CN106896717A - A kind of two-output impulse generator network control system unpredictable time-delay SPC methods - Google Patents
A kind of two-output impulse generator network control system unpredictable time-delay SPC methods Download PDFInfo
- Publication number
- CN106896717A CN106896717A CN201710091044.3A CN201710091044A CN106896717A CN 106896717 A CN106896717 A CN 106896717A CN 201710091044 A CN201710091044 A CN 201710091044A CN 106896717 A CN106896717 A CN 106896717A
- Authority
- CN
- China
- Prior art keywords
- signal
- nodes
- network
- control circuit
- actuator
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Feedback Control In General (AREA)
Abstract
Two-output impulse generator network control system unpredictable time-delay SPC methods, belong to the MIMO NCS technical fields of limited bandwidth resources.For in a kind of TITO NCS, influenced each other between two-output impulse generator signal, transmit produced network delay among the nodes due to network data, not only influence its own close loop control circuit stability, but also another close loop control circuit stability will be influenceed, even result in the problem of TITO NCS loss of stability, propose with the network data transmission process between all real nodes in TITO NCS, instead of network delay compensation model therebetween, and dynamic Feedforward plus SPC are implemented respectively to two loops, measurement to network delay between node can be exempted using the inventive method, estimate or recognize, exempt the requirement synchronous to node clock signal, uncertain network-induced delay is reduced to TITO NCS stability influences, improve system control performance quality.
Description
Technical field
A kind of two-output impulse generator network control system unpredictable time-delay SPC (Smith Predictor Control,
SPC) method, is related to automatically control, the crossing domain of network service and computer technology, more particularly to limited bandwidth resources
MIMO Networked Control Systems technical field.
Background technology
With the development of network service, computer and control technology, and production process control increasingly maximization, wide area
The development of change, complication and networking, increasing application of net is in control system.Network control system
(Networked control systems, NCS) refers to network real-time closed-loop feedback control system, typical case's knot of NCS
Structure is as shown in Figure 1.
NCS can realize complex large system and remote control, and node resource is shared, and increase the flexibility and reliability of system, closely
Nian Laiyi is widely used in complex industrial process control, power system, petrochemical industry, track traffic, Aero-Space, environment prison
The multiple fields such as survey.
In NCS, when sensor, controller and actuator pass through network exchange data, network there may be many bags and pass
Defeated, multi-path transmission, data collision, the network congestion even phenomenon such as disconnecting so that NCS faces many new challenges.Especially
It is the presence of uncertain network-induced delay, it is possible to decrease the control quality of NCS, or even makes system loss of stability, may when serious
System is caused to break down.
At present, research both at home and abroad for NCS, primarily directed to single-input single-output (Single-input and
Single-output, SISO) network control system, constant, uncertain or random in network delay respectively, network delay is less than
One sampling period transmits more than a sampling period, the transmission of list bag or many bags, when whetheing there is data-bag lost, to it
Carry out mathematical modeling or stability analysis and controlling.But, in actual industrial process, generally existing including at least two
Multiple-input and multiple-output (the Multiple- that input is constituted with two outputs (Two-input and two-output, TITO)
Input and multiple-output, MIMO) network control system research it is then relatively fewer, in particular for based on it
The achievement in research of the delay compensation method of system architecture is then relatively less.
The typical structure of MIMO-NCS is as shown in Figure 2.
Compared with SISO-NCS, MIMO-NCS has the characteristics that：
(1) affected one another between input signal and output signal and there may be coupling
In MIMO-NCS, a change for input signal can cause that multiple output signals change, and each is defeated
Go out signal is also not only influenceed by an input signal.Even if by selection pairing meticulously between input and output signal, respectively
Also existed unavoidably between control loop and influenced each other, thus output signal is independently tracked respective input signal is have
Difficult.
(2) internal structure is more much more complex than SISO-NCS
(3) to there is probabilistic factor more for controlled device
In MIMO-NCS, the parameter being related to is more, and the contact between each control loop is more, and object parameters change is right
The influence of overall control performance can become complex.
(4) possibility of control unit failure is larger
In MIMO-NCS, including at least there is two or more close loop control circuits, and including at least having two
Individual or more than two sensors and actuator.The failure of each element may influence the performance matter of whole control system
Amount, can make system unstable, or even cause a serious accident when serious.
Due to the above-mentioned particularity of MIMO-NCS so that be designed the method with control based on SISO-NCS, cannot
Meet the requirement of the control performance of MIMO-NCS and control quality, prevent its from or be not directly applicable the design of MIMO-NCS
In control, the design and analysis to MIMO-NCS bring difficulty.
For MIMO-NCS, network delay compensation is essentially consisted in the difficult point of control：
(1) due to network delay and network topology structure, communication protocol, offered load, the network bandwidth and data package size
It is relevant etc. factor, to more than several or even the dozens of sampling period uncertain network-induced delay, to set up in MIMO-NCS each
The Mathematical Modeling that the uncertain network-induced delay of control loop is accurately predicted, estimates or recognized, is currently what is had any problem.
(2) occur in MIMO-NCS, when previous node is to network during latter node-node transmission network data
Prolong, no matter using which kind of prediction or method of estimation in previous node, be impossible to know the net for producing thereafter in advance in advance
The exact value of network time delay.Time delay causes systematic function to decline or even causes system unstable, while also to the analysis of control system
Difficulty is brought with design.
