CN107463097A - The adaptive quantizing fault tolerant control and its method of a kind of underwater robot - Google Patents
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- CN107463097A CN107463097A CN201710890830.XA CN201710890830A CN107463097A CN 107463097 A CN107463097 A CN 107463097A CN 201710890830 A CN201710890830 A CN 201710890830A CN 107463097 A CN107463097 A CN 107463097A
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- 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
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Abstract
The invention discloses the adaptive quantizing fault tolerant control and its method of a kind of underwater robot, including inner ring control module, inner ring control module control compensation and feedback module, and quantization control signal is produced by signal quantization device underwater robot is controlled；Wherein compensation and feedback module include actuator failure adaptive equalization module, nonlinear feedback model and uncertain adaptive equalization module；Wherein inner ring control module is based on underwater robot kinematics model, underwater human occupant dynamic model and it is expected that module produces quantization control signal by signal quantization device.Adaptive failure compensator is devised, the gain faults and perturbation failure of executing agency can be handled；By designing reverse adaptive law, it compensate for control signal and quantify caused control distribution matrix drift.
Description
Technical field
The invention belongs to underwater robot control technology field；It is related to a kind of fault-tolerant control of the adaptive quantizing of underwater robot
Device processed；Further relate to a kind of adaptive quantizing fault tolerant control method of underwater robot.
Background technology
In engineering control system, signal quantization is significant.In digital circuitry, network control system and mix
Close in control system, the control signal of quantization is very common.The quantization of control input signal is generally referred to continuous control signal
Series of discrete control variable is transformed into, the drift of control distribution matrix can be thus introduced in the controls and add not true
Qualitatively occur.On the other hand, underwater robot has important at many aspects such as marine resources utilization, underwater project constructions
Application value, it is the strong instrument for the research and development that the mankind carry out deep-sea resources.And the digitlization of robot under water
In control system, the quantization of control input is inevitable.Therefore, the quantization motion control method of underwater robot is studied,
With important theory and practice meaning.
Due to underwater special complex environment, the failure of AUV Executive Mechanism is difficult to avoid that, studies failure situations
Under faults-tolerant control be also very necessary.On the Fault Tolerance Control Technology of underwater robot, existing more scholar is studied.
Yang etc. have studied the Fault Tolerance Control Technology of rudder oar linkage type underwater robot.The failure that Fang etc. have studied underwater robot is examined
Disconnected technology, including the fault detect of sensor and the Fault Identification of thruster.Yang etc. have studied based on Gaussian integration point
The fault diagnosis and fault-tolerant control method of underwater robot.But above-mentioned document is both for continuous measurement signal and control signal
Studied, do not studied for discontinuous quantization fault-tolerant control system.Based on this, the present invention is directed to input signal amount
Change and actuator failure and the situation deposited, to the uncertainty of control distribution matrix and added uncertain based on adaptive thought
Property compensates, and can ensure that underwater robot tracks desired signal in a fault situation using quantized signal.
The content of the invention
The invention provides a kind of adaptive quantizing fault tolerant control of underwater robot, devises adaptive failure benefit
Device is repaid, the gain faults and perturbation failure of executing agency can be handled.
It is reversely adaptive by designing present invention also offers a kind of adaptive quantizing fault tolerant control method of underwater robot
Ying Lv, it compensate for control signal and quantify caused control distribution matrix drift.
The technical scheme is that：A kind of adaptive quantizing fault tolerant control of underwater robot, including inner ring control
Molding block, inner ring control module control compensation and feedback module, and quantization control signal is produced to water by signal quantization device
Lower robot is controlled；Wherein compensation and feedback module includes actuator failure adaptive equalization module, nonlinear feedback
Module and uncertain adaptive equalization module；Wherein inner ring control module is based on underwater robot kinematics model, underwater machine
Device human occupant dynamic model and expectation module pass through signal quantization device and produce quantization control signal.
