CN111077781A - Networked control system and output tracking control method thereof - Google Patents
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Abstract
The embodiment of the invention provides a networked control system and an output tracking control method thereof, wherein the networked control system comprises a data buffer, a prediction controller and a time delay compensator; the data buffer caches an output data sequence of the controlled object, and the prediction controller is used for calculating a control quantity predicted value sequence based on a real-time dynamic linearization data model of the controlled object according to the output data sequence of the controlled object and a reference input signal, and sending the control quantity predicted value sequence to the time delay compensator; the time delay compensator selects a control signal applied to a controlled object from the control quantity predicted value sequence so as to realize active compensation of random network time delay in a feedback channel and a forward channel. The embodiment of the invention fully utilizes the packet transmission characteristic of the communication network to actively compensate the random network induced time delay, the data packet disorder and the loss existing in the feedback channel and the forward channel of the networked system.
Description
Technical Field
The invention belongs to the technical field of automatic control, and particularly relates to a networked control system and an output tracking control method thereof.
Background
In recent years, with the rapid development of industrialization and informatization, a communication network has an auxiliary function facing automation, and has gradually developed to be integrated with various industrial control systems in a comprehensive and deep manner, so that a plurality of networked control systems are generated. Compared with the traditional point-to-point control system, the networked control system has many advantages, such as: the system design and installation are simplified, the system cost and energy consumption are reduced, resource sharing and remote control are facilitated, and the flexibility, reliability, mobility and the like of the system are enhanced. Therefore, the networked control system has been widely applied to various fields of national economy and national defense construction, such as: process control, aerospace, traffic management, power production, device manufacturing, robotic control, telemedicine, unmanned aerial vehicles, automotive electronics, smart home, and the like. With the advent of the internet + intelligence era, it is expected that networked control systems will appear in more and wider fields.
However, due to the limitation of network bandwidth and other conditions, the network itself may bring many disadvantages to the networked control system, such as: network induced delays, packet misordering and loss, etc., which can lead to system performance degradation and even instability. Therefore, in recent years, many scholars and engineers have conducted intensive and extensive research and obtained a great deal of research results for networked systems with the above-mentioned communication constraints, while relatively few research has been conducted for the problem of output tracking control of networked systems, and the existing methods have the following disadvantages: 1) most methods are only suitable for linear systems, and all controlled objects are nonlinear in nature in reality, even time-varying nonlinear and strongly nonlinear; 2) most methods are designed based on models, and many controlled objects have increasingly complex structures and increasingly large scales, so that an accurate mathematical model is difficult to establish; 3) most methods are prone to generate steady-state output tracking errors when the model of the controlled object is inaccurate. Due to the limitation, the application and popularization of the conventional networked output tracking control method in actual engineering are greatly limited.
Disclosure of Invention
To overcome the above existing problems or at least partially solve the above problems, embodiments of the present invention provide a networked control system and an output tracking control method thereof.
According to a first aspect of the embodiments of the present invention, a networked control system is provided, where the networked control system includes a data buffer, a prediction controller, and a delay compensator;
the data buffer is used for buffering the output data sequence of the controlled object and sending the output data sequence of the controlled object to the prediction controller;
the prediction controller is used for calculating a control quantity predicted value sequence according to the output data sequence and the reference input signal of the controlled object, the real-time dynamic linearization data model of the controlled object according to the upper bound of the real-time network delay of the feedback channel and the random network delay of the forward channel, and sending the control quantity predicted value sequence to the delay compensator;
and the time delay compensator is used for selecting a control signal applied to a controlled object from the control quantity predicted value sequence so as to realize active compensation of random network time delay in a feedback channel and a forward channel.