(3) to meet in MIMO-NCS, all node clock signal Complete Synchronizations in different distributions place are unpractical.
(4) due in MIMO-NCS, being affected one another between input and output signal, and there may be coupling, system
Internal structure is more complicated than SISO-NCS, and the uncertain factor for existing is more, the control performance quality good or not of each control loop
Influence will be produced on the performance quality of whole system and stability with its stability problem and will be restricted, its implement delay compensation with
Control is more much more difficult than SISO-NCS.
The content of the invention
The uncertain net of a kind of two-output impulse generator network control system (TITO-NCS) in the present invention relates to MIMO-NCS
The compensation of network time delay and control, the typical structure of its TITO-NCS are as shown in Figure 3.
For the close loop control circuit 1 in Fig. 3：
1) from input signal x1S () arrives output signal y1S the closed loop transfer function, between () is：
In formula：C1S () is controller, G11S () is controlled device；τ1Represent control signal u1S () is from C1(s) controller
The C1 nodes at place, the uncertain network-induced delay that actuator A1 nodes are experienced is transferred to through preceding to network path；τ2Representing will
Output signal y1(s) from sensor S1 nodes, through feedback network tunnel to C1S the C1 nodes where () controller are experienced
Uncertain network-induced delay.
2) from the drive signal u of the actuator A2 nodes of close loop control circuit 2 output2S (), is intersected logical by controlled device
Road transmission function G12S () influences the output signal y of close loop control circuit 11(s), from input signal u2S () arrives output signal y1(s)
Between closed loop transfer function, be：
Above-mentioned closed loop transfer function, equation (1) and the denominator of (2)In, contain uncertain network
Delay, τ1And τ2Exponential termWithThe presence of time delay will deteriorate the performance quality of control system, even result in system mistake
Go stability.
For the close loop control circuit 2 in Fig. 3：
1) from input signal x2S () arrives output signal y2S the closed loop transfer function, between () is：
In formula：C2S () is controller, G22S () is controlled device；τ3Represent control signal u2S () is from C2(s) controller
The C2 nodes at place, the uncertain network-induced delay that actuator A2 nodes are experienced is transferred to through preceding to network path；τ4Representing will
Output signal y2(s) from sensor S2 nodes, through feedback network tunnel to C2S the C2 nodes where () controller are experienced
Uncertain network-induced delay.
2) from the drive signal u of the actuator A1 nodes of close loop control circuit 1 output1S (), is intersected logical by controlled device
Road transmission function G21S () influences the output signal y of close loop control circuit 22(s), from input signal u1S () arrives output signal y2(s)
Between closed loop transfer function, be：
Above-mentioned closed loop transfer function, equation (3) and the denominator of (4)In, contain uncertain network
Delay, τ3And τ4Exponential termWithThe presence of time delay loses the performance quality of control system, the system of even resulting in is deteriorated
Stability.
Goal of the invention：
For the TITO-NCS of Fig. 3, in the transmission function equation (1) of its close loop control circuit 1 and the denominator of (2), wrap
Uncertain network-induced delay τ is contained1And τ2Exponential termWithAnd close loop control circuit 2 transmission function equation (3) and
(4) in denominator, uncertain network-induced delay τ is contained3And τ4Exponential termWith
Due to the output signal y of close loop control circuit 11S () is not only subject to its input signal x1The influence of (s), while also receiving
To the input signal x of close loop control circuit 22The influence of (s)；At the same time, the output signal y of close loop control circuit 22S () not only
By its input signal x2The influence of (s), while also by the input signal x of close loop control circuit 11The influence of (s).During network
The presence prolonged can reduce the control performance quality of respective close loop control circuit and influence the stability of respective close loop control circuit, together
When will also decrease the control performance quality of whole system and influence the stability of whole system, whole system will be caused to lose when serious
Go stability.
Therefore, for the close loop control circuit 1 in Fig. 3 and loop 2, the present invention proposes that one kind adds SPC based on dynamic Feedforward
Delay compensation method；In exempting to each close loop control circuit, the measurement of uncertain network-induced delay, estimation between node
Or identification, and then reduce network delay τ1And τ2, and τ3And τ4To respective close loop control circuit and to whole control system control
The influence of performance quality processed and the stability of a system；When prediction model is equal to its true model, it is capable of achieving respective closed-loop control and returns
Exponential term not comprising network delay in the characteristic equation on road, and then shadow of the network delay to whole system stability can be reduced
Ring, improve the dynamic property quality of system, realize segmentation, real-time, online and dynamic to TITO-NCS uncertain network-induced delays
Predictive compensation and SPC control.