The present invention another technical scheme be：A kind of adaptive quantizing fault tolerant control method of underwater robot, including with
Lower step：
Step 1, the kinematics and dynamics of underwater robot are built；
Step 2, underwater robot control input, signal quantization is completed using signal quantization device, establishes its quantitative model；
Step 3, AUV Executive Mechanism fault model is established；
Step 4, the adaptive quantizing Controlling model of underwater robot is established.
Further, the features of the present invention also resides in：
Quantitative model can be decomposed into a linear segment wherein in step 2 and one non-linear is not sealed.
Wherein the failure of executing agency includes in step 3：Executing agency output failure, executing agency shift fault and hold
The yardstick of row mechanism gain faults.
Wherein the type of the failure of executing agency includes in step 3：Fault-free type, partial fault type and total failure class
Type.
Also include design inner ring virtual controlling rule wherein in step 4.
Also include approaching inner ring tracking error by fuzzy logic wherein in step 4.
Compared with prior art, the beneficial effects of the invention are as follows：Kinematics power of the inventive method from underwater robot
Learn angle to set out, in the case of executing agency has failure, quantization control signal can be used to realize the fortune of underwater robot
Dynamic control；The present invention can also overcome the influence of time-varying external interference, possess stronger robustness and adaptivity.Institute of the present invention
The control method carried can realize faults-tolerant control, possess non-fragility；Gain is controlled to be changed according to external disturbance and failure situations
And change, there is non-conservation.In addition, controller architecture is simple, the computational load of computer can be mitigated, there is higher reality
With value.
Brief description of the drawings
Fig. 1 is the control structure schematic diagram of the present invention；
Fig. 2 is the loss in efficiency and shift fault schematic diagram of AUV Executive Mechanism in the present invention.
In figure：1 is expectation module；2 be inner ring control module；3 be actuator failure adaptive equalization module；4 be non-
Linear feedback module；5 be underwater robot kinematics model；6 be underwater human occupant dynamic model；7 be uncertain adaptive
Answer compensating module；8 be executing agency's nonlinear model；9 be signal quantization device.
Embodiment
Technical scheme is further illustrated with specific embodiment below in conjunction with the accompanying drawings.
The invention provides a kind of adaptive quantizing fault tolerant control of underwater robot, as shown in figure 1, including inner ring
Control module 2, inner ring control module 2 and actuator failure adaptive equalization module 3, nonlinear feedback model 4 and uncertain
Property the composition of adaptive equalization module 7 compensation connect with feedback module, and inner ring control module 2 passes through and compensated and feedback module
The fault message of the underwater robot of offer, signal quantization device 8 is set to produce quantization control signal；Build the non-of executing agency simultaneously
Linear model 8, and again on the basis of build underwater robot kinetic model 6 and underwater robot kinematics model 5,
And the phase caused by the kinematics model 5 and expectation module 1 of kinetic model 6, underwater robot based on underwater robot
Hope signal co- controlling inner ring control module 2.
Present invention also offers a kind of adaptive quantizing fault tolerant control method of underwater robot, comprise the following steps：
Step 1, the kinematics and dynamics of underwater robot are built；The wherein kinematics kinetic simulation of underwater robot
Type is：
Wherein M is inertial matrix, and C (v) is coriolis force and centripetal force matrix, and D (v) is hydrodynamic force matrix, and g (η) is recovery
Power and torque vector, N is executing agency's number, τdFor external disturbance power and torque, J (η) is transition matrix, and η represents underwater machine
The position of device people and attitude vectors,Represent the velocity vector of underwater robot.Represent the execution of underwater robot
The control output vector of mechanism, u=[u1,u2,…,un]T, Q (u)=[Q1(u1),Q2(u2),…,Qn(un)]T, wherein Qi(ui)
ForQuantized value, F [Q (u)] represent failure situations under quantized signal.