According to a second aspect of the embodiments of the present invention, there is provided an output tracking control method for a networked control system, including:
the data buffer caches an output data sequence of a controlled object and sends the output data sequence of the controlled object to the prediction controller;
the prediction controller calculates a control quantity prediction value sequence based on a real-time dynamic linearization data model of the controlled object according to the output data sequence and the reference input signal of the controlled object and the upper bound of the real-time network delay of the feedback channel and the random network delay of the forward channel, and sends the control quantity prediction value sequence to the delay compensator;
and the time delay compensator selects a control signal applied to a controlled object from the control quantity predicted value sequence so as to realize active compensation of random network time delay in a feedback channel and a forward channel.
On the basis of the technical scheme, the invention can be improved as follows.
Optionally, the output data sequence of the controlled object is represented as:
Y(k)＝[y(k)y(k-1)…y(k-Ly-1)]；
at each sampling moment, the data buffer packs and sends an output data sequence Y (k) of the controlled object and a timestamp thereof to the prediction controller;
wherein L isyAnd outputting the pseudo-order for the controlled object.
Optionally, a discrete-time nonlinear system is used to describe the controlled object:
y(k+1)＝f-y(k),…,y(k-ny),u(k),…,u(k-nu))；(1)
wherein y (k) epsilon R and u (k) epsilon R are respectively the time k, the output and the input of the controlled object, f (-) is an unknown nonlinear function, nyAnd nuRespectively unknown system output order and input order.
Optionally, the method further comprises representing the discrete-time nonlinear system of the controlled object as a real-time dynamic linearized data model:
non-linear function f (-) with respect to hyu(k) There are continuous partial derivatives of each variable of (1), wherein
LyNot less than 0 and LuMore than or equal to 1, respectively outputting a pseudo order and inputting a pseudo order for the system;
for an arbitrary time k1≠k2And k is1≥0、k2Not less than 0 and hyu(k1)≠hyu(k2) All have:
|y(k1+1)-y(k2+1)|≤b|hyu(k1)-hyu(k2)|；(2)
wherein b is a constant and b > 0;
note Δ hyu(k)＝hyu(k)-hyu(k-1), when | | |. DELTA.hyu(k) When | ≠ 0 is established, the discrete-time nonlinear system of the controlled object is expressed as the following real-time dynamic linearized data model:
y(k+1)＝y(k)+φyu(k)TΔhyu(k)；(3)
in the formula (I), the compound is shown in the specification,
is a pseudo gradient and bounded for any time k.
Optionally, the calculating, by the prediction controller, the control quantity predicted value sequence according to the output data sequence and the reference input signal of the controlled object, and according to the upper bound of the real-time network delay of the feedback channel and the random network delay of the forward channel, based on the real-time dynamic linearized data model of the controlled object, and sending the control quantity predicted value sequence to the delay compensator includes:
latest output data based on received controlled object
Calculating corresponding control quantity predicted value
Wherein the content of the first and second substances,
for the feedback channel real-time network delay at time k,
is the upper bound of the random network delay of the forward channel;
a sequence of predicted values of the controlled variable corresponding to the sequence of output data of the controlled object
And its corresponding timestamp k packet is sent to the delay compensator.
Optionally, the latest output data based on the received controlled object
Calculating corresponding control quantity predicted value
The method comprises the following steps:
according to the latest output data of the controlled object
Calculating pseudo gradients of a controlled system
Estimated value of (a):
in the formula (I), the compound is shown in the specification,
is a pseudo gradient
With μ > 0 as a weighting factor, η ∈ (0, 2)]For the purpose of the step-size factor,
is composed of
Is a sufficiently small positive number, sign (-) is a sign operation function;
and (3) calculating an output increment predicted value and an output predicted value of the controlled object by combining the formula (3), the formula (5) and the formula (6):
wherein, i is 1,2, …,
and when i-j is less than or equal to 0, the following components are present:
wherein j is 1,2, …, Ly，
g＝1,2,…,Lu；
Based on the output increment predicted value and the output predicted value of the controlled object respectively calculated by the formula (7) and the formula (8), the following algorithm is adopted to obtain the output increment predicted value and the output predicted value
Control signal of the moment:
in the formula, ρi∈(0,1]Is the step factor, i ═ 1,2, …, Ly+Lu，
λ > 0 is a weighting factor,
is a reference input signal;
the prediction controller predicts a sequence of control quantity prediction values of a controlled object
And its timestamp k is sent in packets to the delay compensator.