Using method：
For the close loop control circuit 1 in Fig. 3：
The first step：In order to realize meeting during predictive compensation condition, no longer wrapped in the closed loop transform function of close loop control circuit 1
Exponential term containing network delay, to realize to network delay τ1And τ2Compensation with control, use with control signal u1(s) conduct
Input signal, controlled device prediction model G11mS (), used as controlled process, control is pre- by network transfer delay with process data
Estimate modelAndAround controller C in controller C1 nodes1(s), one positive feedback Prediction Control loop of construction and
One negative-feedback Prediction Control loop；In controlled device G11S () holds, build a dynamic Feedforward controller D12(s), for dropping
The low interference signal u from close loop control circuit 22pS () passes through cross jamming passage G12S () is to the dynamic of close loop control circuit 1
The influence of energy, while D12S () has uneoupled control effect concurrently；The structure for implementing this step is as shown in Figure 4；
Second step：In for actual TITO-NCS, it is difficult to obtain the problem of network delay exact value, to realize in fig. 4
Compensation and SPC to network delay, in addition to the condition that controlled device prediction model to be met is equal to its true model, it is necessary to
Meet uncertain network-induced delay prediction modelAndTo be equal to its true modelAndCondition.Therefore,
From sensor S1 nodes to controller C1 nodes, and from controller C1 nodes to actuator A1 nodes, using true
Real network data transmission processAndInstead of network delay predict-compensate model therebetweenAndThus nothing
Whether its true model is equal to by the prediction model of controlled device, when can be realized from system architecture not comprising network therebetween
The predict-compensate model for prolonging, so that in exempting to close loop control circuit 1, uncertain network-induced delay τ between node1And τ2Measurement,
Estimate or recognize；When prediction model is equal to its true model, it is capable of achieving to its uncertain network-induced delay τ1And τ2Compensation with
SPC；The network delay compensation for implementing the inventive method is as shown in Figure 5 with SPC structures；
For the close loop control circuit 2 in Fig. 3：
The first step：In order to realize meeting during predictive compensation condition, no longer wrapped in the closed loop transform function of close loop control circuit 2
Exponential term containing network delay, to realize to network delay τ3And τ4Compensation with control, use with control signal u2(s) conduct
Input signal, controlled device prediction model G22mS (), used as controlled process, control is pre- by network transfer delay with process data
Estimate modelAndAround controller C in controller C2 nodes2S (), constructs a positive feedback Prediction Control loop
With a negative-feedback Prediction Control loop；In controlled device G22S () holds, build a dynamic Feedforward controller D21S (), is used for
Reduce the interference signal u from close loop control circuit 11pS () passes through cross jamming passage G21S () is to the dynamic of close loop control circuit 2
The influence of performance, while D21S () has uneoupled control effect concurrently；The structure for implementing this step is as shown in Figure 4；
Second step：In for actual TITO-NCS, it is difficult to obtain the problem of network delay exact value, to realize in fig. 4
Compensation and SPC to network delay, in addition to the condition that controlled device prediction model to be met is equal to its true model, it is necessary to
Meet uncertain network-induced delay prediction modelAndTo be equal to its true modelAndCondition.Therefore,
From sensor S2 nodes to controller C2 nodes, and from controller C2 nodes to actuator A2 nodes, using true
Real network data transmission processAndInstead of network delay predict-compensate model therebetweenAndThus nothing
Whether its true model is equal to by the prediction model of controlled device, when can be realized from system architecture not comprising network therebetween
The predict-compensate model for prolonging, so that in exempting to close loop control circuit 2, uncertain network-induced delay τ between node3And τ4Measurement,
Estimate or recognize；When prediction model is equal to its true model, it is capable of achieving to its uncertain network-induced delay τ3And τ4Compensation with
SPC；The network delay compensation for implementing the inventive method is as shown in Figure 5 with SPC structures；
For the close loop control circuit 1 in Fig. 5：
1) from input signal x1S () arrives output signal y1S the closed loop transfer function, between () is：
In formula：G11mS () is controlled device G11The prediction model of (s), C1S () is controller.
2) the signal u of actuator A2 nodes in close loop control circuit 2 is come from2p(s), by dynamic Feedforward controller D12
S () acts on close loop control circuit 1；At the same time, signal u2pS () passes through cross jamming passage G12S () acts on closed-loop control
Loop 1；From input signal u2pS () arrives output signal y1S the closed loop transfer function, between () is：
Using the inventive method, when controlled device prediction model is equal to its true model, that is, work as G11m(s)=G11When (s),
The closed loop transform function of close loop control circuit 1 byBecome 1+C1(s)
G11(s)=0, no longer comprising the network delay τ of the influence stability of a system in its closed loop transform function1And τ2Exponential term
WithSo as to influence of the network delay to the stability of a system can be reduced, improve the dynamic control performance quality of system, it is right to realize
The dynamic compensation of uncertain network-induced delay and SPC.
For the close loop control circuit 2 in Fig. 5：
1) from input signal x2S () arrives output signal y2S the closed loop transfer function, between () is：
In formula：G22mS () is controlled device G22The prediction model of (s), C2S () is controller.
2) the signal u of actuator A1 nodes in close loop control circuit 1 is come from1p(s), by dynamic Feedforward controller D21
S () acts on close loop control circuit 2；At the same time, signal u1pS () passes through cross jamming passage G21S () acts on closed-loop control
Loop 2；From input signal u1pS () arrives output signal y2S the closed loop transfer function, between () is：
Using the inventive method, when controlled device prediction model is equal to its true model, that is, work as G22m(s)=G22When (s),
The closed loop transform function of close loop control circuit 2 byBecome 1+C2(s)
G22(s)=0, no longer comprising the network delay τ of the influence stability of a system in its closed loop transform function3And τ4Exponential termWithSo as to influence of the network delay to the stability of a system can be reduced, improve the dynamic control performance quality of system, realize
To the dynamic compensation of uncertain network-induced delay and SPC.
