms. The first one is the accumulation of the tracking error, which ensures that the output of the closed-loop system tracks the reference signal without static error. The second one is the state feedback. The third one is the compensation of the input delay. The last one is the preview compensation of the reference signal.

According to the character of the reference signal considered here, the abovementioned design method for the preview controller is applicable to some irregular reference signals which cannot be modeled by the dynamic system’s outputs.

Now, let us apply present theory to an air slider linear motor.

*Example 6 (see [34]). *The dynamic equation of the motor is described as follows:where is place, is velocity, is current input, is constant disturbance signal, is friction factor, is the mass of movable part, is propulsive force coefficient, and is input delay. The motor’s parameters are , , and , and could be taken as , , and , respectively.

Letthen, (33) can be rewritten asThe place of is the output vector, and it can be described as where

Taking sampling period , a discretization system is obtained:whereThe delay is determined by . According to the value of , we have , , and , respectively.

The reference signal is given as the following two types.

*(1) Step Signal*. Let the reference signal bewhich can be discretized into

*(2) Fading Signal*. Let the reference signal bewhich can be discretized intoThrough verification, is stabilizable, is detectable, and the matrix is of full row rank. Namely, Assumption (A1) is satisfied. We take the weight matrices and . By Theorem 3, there exists the preview controller described as (31) for (38).

Let the preview length of the reference signal be ; that is, . The output responses of the closed-loop system are given as in Figures 1 and 2.

The output responses of the closed-loop system tracking to the step signal are shown in Figure 1 and those to the fading signal are shown in Figure 2. From Figures 1 and 2, it can be seen that the closed-loop’s output can track the reference signal asymptotically with the controller (31). Comparing with the output responses with different delays, it can be seen that under the same preview length the tracking performance will get worse when the delay is large.

When the preview length is equal to the input delay, the future value of the reference signal is only used to compensate the delay. In order to get a better performance, let us take a larger preview length. When the input delay , the preview lengths , , and are taken; that is , , and , respectively. The output responses of the closed-loop system are given as in Figures 3 and 4.

It can be seen from Figures 3 and 4 that the tracking performance is very good when the preview length is , which indicates using the controller with preview compensation can reduce the tracking error and improve the tracking speed efficiently. On the other hand, a proper preview length can give a better response.

#### 5. Observer-Based Controller

If the state vector cannot be measured directly, then it is necessary to design an observer to obtain the estimate of the state vector.

Since is constant but cannot be measured, we take it as a portion of the desired estimate vector. System (1) can be rewritten as

Let and be the estimates of and , respectively. Let be the output values up to the step; namely, ; let be the input values up to the step; namely, . The input vector here is obtained by replacing by in (31). Then, based on and , the full-order observer for the system of (44) is given bywhere is the output of the observer and and are constant gain matrices, which are determined so that the matrixis stable.

Lemma 7. *Consider delay system (1). If is detectable and the matrix is of full column rank, then there exist suitable gains and such that (45) serves as a full-order observer of (44).*

*Proof. *According to the conclusions in [2], the pair is detectable if and only if is detectable and the matrix is of full column rank. As a consequence, there exist suitable gains and such that is stable under the conditions in Lemma 7. That is to say, the characteristic values of are less than 1. Substituting the second formula of (45) into the first one and collecting the like terms, we getLet us define the subtraction of the actual state of (44) and the estimated state of (45)as estimation error. Notice that the input vector of (44) should be . Then, it is easy to get the estimation error dynamic equation as follows: Since the matrix is stable, it follows that asymptotically converges to zero; namely,Thus, we havewhich indicates that (45) can serve as a full-order observer of (44). This completes the proof.

From Lemma 7, it is known that and can serve as the reconstructed states of and , respectively. Now, a preview control theorem with observer for system (1) is given as follows.

Theorem 8. *If (A1) and (A2) hold, is positive definite, the matrix is of full column rank, and, for , the vectors , , and , then the closed-loop system of (1) with state observer is given byThe gain matrices and are constant, which are determined such that the matrix is stable. and have the following forms: where and are determined by (28) and and are given by Theorem 1.*

*Example 9. *Consider the control system in Example 6. If the state vector cannot be measured directly, then the technique described in Theorem 8 is used to design a controller for the plant. The matrix is of full column rank and therefore there exists a full-order observer with the form of (45). Let and serve as the observer’s gain matrices. The output responses are described in Figures 5 and 6.

Compared with the responses in Figures 1 and 2, the output responses in Figures 5 and 6 have a larger error in the initial phase; the tracking performances later are almost the same. The simulation results indicate the design methods for the preview controller with full-order observer are effective.

#### 6. Conclusion

In this paper, a class of preview controller problems of discrete-time linear systems with input delay has been solved. A preview controller with delay compensation and preview compensation is derived. The difficulties of input delay are successfully overcome by predictor feedback. A design method of the full state observer is given when the state vector of the system cannot be measured directly. Numerical results show that the present methods are effective.

Further studies are needed on selecting a proper preview length according to the characteristics of the system, which is a complex problem but a significant one.

#### Competing Interests

The authors declare that they have no competing interests.

#### Acknowledgments

The authors would like to thank the National Natural Science Foundation of China for their financial support under Grant no. 61174209.

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Copyright © 2016 Fucheng Liao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.