Step 2, underwater robot control input, signal quantization is completed using signal quantization device, establishes its quantitative model；Tool
The underwater robot control input of body completes signal quantization using signal quantization device, and its model can be expressed as：
WhereinJ=1,2 ..., ui,min＞ 0 represents q (ui) the ＜ ρ of deadzone parameter 0i＜ 1, δi=(1-
ρi)/(1+ρi), constant ρi∈ (0,1) is estimating for quantization resolution, that is to say, that ρiSmaller, quantizer is more coarse.Normal conditions
Under, Qi(ui) it is broken down into a linear segment and a non-linear partial：
Qi(ui)=ui+Δi (3)
Wherein
Step 3, AUV Executive Mechanism fault model is established；As shown in Fig. 2 under water in complex environment, intelligence
The executing agency of robot breaks down unavoidably, and the control efficiency of control surface deflection becomes with the change of jet density and flow velocity
Change, the different of water stream characteristics also usually trigger hydrodynamic(al) rudder offset-type failure occur.Analyzed based on more than, and consider underwater robot
The quantizing process of control input signal, actuator failure can be modeled as follows：
Fi[Qi(ui)]=hi(t)Qi(ui)+di,u(t)=hi(t)ui+hi(t)Δi+di,u(t) (4)
Wherein Fi[Qi(ui)] be executing agency output,Represent the shift fault of executing agency, hi(t) table
Show the yardstick of executing agency's gain faults, the value between [0,1].The failure of three types can be by hi(t) it is expressed as：
hi(t)=1：Executing agency is worked with total efficiency.
0 ＜ hi(t) ＜ 1, its efficiency of executing agency's partial loss.For example, hi(t) executing agency=0.8 is characterized to have lost
20% efficiency.hi(t)=0, executing agency is in stuck state, and the output of executing agency is no longer influenceed by inputting.
Step 4, the adaptive quantizing Controlling model of underwater robot is established；Assuming that desired signal is ηd, definition tracking mistake
Difference is eη=η-ηd, the dynamical equation of tracking error can be obtained by, which deriving, is：
Design outer shroud virtual controlling, which is restrained, is：
Wherein k1＞ 0 is design parameter.Further, it is e to define inner ring tracking errorv=v-vvirtual, then the inner ring
The dynamical equation of tracking error is represented by：
SelectionTo V0Carrying out derivation can obtain：
Due to and C (v), g (η) and hydrodynamic force matrix D (v) also assume that to be unknown, present invention introduces fuzzy logic to it
Approached.Ideally：
- C (v) v-D (v) v=θT(t)φ(v)+εφ (10)
Wherein,For matrix of unknown parameters, NlFor the number of fuzzy logic,For fuzzy close
Function, its component can be expressed as：
L=1,2 ..., Nl。For fuzzy approximation error, meetDefinitionSimply
It can be calculated：
Wherein κ=0.2785,For design constant,Further obtain：
Notice
Wherein τd,i(t) meetFurther derive and understand：
Define d=supt≥0||ui,min+di,u(t)+τd,i(t) | |, then
It is further known that：
Wherein εd＞ 0 is design parameter,Then：
Then understand：
Design virtual controlling, which is restrained, is：
WhereinForEstimate, definitionContinuing derivation can obtain：
For the control efficiency drift for overcoming signal well to bring, analyzed as follows：
Define Hi=1/inft≥0||hi| |,For its estimate,Designing actual control law is：
Then：
Then：
Further shift onto to obtain：
Select final Lyapunov functions for：
Understand：
Understand selection adaptive law for：
The adaptive law can restrain control system, whereinσd,σHFor normal number.
Claims (7)
- A kind of 1. adaptive quantizing fault tolerant control of underwater robot, it is characterised in that including inner ring control module (2), Inner ring control module (2) control compensation and feedback module, and quantization control signal is produced to underwater by signal quantization device (8) Robot is controlled；The compensation and feedback module include actuator failure adaptive equalization module (3), nonlinear feedback model (4) and not Certainty adaptive equalization module (7)；The inner ring control module (1) be based on underwater robot kinematics model (5), underwater human occupant dynamic model (6) and It is expected that module (1) produces quantization control signal by signal quantization device (8).