In close loop control circuit 1 and loop 2, dynamic Feedforward controller D12(s) and D21The selection of (s)：
Influence close loop control circuit 1 and the interference signal u of the control performance quality of loop 22p(s) and u1p(s), by intersecting
Interfering channel G12(s) and G21S () acts on close loop control circuit 1 and loop 2, using dynamic Feedforward controller D12(s) and D21
S () is used to reduce interference signal to close loop control circuit 1 and the influence of the dynamic property of loop 2.Under normal circumstances, D may be selected12
(s)=G12(s)/G11(s), D21(s)=G21(s)/G22(s)。
The scope of application of the invention：
A kind of two-output impulse generator network control system of its true model is equal to suitable for controlled device prediction model
(TITO-NCS) compensation of uncertain network-induced delay adds SPC with dynamic Feedforward；Its Research Thinking and method, can equally be well applied to by
When control object prediction model is equal to MIMO Networked Control Systems (MIMO-NCS) uncertain network of its true model
The compensation prolonged and dynamic Feedforward plus SPC.
It is a feature of the present invention that the method is comprised the following steps：
For close loop control circuit 1：
(1) is h when the sensor S1 nodes cycle1Sampled signal trigger when, employing mode A is operated；
(2) is when controller C1 nodes are by feedback signal y1bWhen () triggers s, employing mode B is operated；
(3) works as actuator A1 node controlled signals u1When () triggers s, employing mode C is operated；
For close loop control circuit 2：
(4) is h when the sensor S2 nodes cycle2Sampled signal trigger when, employing mode D is operated；
(5) is when controller C2 nodes are by feedback signal y2bWhen () triggers s, employing mode E is operated；
(6) works as actuator A2 node controlled signals u2When () triggers s, employing mode F is operated；
The step of mode A, includes：
A1：Sensor S1 nodes work in time type of drive, and its trigger signal is cycle h1Sampled signal；
A2：After sensor S1 nodes are triggered, to controlled device G11The output signal y of (s)11S () and controlled device are intersected
Channel transfer function G12The output signal y of (s)12(s), and actuator A1 nodes output signal y11mbS () is sampled, and
Calculate the system output signal y of close loop control circuit 11(s) and feedback signal y1b(s), and y1(s)=y11(s)+y12(s) and
y1b(s)=y1(s)-y11mb(s)；
A3：By feedback signal y1b(s), by the feedback network path of close loop control circuit 1 to controller C1 node-node transmissions,
Feedback signal y1bS () will experience network transfer delay τ2Afterwards, controller C1 nodes are got to；
The step of mode B, includes：
B1：Controller C1 nodes work in event driven manner, by feedback signal y1bS () is triggered；
B2：In controller C1 nodes, by the system Setting signal x of close loop control circuit 11S (), subtracts feedback signal y1b
(s) and controlled device prediction model G11mThe output valve y of (s)11maS (), obtains deviation signal e1(s), i.e. e1(s)=x1(s)-y1b
(s)-y11ma(s)；
B3：To e1S () implements control algolithm C1S (), obtains control signal u1(s)；
B4：By control signal u1S feedforward network path that () passes through close loop control circuit 1Unit is to actuator A1 nodes
Transmission, u1S () will experience network transfer delay τ1Afterwards, actuator A1 nodes are got to；
The step of mode C, includes：
C1：Actuator A1 nodes work in event driven manner, controlled signal u1S () is triggered；
C2：In actuator A1 nodes, by control signal u1S () acts on controlled device prediction model G11mS () obtains it
Output valve y11mb(s)；The signal u of the actuator A2 nodes of close loop control circuit 2 will be come from2pS () acts on dynamic Feedforward control
Device D12S () obtains its output valve ud12(s)；By control signal u1(s) and ud12S () subtracts each other to obtain actuator A1 output signal nodes u1p
(s), i.e. u1p(s)=u1(s)-ud12(s)；
C3：By signal u1pS () acts on controlled device G11S () obtains its output valve y11(s)；By signal u1pS () acts on
Controlled device cross aisle transmission function G21S () obtains its output valve y21(s)；So as to realize to controlled device G11(s) and G21
The dynamic Feedforward control of (s) plus SPC, while realizing to uncertain network-induced delay τ1And τ2Compensation with control；
The step of mode D, includes：
D1：Sensor S2 nodes work in time type of drive, and its trigger signal is cycle h2Sampled signal；
D2：After sensor S2 nodes are triggered, to controlled device G22The output signal y of (s)22S () and controlled device are intersected
Channel transfer function G21The output signal y of (s)21(s), and actuator A2 nodes output signal y22mbS () is sampled, and
Calculate the system output signal y of close loop control circuit 22(s) and feedback signal y2b(s), and y2(s)=y22(s)+y21(s) and
y2b(s)=y2(s)-y22mb(s)；
D3：By feedback signal y2b(s), by the feedback network path of close loop control circuit 2 to controller C2 node-node transmissions,
Feedback signal y2bS () will experience network transfer delay τ4Afterwards, controller C2 nodes are got to；
The step of mode E, includes：
E1：Controller C2 nodes work in event driven manner, by feedback signal y2bS () is triggered；
E2：In controller C2 nodes, by the system Setting signal x of close loop control circuit 22S (), subtracts feedback signal y2b
(s) and controlled device prediction model G22mThe output valve y of (s)22maS (), obtains deviation signal e2(s), i.e. e2(s)=x2(s)-y2b
(s)-y22ma(s)；
E3：To e2S () implements control algolithm C2S (), obtains control signal u2(s)；
E4：By control signal u2S feedforward network path that () passes through close loop control circuit 2Unit is saved to actuator A2
Point transmission, u2S () will experience network transfer delay τ3Afterwards, actuator A2 nodes are got to；
The step of mode F, includes：
F1：Actuator A2 nodes work in event driven manner, controlled signal u2S () is triggered；
F2：In actuator A2 nodes, by control signal u2S () acts on controlled device prediction model G22mS () obtains it
Output valve y22mb(s)；The signal u of the actuator A1 nodes of close loop control circuit 1 will be come from1pS () acts on dynamic Feedforward control
Device D21S () obtains its output valve ud21(s)；By control signal u2(s) and ud21S () subtracts each other to obtain actuator A2 output signal nodes u2p
(s), i.e. u2p(s)=u2(s)-ud21(s)；
F3：By signal u2pS () acts on controlled device G22S () obtains its output valve y22(s)；By signal u2pS () acts on
Controlled device cross aisle transmission function G12S () obtains its output valve y12(s)；So as to realize to controlled device G22(s) and G12
The dynamic Feedforward control of (s) plus SPC, while realizing to uncertain network-induced delay τ3And τ4Compensation with control；
The present invention has following features：
1st, due to from exempting in structure in TITO-NCS, the measurement of uncertain network-induced delay, observation, estimate or recognize,
The synchronous requirement of node clock signal can also be exempted simultaneously, time delay can be avoided to estimate the inaccurate evaluated error for causing of model, kept away
Exempt to expending the waste of node storage resources needed for time-delay identification, at the same can also avoid " sky sampling " that is caused due to time delay or
The compensation error that " sampling " brings more.