Optionally, the selecting, by the delay compensator, the control signal applied to the controlled object from the sequence of predicted values of the controlled variable to realize active compensation of random network delays in the feedback channel and the forward channel includes:
at each sampling time, a sequence of predicted values is received based on the latest control quantity received
From which to select
And a control quantity predicted value applied to the controlled object to actively compensate the random network delay in the forward channel of the system, wherein,
the sampling time k is the random network delay of the forward channel.
The embodiment of the invention provides a networked control system and an output tracking control method thereof, wherein the method actively compensates random network induced time delay, data packet disorder and loss existing in a feedback channel and a forward channel of the networked system by fully utilizing the packet transmission characteristic of a communication network.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a schematic overall structure diagram of a networked control system according to an embodiment of the present invention;
fig. 2 is a flowchart of an output tracking control method of a networked control system according to an embodiment of the present invention;
fig. 3 is a local control effect diagram without random network delay when λ is 1;
fig. 4 is a graph of the control effect of random network delay without compensation when λ is 1;
FIG. 5 is a graph of the control effect with random network delay and compensation when λ is 1;
fig. 6 is a local control effect diagram without random network delay when λ is 6;
fig. 7 is a graph of the control effect of random network delay without compensation when λ is 6;
fig. 8 is a graph showing the control effect of compensation with a random network delay when λ is 6.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a schematic diagram illustrating an overall structure of a networked control system according to an embodiment of the present invention, where the networked control system includes a data buffer, a prediction controller, and a delay compensator.
The data buffer is used for buffering the output data sequence of the controlled object and sending the output data sequence of the controlled object to the prediction controller;
the prediction controller is used for calculating a control quantity predicted value sequence based on a real-time dynamic linearization data model of the controlled object according to the output data sequence and the reference input signal of the controlled object, the upper bound of the real-time network delay of the feedback channel and the random network delay of the forward channel, and sending the control quantity predicted value sequence to the delay compensator;
and the time delay compensator is used for selecting a control signal applied to the controlled object from the control quantity predicted value sequence so as to realize active compensation of random network time delay in the feedback channel and the forward channel.
It can be understood that the prior art has many disadvantages to the control system due to the limitation of the network bandwidth and other conditions, and the network itself, such as: network induced delays, packet misordering and loss, etc., which can lead to system performance degradation and even instability. In order to solve the problems in the prior art, embodiments of the present invention fully utilize the "packet transmission" characteristic of the communication network, and provide a networked control system based on output tracking control, so as to actively compensate the situations of random network induced delay, data packet disorder and loss existing in the feedback channel and the forward channel of the networked system.
In the embodiment of the present invention, the random network induced delay, the data packet misordering and loss in the feedback channel and the forward channel are respectively and uniformly processed into the random network delay of the respective channels (including the feedback channel and the forward channel). In order to compensate for random network delays in a feedback channel and a forward channel, a networked control system in an embodiment of the invention mainly comprises a data buffer, a prediction controller and a delay compensator.
The data buffer is arranged in the sensor and is mainly used for buffering output data of the controlled object, packaging the output data with the timestamp and sending the packaged output data to the controller.
The prediction controller is arranged in the controller, utilizes feedback data (namely output data of a controlled object and a timestamp thereof) from the data buffer, a reference input signal and historical control quantity stored in the prediction controller, calculates a control quantity predicted value based on a real-time dynamic linearized data model of the controlled object according to the upper bound of real-time network delay of a feedback channel and random network delay of a forward channel by adopting a prediction control method, and packs a group of control quantity predicted value sequences and timestamps thereof to send to the delay compensator.