2nd, it is unrelated with the selection of specific network communication protocol due to from TITO-NCS structures, realizing, thus be both applicable
In the TITO-NCS using wired network protocol, the TITO-NCS of wireless network protocol is also applicable for use with；It is not only suitable for determining
Property procotol, also suitable for the procotol of uncertainty；The TITO-NCS of heterogeneous network composition is not only suitable for, while also fitting
For the TITO-NCS that heterogeneous network is constituted.
3rd, it is unrelated with the selection of the control strategy of specific controller due to from TITO-NCS structures, realizing, thus both may be used
For the TITO-NCS using conventional control, also can be used for using Based Intelligent Control or the TITO-NCS using complex control strategy.
4th, the control loop 1 in TITO-NCS：Using dynamic Feedforward controller D12S (), can reduce from closed-loop control
The interference signal u in loop 22pS () passes through cross jamming passage G12The influence of (s) to the dynamic property of close loop control circuit 1, while
D12S () has uneoupled control effect concurrently.
5th, the control loop 2 in TITO-NCS：Using dynamic Feedforward controller D21S (), can reduce from closed-loop control
The interference signal u in loop 11pS () passes through cross jamming passage G21The influence of (s) to the dynamic property of close loop control circuit 2, while
D21S () has uneoupled control effect concurrently.
6th, because the present invention uses compensation and control method that " software " changes TITO-NCS structures, thus in fact
Any hardware device need not be further added by during existing, the software resource carried using existing TITO-NCS intelligent nodes, it is sufficient to real
Existing its compensation and control function, can save hardware investment and be easy to be extended and applied.
Brief description of the drawings
Fig. 1：The typical structure of NCS
Fig. 1 is by sensor S nodes, controller C nodes, actuator A nodes, controlled device, feedforward network tunnel list
UnitAnd feedback network tunnel unitConstituted.
In Fig. 1：X (s) represents system input signal；Y (s) represents system output signal；C (s) represents controller；U (s) tables
Show control signal；τcaThe feedforward network that control signal u (s) is experienced in expression from controller C nodes to actuator A node-node transmissions
Tunnel time delay；τscThe feedback net that detection signal y (s) of sensor S nodes is experienced in expression to controller C node-node transmissions
Network tunnel time delay；G (s) represents controlled device transmission function.
Fig. 2：The typical structure of MIMO-NCS
Fig. 2 is by r sensor S node, controller C nodes, m actuator A node, controlled device G, m feedforward network
Tunnel time delayUnit, and r feedback network tunnel time delayUnit institute group
Into.
In Fig. 2：yjS () represents j-th output signal of system；uiS () represents i-th control signal；Representing will control
Signal uiS feedforward network tunnel time delay that () is experienced from from controller C nodes to i-th actuator A node-node transmission；Table
Show j-th detection signal y of sensor S nodesjS feedback network tunnel that () is experienced to controller C node-node transmissions
Time delay；G represents controlled device transmission function.
Fig. 3：The typical structure of TITO-NCS
Fig. 3 is made up of close loop control circuit 1 and 2, and its system includes sensor S1 and S2 node, controller C1 and C2 section
Point, actuator A1 and A2 node, controlled device transmission function G11(s) and G22(s) and controlled device cross aisle transmission function
G21(s) and G12(s), feedforward network tunnel unitWithAnd feedback network tunnel unitWithInstitute
Composition.
In Fig. 3：x1(s) and x2S () represents the input signal of system；y1(s) and y2S () represents the output signal of system；C1
(s) and C2S () represents the controller of control loop 1 and 2；u1(s) and u2S () represents control signal；τ1And τ3Represent and believe control
Number u1(s) and u2S feedforward network tunnel that () is experienced from controller C1 and C2 from node to actuator A1 and A2 node-node transmission
Time delay；τ2And τ4Represent the detection signal y of sensor S1 and S2 node1(s) and y2S () is to controller C1 and C2 node-node transmission
The feedback network tunnel time delay for being experienced.
Fig. 4：A kind of TITO-NCS delay compensations comprising prediction model and control structure
In Fig. 4：C1S () is the controller of control loop 1；C2S () is the controller of control loop 2；AndIt is
Network transfer delayAndEstimate Time Delay Model；AndIt is network transfer delayAndIt is pre-
Estimate Time Delay Model；G11mS () is controlled device transmission function G11The prediction model of (s)；G22mS () is controlled device transmission function
G22The prediction model of (s)；D12(s) and D21S () is dynamic Feedforward controller.
Fig. 5：A kind of two-output impulse generator network control system unpredictable time-delay SPC methods
Specific embodiment
Exemplary embodiment of the invention will be described in detail by referring to accompanying drawing 5 below, make the ordinary skill people of this area
Member becomes apparent from features described above of the invention and advantage.
Specific implementation step is as described below：
For close loop control circuit 1：
The first step：Sensor S1 nodes work in time type of drive, are h when the sensor S1 nodes cycle1Sampling
After signal triggering, will be to controlled device G11The output signal y of (s)11(s) and controlled device cross aisle transmission function G12(s)
Output signal y12(s), and actuator A1 nodes output signal y11mbS () is sampled, and calculate close loop control circuit 1
System output signal y1(s) and feedback signal y1b(s), and y1(s)=y11(s)+y12(s) and y1b(s)=y1(s)-y11mb
(s)；
Second step：Sensor S1 nodes are by feedback signal y1b(s), by the feedback network path of close loop control circuit 1 to
Controller C1 node-node transmissions, feedback signal y1bS () will experience network transfer delay τ2Afterwards, controller C1 nodes are got to；
3rd step：Controller C1 nodes work in event driven manner, by feedback signal y1bS () triggers after, by closed loop
The system Setting signal x of control loop 11S (), subtracts feedback signal y1b(s) and controlled device prediction model G11mThe output of (s)
Value y11maS (), obtains deviation signal e1(s), i.e. e1(s)=x1(s)-y1b(s)-y11ma(s)；To e1S () implements control algolithm C1
S (), obtains control signal u1(s)；
4th step：By control signal u1S feedforward network path that () passes through close loop control circuit 1Unit is to actuator A1
Node-node transmission, u1S () will experience network transfer delay τ1Afterwards, actuator A1 nodes are got to；
5th step：Actuator A1 nodes work in event driven manner, controlled signal u1S () triggers after, will control
Signal u1S () acts on controlled device prediction model G11mS () obtains its output valve y11mb(s)；Close loop control circuit 2 will be come from
The signal u of actuator A2 nodes2pS () acts on dynamic Feedforward controller D12S () obtains its output valve ud12(s)；Control is believed
Number u1(s) and ud12S () subtracts each other to obtain actuator A1 output signal nodes u1p(s), i.e. u1p(s)=u1(s)-ud12(s)；
6th step：By signal u1pS () acts on controlled device G11S () obtains its output valve y11(s)；By signal u1pS () is made
For controlled device cross aisle transmission function G21S () obtains its output valve y21(s)；So as to realize to controlled device G11(s) and
G21The dynamic Feedforward control of (s) plus SPC, while realizing to uncertain network-induced delay τ1And τ2Compensation with control；
7th step：Return to the first step；
For close loop control circuit 2：
The first step：Sensor S2 nodes work in time type of drive, are h when the sensor S2 nodes cycle2Sampling
After signal triggering, will be to controlled device G22The output signal y of (s)22(s) and controlled device cross aisle transmission function G21(s)
Output signal y21(s), and actuator A2 nodes output signal y22mbS () is sampled, and calculate closed-loop control time
The system output signal y on road 22(s) and feedback signal y2b(s), and y2(s)=y22(s)+y21(s) and y2b(s)=y2(s)-y22mb
(s)；
Second step：By feedback signal y2b(s), by the feedback network path of close loop control circuit 2 to controller C2 nodes
Transmission, feedback signal y2bS () will experience network transfer delay τ4Afterwards, controller C2 nodes are got to；
3rd step：Controller C2 nodes work in event driven manner, by feedback signal y2bS () triggers after, by closed loop
The system Setting signal x of control loop 22S (), subtracts feedback signal y2b(s) and controlled device prediction model G22mThe output of (s)
Value y22maS (), obtains deviation signal e2(s), i.e. e2(s)=x2(s)-y2b(s)-y22ma(s)；To e2S () implements control algolithm C2
S (), obtains control signal u2(s)；
4th step：By control signal u2S feedforward network path that () passes through close loop control circuit 2Unit is to actuator
A2 node-node transmissions, u2S () will experience network transfer delay τ3Afterwards, actuator A2 nodes are got to；
5th step：Actuator A2 nodes work in event driven manner, controlled signal u2S () triggers after, will control
Signal u2S () acts on controlled device prediction model G22mS () obtains its output valve y22mb(s)；Close loop control circuit 1 will be come from
The signal u of actuator A1 nodes1pS () acts on dynamic Feedforward controller D21S () obtains its output valve ud21(s)；Control is believed
Number u2(s) and ud21S () subtracts each other to obtain actuator A2 output signal nodes u2p(s), i.e. u2p(s)=u2(s)-ud21(s)；
6th step：By signal u2pS () acts on controlled device G22S () obtains its output valve y22(s)；By signal u2pS () is made
For controlled device cross aisle transmission function G12S () obtains its output valve y12(s)；So as to realize to controlled device G22(s) and
G12The dynamic Feedforward control of (s) plus SPC, while realizing to uncertain network-induced delay τ3And τ4Compensation with control；
7th step：Return to the first step；
The foregoing is only presently preferred embodiments of the present invention and oneself, be not intended to limit the invention, it is all in essence of the invention
Within god and principle, any modification, equivalent substitution and improvements made etc. should be included within the scope of the present invention.