The time delay compensator is arranged in the actuator, buffers the latest control quantity predicted value sequence sent from the prediction controller, and selects the control signal applied to the controlled object according to the time stamp so as to realize the active compensation of the random network time delay in the feedback channel and the forward channel.
In another embodiment of the present invention, an output tracking control method of a networked control system is provided, and fig. 2 is a flowchart of the output tracking control method of the networked control system according to the embodiment of the present invention, where the tracking control method includes:
the data buffer caches an output data sequence of a controlled object and sends the output data sequence of the controlled object to the prediction controller;
the prediction controller calculates a control quantity prediction value sequence based on a real-time dynamic linearization data model of the controlled object according to the output data sequence and the reference input signal of the controlled object and the upper bound of the real-time network delay of the feedback channel and the random network delay of the forward channel, and sends the control quantity prediction value sequence to the delay compensator;
and the time delay compensator selects a control signal applied to a controlled object from the control quantity predicted value sequence so as to realize active compensation of random network time delay in a feedback channel and a forward channel.
It can be understood that, the embodiments of the present invention fully utilize the "packet transmission" characteristic of the communication network, and provide a networked control system based on the prediction output tracking control, so as to actively compensate the situations of random network induced delay, data packet disorder and loss existing in the feedback channel and the forward channel of the networked system.
On the basis of the above embodiments, in the embodiments of the present invention, the output data sequence of the controlled object may be represented as:
Y(k)＝[y(k)y(k-1)…y(k-Ly-1)]；
the data buffer packs and sends an output data sequence Y (k) and a time stamp of the controlled object to the prediction controller at each sampling moment;
wherein L isyAnd outputting the pseudo-order for the controlled object.
On the basis of the above embodiments, in the embodiments of the present invention, a discrete-time nonlinear system is used to describe a controlled object:
y(k+1)＝f(y(k),…,y(k-ny),u(k),…,u(k-nu))；(1)
wherein y (k) E.R and u (k) E.R are respectively the time k, and the output of the controlled objectAnd input, f (-) is an unknown non-linear function, nyAnd nuRespectively unknown system output order and input order.
On the basis of the above embodiments, in the embodiment of the present invention, the discrete-time nonlinear system of the controlled object satisfies the following conditions:
(1) non-linear function f (-) with respect to hyu(k) There are continuous partial derivatives of each variable of (1), wherein
LyNot less than 0 and LuMore than or equal to 1 respectively outputs the pseudo-order and inputs the pseudo-order for the system, and the pseudo-order can be properly selected according to the complexity of the controlled system.
(2) For an arbitrary time k1≠k2And k is1≥0、k2Not less than 0 and hyu(k1)≠hyu(k2) All have:
|y(k1+1)-y(k2+1)|≤b|hyu(k1)-hyu(k2)|；(2)
wherein b is a constant and b > 0;
note Δ hyu(k)＝hyu(k)-hyu(k-1), when | | |. DELTA.hyu(k) When | ≠ 0 is established, the discrete-time nonlinear system of the controlled object can be equivalently expressed as the following real-time dynamic linearized data model:
y(k+1)＝y(k)+φyu(k)TΔhyu(k)；(3)
in the formula (I), the compound is shown in the specification,
is a pseudo gradient and bounded for any time k.
On the basis of the foregoing embodiments, in the embodiments of the present invention, the calculating, by the prediction controller, the control quantity predicted value sequence based on the real-time dynamic linearized data model of the controlled object according to the output data sequence and the reference input signal of the controlled object and according to the upper bound of the real-time network delay of the feedback channel and the random network delay of the forward channel, and sending the control quantity predicted value sequence to the delay compensator includes:
latest output data based on received controlled object
Calculating corresponding control quantity predicted value
Wherein the content of the first and second substances,
for the feedback channel real-time network delay at time k,
is the upper bound of the random network delay of the forward channel;
a sequence of predicted values of the controlled variable corresponding to the sequence of output data of the controlled object
And its corresponding timestamp k packet is sent to the delay compensator.