The content not being described in detail in this specification belongs to prior art known to professional and technical personnel in the field.
Claims (4)
1. a kind of two-output impulse generator network control system unpredictable time-delay SPC methods, it is characterised in that the method includes following
Step：
For close loop control circuit 1：
(1) is h when the sensor S1 nodes cycle1Sampled signal trigger when, employing mode A is operated；
(2) is when controller C1 nodes are by feedback signal y1bWhen () triggers s, employing mode B is operated；
(3) works as actuator A1 node controlled signals u1When () triggers s, employing mode C is operated；
For close loop control circuit 2：
(4) is h when the sensor S2 nodes cycle2Sampled signal trigger when, employing mode D is operated；
(5) is when controller C2 nodes are by feedback signal y2bWhen () triggers s, employing mode E is operated；
(6) works as actuator A2 node controlled signals u2When () triggers s, employing mode F is operated；
The step of mode A, includes：
A1：Sensor S1 nodes work in time type of drive, and its trigger signal is cycle h1Sampled signal；
A2：After sensor S1 nodes are triggered, to controlled device G11The output signal y of (s)11(s) and controlled device cross aisle
Transmission function G12The output signal y of (s)12(s), and actuator A1 nodes output signal y11mbS () is sampled, and calculate
Go out the system output signal y of close loop control circuit 11(s) and feedback signal y1b(s), and y1(s)=y11(s)+y12(s) and y1b
(s)=y1(s)-y11mb(s)；
A3：By feedback signal y1b(s), by the feedback network path of close loop control circuit 1 to controller C1 node-node transmissions, feedback
Signal y1bS () will experience network transfer delay τ2Afterwards, controller C1 nodes are got to；
The step of mode B, includes：
B1：Controller C1 nodes work in event driven manner, by feedback signal y1bS () is triggered；
B2：In controller C1 nodes, by the system Setting signal x of close loop control circuit 11S (), subtracts feedback signal y1b(s)
With controlled device prediction model G11mThe output valve y of (s)11maS (), obtains deviation signal e1(s), i.e. e1(s)=x1(s)-y1b
(s)-y11ma(s)；
B3：To e1S () implements control algolithm C1S (), obtains control signal u1(s)；
B4：By control signal u1S feedforward network path that () passes through close loop control circuit 1Unit is passed to actuator A1 nodes
It is defeated, u1S () will experience network transfer delay τ1Afterwards, actuator A1 nodes are got to；
The step of mode C, includes：
C1：Actuator A1 nodes work in event driven manner, controlled signal u1S () is triggered；
C2：In actuator A1 nodes, by control signal u1S () acts on controlled device prediction model G11mS () obtains its output
Value y11mb(s)；The signal u of the actuator A2 nodes of close loop control circuit 2 will be come from2pS () acts on dynamic Feedforward controller D12
S () obtains its output valve ud12(s)；By control signal u1(s) and ud12S () subtracts each other to obtain actuator A1 output signal nodes u1p(s),
That is u1p(s)=u1(s)-ud12(s)；
C3：By signal u1pS () acts on controlled device G11S () obtains its output valve y11(s)；By signal u1pS () acts on controlled
Object cross aisle transmission function G21S () obtains its output valve y21(s)；So as to realize to controlled device G11(s) and G21(s)
Dynamic Feedforward control plus SPC, while realizing to uncertain network-induced delay τ1And τ2Compensation with control；
The step of mode D, includes：
D1：Sensor S2 nodes work in time type of drive, and its trigger signal is cycle h2Sampled signal；
D2：After sensor S2 nodes are triggered, to controlled device G22The output signal y of (s)22(s) and controlled device cross aisle
Transmission function G21The output signal y of (s)21(s), and actuator A2 nodes output signal y22mbS () is sampled, and calculate
Go out the system output signal y of close loop control circuit 22(s) and feedback signal y2b(s), and y2(s)=y22(s)+y21(s) and y2b
(s)=y2(s)-y22mb(s)；
D3：By feedback signal y2b(s), by the feedback network path of close loop control circuit 2 to controller C2 node-node transmissions, feedback
Signal y2bS () will experience network transfer delay τ4Afterwards, controller C2 nodes are got to；
The step of mode E, includes：
E1：Controller C2 nodes work in event driven manner, by feedback signal y2bS () is triggered；
E2：In controller C2 nodes, by the system Setting signal x of close loop control circuit 22S (), subtracts feedback signal y2b(s)
With controlled device prediction model G22mThe output valve y of (s)22maS (), obtains deviation signal e2(s), i.e. e2(s)=x2(s)-y2b
(s)-y22ma(s)；
E3：To e2S () implements control algolithm C2S (), obtains control signal u2(s)；
E4：By control signal u2S feedforward network path that () passes through close loop control circuit 2Unit is passed to actuator A2 nodes
It is defeated, u2S () will experience network transfer delay τ3Afterwards, actuator A2 nodes are got to；
The step of mode F, includes：
F1：Actuator A2 nodes work in event driven manner, controlled signal u2S () is triggered；
F2：In actuator A2 nodes, by control signal u2S () acts on controlled device prediction model G22mS () obtains its output
Value y22mb(s)；The signal u of the actuator A1 nodes of close loop control circuit 1 will be come from1pS () acts on dynamic Feedforward controller D21
S () obtains its output valve ud21(s)；By control signal u2(s) and ud21S () subtracts each other to obtain actuator A2 output signal nodes u2p(s),
That is u2p(s)=u2(s)-ud21(s)；
F3：By signal u2pS () acts on controlled device G22S () obtains its output valve y22(s)；By signal u2pS () acts on controlled
Object cross aisle transmission function G12S () obtains its output valve y12(s)；So as to realize to controlled device G22(s) and G12(s)
Dynamic Feedforward control plus SPC, while realizing to uncertain network-induced delay τ3And τ4Compensation with control.