It can be understood that, in the embodiment of the present invention, the random network delay of the feedback channel is considered
And forward path random network delay
Based on a dynamic linearized data model, the system outputs y (k) to track a reference input signal R (k) epsilon R, namely networked output tracking control.
In the embodiment of the invention, the data buffer, the prediction controller and the time delay compensator are all time-driven, and clocks are synchronous; the random network delay of the system feedback channel and the random network delay of the forward channel are bounded, namely, the condition that the random network delay of the system feedback channel and the random network delay of the forward channel are bounded
And
wherein
And
is an integer in which, among others,
for the random network delay of the feedback channel at time k,
is the upper bound of the random network delay of the feedback channel;
is the random network delay of the forward path at time k,
is the upper bound of the random network delay of the forward path.
In the embodiment of the invention, the latest output data of the controlled object is received
Calculating corresponding control quantity predicted value
Specifically, in order to calculate the control amount predicted value
At the current time k, according to the latest output data of the controlled object
Calculating pseudo gradients of controlled objects
Is estimated byThe value, the calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
is a pseudo gradient
With μ > 0 as a weighting factor, η ∈ (0, 2)]For the purpose of the step-size factor,
is composed of
The initial value of (e) is a sufficiently small positive number, and may be 10-5Sign (·) is a sign operation function.
And (3) calculating an output increment predicted value and an output predicted value of the controlled object by combining the formula (3), the formula (5) and the formula (6):
wherein, i is 1,2, …,
and when i-j is less than or equal to 0, the following components are present:
wherein j is 1,2, …, Ly，
g＝1,2,…,Lu；
Based on the output increment predicted value and the output predicted value of the controlled object respectively calculated by the formula (7) and the formula (8), the following algorithm is adopted to obtain the output increment predicted value and the output predicted value
Control signal of the moment:
in the formula, ρi∈(0,1]Is the step factor, i ═ 1,2, …, Ly+Lu，
λ > 0 is a weighting factor,
is a reference input signal;
the prediction controller predicts a sequence of control quantity prediction values of a controlled object
And its timestamp k is sent in packets to the delay compensator.
On the basis of the foregoing embodiments, in an embodiment of the present invention, the selecting, by the delay compensator, the control signal applied to the controlled object from the sequence of predicted control quantity values to actively compensate for the random network delays in the feedback channel and the forward channel includes:
at each sampling time, a sequence of predicted values is received based on the latest control quantity received
From which to select
And a control quantity predicted value, i.e. u (k), applied to the controlled object to actively compensate the random network delay in the forward channel of the system, wherein,
the sampling time k is the random network delay of the forward channel.
The MATLAB software is utilized to perform numerical simulation verification on the output tracking control method provided by the embodiment of the invention, and the following nonlinear system is considered:
in the simulation, the initial input and output of the controlled system are all 0, and the reference input is a sine and cosine superimposed signal, as shown in fig. 3-8. The random network delay in the feedback channel in the system is 2-5 steps, and the random network delay in the forward channel is 1-4 steps, namely
The parameters are taken as: l isy＝Lu＝1，η＝1，ρ＝[1 1]，μ＝0.001，
ε＝10-5。
The simulation is divided into two cases, the first, λ ═ 1: the simulation is divided into the following 3 cases: (1) no network delay; (2) network delay but no compensation; (3) with network delay and compensation, and for comparing the output tracking performance of the three cases, defining the performance index as
The simulation results for the three cases are shown in figures 3-5, respectively.
FIG. 3 is a local control result diagram of the controlled system without random network delay, and it can be seen from FIG. 3 that the output of the controlled system can track the time-varying reference input well, and the performance index is ELCS＝3.7673。
FIG. 4 is a diagram of a control result of a controlled system with random network delay but without compensation, and it can be seen from FIG. 4 that the random network delay in the networked system finally causes divergence of the controlled system, and the performance index is ENCS＝∞。
Fig. 5 is a diagram of a control result of a controlled system with random network delay and compensation, that is, an output tracking control scheme provided by the embodiment of the present invention. As can be seen from fig. 5, compared with the control result of the uncompensated networked system (fig. 4), under the same influence of the random network delay, the compensated networked system is stable, the control effect is close to the local control effect without the random network delay (fig. 3), and the performance index is ENPCS＝17.4274。
Second, λ ═ 6, the simulation was still divided into 3 cases: (1) no network delay; (2) network delay but no compensation; (3) there is network delay and compensation. The simulation results for the three cases are shown in fig. 6-8, respectively.
Fig. 6 is a local control result diagram of the controlled system without random network delay, and it can be seen from fig. 6 that the output of the controlled system can track the time-varying reference input well, but compared with fig. 3 (λ ═ 1), the output tracking performance is slightly worse, and the performance index is E at this timeLCS＝23.0861。
FIG. 7 is a diagram of a control result of a controlled system with random network delay but without compensation, and it can be seen from FIG. 7 that although the networked system is stable, the output tracking performance of the networked system is much worse than the local control effect (FIG. 6) without random network delay, and the performance index is ENCS＝279.6587。
FIG. 8 is a diagram showing the control result of the controlled system with random network delay and compensation, i.e. the inventionThe output of the example tracks the control scheme. As can be seen from fig. 8, compared with the control result of the uncompensated networked system (fig. 7), under the same influence of the random network delay, the control effect of the compensated networked system is much better, even very close to the local control effect of the uncompensated networked system (fig. 6), and the performance index is ENPCS＝25.0877。
The embodiment of the invention provides a networked control system and an output tracking control method thereof, wherein the method actively compensates random network induced time delay, data packet disorder and loss existing in a feedback channel and a forward channel of the networked system by fully utilizing the packet transmission characteristic of a communication network.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (8)
1. A networked control system based on output tracking control is characterized by comprising a data buffer, a prediction controller and a time delay compensator;
the data buffer is used for buffering the output data sequence of the controlled object and sending the output data sequence of the controlled object to the prediction controller;
the prediction controller is used for calculating a control quantity predicted value sequence according to the output data sequence and the reference input signal of the controlled object, the real-time dynamic linearization data model of the controlled object according to the upper bound of the real-time network delay of the feedback channel and the random network delay of the forward channel, and sending the control quantity predicted value sequence to the delay compensator;
and the time delay compensator is used for selecting a control signal applied to a controlled object from the control quantity predicted value sequence so as to realize active compensation of random network time delay in a feedback channel and a forward channel.
2. An output tracking control method of the networked control system according to claim 1, comprising:
the data buffer caches an output data sequence of a controlled object and sends the output data sequence of the controlled object to the prediction controller;
the prediction controller calculates a control quantity prediction value sequence based on a real-time dynamic linearization data model of the controlled object according to the output data sequence and the reference input signal of the controlled object and the upper bound of the real-time network delay of the feedback channel and the random network delay of the forward channel, and sends the control quantity prediction value sequence to the delay compensator;
and the time delay compensator selects a control signal applied to a controlled object from the control quantity predicted value sequence so as to realize active compensation of random network time delay in a feedback channel and a forward channel.
3. The output tracking control method according to claim 2, wherein the output data sequence of the controlled object is expressed as:
Y(k)＝[y(k) y(k-1) … y(k-Ly-1)]；
at each sampling moment, the data buffer packs and sends an output data sequence Y (k) of the controlled object and a timestamp thereof to the prediction controller;
wherein L isyAnd outputting the pseudo-order for the controlled object.