2. method according to claim 1, it is characterised in that：From TITO-NCS structures, realize system not comprising control
The predict-compensate model of all-network time delay in loop 1 and control loop 2, so as to exempt to network delay between node and node
τ1And τ2, and τ3And τ4Measurement, estimate or recognize, exempt the requirement synchronous to node clock signal.
3. method according to claim 1, it is characterised in that：Realized from TITO-NCS structures, during to uncertain network
Prolong the implementation of compensation method, with specific control strategy C1(s) and C2S the selection of () is unrelated；With the selection of specific network communication protocol
It is unrelated.
4. method according to claim 1, it is characterised in that：Using dynamic Feedforward controller D12S (), can reduce and come from
The interference signal u of close loop control circuit 22pS () passes through cross jamming passage G12The shadow of (s) to the dynamic property of close loop control circuit 1
Ring, while D12S () has uneoupled control effect concurrently；Using dynamic Feedforward controller D21S (), can reduce and be returned from closed-loop control
The interference signal u on road 11pS () passes through cross jamming passage G21The influence of (s) to the dynamic property of close loop control circuit 2, while D21
S () has uneoupled control effect concurrently.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710091044.3A CN106896717A (en) | 2017-02-20 | 2017-02-20 | A kind of two-output impulse generator network control system unpredictable time-delay SPC methods |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710091044.3A CN106896717A (en) | 2017-02-20 | 2017-02-20 | A kind of two-output impulse generator network control system unpredictable time-delay SPC methods |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106896717A true CN106896717A (en) | 2017-06-27 |
Family
ID=59184836
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710091044.3A Pending CN106896717A (en) | 2017-02-20 | 2017-02-20 | A kind of two-output impulse generator network control system unpredictable time-delay SPC methods |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106896717A (en) |
-
2017
- 2017-02-20 CN CN201710091044.3A patent/CN106896717A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106707762A (en) | Hybrid control method for uncertain time delay of two-input and two-output network control system | |
| CN107065572A (en) | A kind of mixed control method of the unknown time delays of two-output impulse generator NDCS | |
| CN106773723A (en) | A kind of two input two exports Delays In Networked Control System compensation SPC and IMC methods | |
| CN106802562A (en) | A kind of two input two exports network decoupling and controlling system long delay compensation method | |
| CN106773725A (en) | A kind of two input two exports the unknown delay compensation of network control system and IMC methods | |
| CN106707761A (en) | Two-input and two-output networked control system unknown time delay IMC method | |
| CN106802559A (en) | A kind of two input two exports Network Delays in Networked Control Systems Based two degrees of freedom IMC methods | |
| CN106773727A (en) | A kind of TITO NCS unpredictable time-delay compensation methodes of two degrees of freedom IMC and SPC | |
| CN106773726A (en) | A kind of two input two exports network decoupling and controlling system random delay compensation method | |
| CN106896717A (en) | A kind of two-output impulse generator network control system unpredictable time-delay SPC methods | |
| CN106919047A (en) | A kind of two-output impulse generator Delays In Networked Control System two degrees of freedom IMC methods | |
| CN106802555A (en) | A kind of two-output impulse generator Delays In Networked Control System compensation method | |
| CN106842930A (en) | A kind of unknown time delay SPC methods of two-output impulse generator network control system | |
| CN106842945A (en) | A kind of IMC methods of two-output impulse generator network control system random delay | |
| CN106773731A (en) | A kind of dual input exports the unknown time delay mixed control method of network decoupling and controlling system | |
| CN106842943A (en) | Two inputs two based on SPC export network decoupling and controlling system delay compensation method | |
| CN106814618A (en) | A kind of two input two exports the IMC methods of the big network delay of network decoupling and controlling system | |
| CN106814621A (en) | A kind of two input two exports network decoupling and controlling system random network time delay IMC methods | |
| CN106802560A (en) | A kind of two input two exports SPC the and IMC methods of network control system random delay | |
| CN106802556A (en) | A kind of IMC methods of two input and output network decoupling and controlling system unknown network time delay | |
| CN107065529A (en) | The unknown time delay two degrees of freedom IMC methods of two-output impulse generator network decoupling and controlling system | |
| CN106814614A (en) | A kind of two input two exports network control system time-vary delay system compensation method | |
| CN106773724A (en) | A kind of two input two exports Delays In Networked Control System compensation and IMC methods | |
| CN106814611A (en) | A kind of TITO NCS uncertain network-induced delay compensation methodes of two degrees of freedom IMC and SPC | |
| CN107065574A (en) | A kind of two-output impulse generator NDCS unpredictable time-delays SPC methods |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170627 |
|
| RJ01 | Rejection of invention patent application after publication |