4. The output tracking control method according to claim 3, characterized in that the controlled object is described by a discrete time nonlinear system:
y(k+1)＝f(y(k),…,y(k-ny),u(k),…,u(k-nu))； (1)
wherein y (k) E.R and u (k) E.R are respectively the time k, and the controlled objectF (-) is an unknown non-linear function, nyAnd nuRespectively unknown system output order and input order.
5. The output tracking control method of claim 4, further comprising representing the discrete-time nonlinear system of the controlled object as a real-time dynamic linearized data model:
non-linear function f (-) with respect to hyu(k) There are continuous partial derivatives of each variable of (1), wherein
LyNot less than 0 and LuMore than or equal to 1, respectively outputting a pseudo order and inputting a pseudo order for the system;
for an arbitrary time k1≠k2And k is1≥0、k2Not less than 0 and hyu(k1)≠hyu(k2) All have:
|y(k1+1)-y(k2+1)|≤b|hyu(k1)-hyu(k2)|； (2)
wherein b is a constant and b > 0;
note Δ hyu(k)＝hyu(k)-hyu(k-1), when | | |. DELTA.hyu(k) When | ≠ 0 is established, the discrete-time nonlinear system of the controlled object is expressed as the following real-time dynamic linearized data model:
y(k+1)＝y(k)+φyu(k)TΔhyu(k)； (3)
in the formula (I), the compound is shown in the specification,
is a pseudo gradient and bounded for any time k.
6. The output tracking control method of claim 5, wherein the calculating, by the predictive controller, a sequence of predicted values of the controlled variable based on the real-time dynamic linearized data model of the controlled object according to the output data sequence and the reference input signal of the controlled object and the upper bound of the real-time network delay of the feedback channel and the random network delay of the forward channel, and sending the sequence of predicted values of the controlled variable to the delay compensator comprises:
latest output data based on received controlled object
Calculating corresponding control quantity predicted value
Wherein the content of the first and second substances,
for the feedback channel real-time network delay at time k,
is the upper bound of the random network delay of the forward channel;
a sequence of predicted values of the controlled variable corresponding to the sequence of output data of the controlled object
And its corresponding timestamp k packet is sent to the delay compensator.
7. The output tracking control method of claim 6, wherein the receiving is based on the latest output data of the controlled object
Calculating corresponding control quantity predicted value
The method comprises the following steps:
according to the latest output data of the controlled object
Calculating pseudo gradients of a controlled system
Estimated value of (a):
wherein the content of the first and second substances,
in the formula (I), the compound is shown in the specification,
is a pseudo gradient
With μ > 0 as a weighting factor, η ∈ (0, 2)]For the purpose of the step-size factor,
is composed of
Is a sufficiently small positive number, sign (-) is a sign operation function;
and (3) calculating an output increment predicted value and an output predicted value of the controlled object by combining the formula (3), the formula (5) and the formula (6):
in the formula (I), the compound is shown in the specification,
and when i-j is less than or equal to 0, the following components are present:
wherein j is 1,2, …, Ly，
g＝1,2,…,Lu；
Based on the output increment predicted value and the output predicted value of the controlled object respectively calculated by the formula (7) and the formula (8), the following algorithm is adopted to obtain the output increment predicted value and the output predicted value
Control signal of the moment:
in the formula, ρi∈(0,1]Is the step factor, i ═ 1,2, …, Ly+Lu，
λ > 0 is a weighting factor,
is a reference input signal;
the prediction controller predicts a sequence of control quantity prediction values of a controlled object
And its timestamp k is sent in packets to the delay compensator.
8. The output tracking control method of claim 7, wherein the time delay compensator selects the control signal applied to the controlled object from the sequence of control quantity predicted values to realize the active compensation of the random network time delay in the feedback channel and the forward channel comprises:
at each sampling time, a sequence of predicted values is received based on the latest control quantity received
From which to select
And a control quantity predicted value applied to the controlled object to actively compensate the random network delay in the forward channel of the system, wherein,
the sampling time k is the random network delay of the forward channel.
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