- 2. the adaptive quantizing fault tolerant control method of a kind of underwater robot, it is characterised in that comprise the following steps：Step 1, the kinematics and dynamics for building underwater robot are：Wherein M is inertial matrix, and C (v) is coriolis force and centripetal force Matrix, D (v) are hydrodynamic force matrix, and g (η) is restoring force and torque vector, and N is executing agency's number, τdFor external disturbance power and Torque, J (η) are transition matrix, and η represents position and the attitude vectors of underwater robot,Represent the speed of underwater robot Vector,Represent the control output vector of the executing agency of underwater robot, u=[u1,u2,…,un]T；Q (u)=[Q1 (u1),Q2(u2),…,Qn(un)]T, wherein Qi(ui) beQuantized value；F [Q (u)] represents the quantization letter under failure situations Number；Step 2, underwater robot control input, signal quantization is completed using signal quantization device (8), establishes its quantitative model；Step 3, AUV Executive Mechanism fault model is established；Step 4, the adaptive quantizing Controlling model of underwater robot is established.
- 3. the adaptive quantizing fault tolerant control method of underwater robot according to claim 2, it is characterised in that the step Quantitative model is expressed as in rapid 2：<mrow> <msub> <mi>Q</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <msub> <mi>u</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mi>sgn</mi> <mrow> <mo>(</mo> <msub> <mi>u</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>,</mo> </mrow> </mtd> <mtd> <mrow> <mfrac> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mrow> <mn>1</mn> <mo>+</mo> <msub> <mi>&delta;</mi> <mi>i</mi> </msub> </mrow> </mfrac> <mo><</mo> <mrow> <mo>|</mo> <msub> <mi>u</mi> <mi>i</mi> </msub> <mo>|</mo> </mrow> <mo>&le;</mo> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mo>,</mo> <msub> <mover> <mi>u</mi> <mo>&CenterDot;</mo> </mover> <mi>i</mi> </msub> <mo><</mo> <mn>0</mn> <mo>,</mo> <mi>o</mi> <mi>r</mi> <mi> </mi> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mo><</mo> <mrow> <mo>|</mo> <msub> <mi>u</mi> <mi>i</mi> </msub> <mo>|</mo> </mrow> <mo>&le;</mo> <mfrac> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mrow> <mn>1</mn> <mo>-</mo> <msub> <mi>&delta;</mi> <mi>i</mi> </msub> </mrow> </mfrac> <mo>,</mo> <msub> <mover> <mi>u</mi> <mo>&CenterDot;</mo> </mover> <mi>i</mi> </msub> <mo>></mo> <mn>0</mn> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>+</mo> <msub> <mi>&delta;</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mi>sgn</mi> <mrow> <mo>(</mo> <msub> <mi>u</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>,</mo> </mrow> </mtd> <mtd> <mrow> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mo><</mo> <mrow> <mo>|</mo> <msub> <mi>u</mi> <mi>i</mi> </msub> <mo>|</mo> </mrow> <mo>&le;</mo> <mfrac> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mrow> <mn>1</mn> <mo>-</mo> <msub> <mi>&delta;</mi> <mi>i</mi> </msub> </mrow> </mfrac> <mo>,</mo> <msub> <mover> <mi>u</mi> <mo>&CenterDot;</mo> </mover> <mi>i</mi> </msub> <mo><</mo> <mn>0</mn> <mo>,</mo> <mi>o</mi> <mi>r</mi> <mfrac> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mrow> <mn>1</mn> <mo>-</mo> <msub> <mi>&delta;</mi> <mi>i</mi> </msub> </mrow> </mfrac> <mo><</mo> <mrow> <mo>|</mo> <msub> <mi>u</mi> <mi>i</mi> </msub> <mo>|</mo> </mrow> <mo>&le;</mo> <mfrac> <mrow> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>+</mo> <msub> <mi>&delta;</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> </mrow> <mrow> <mn>1</mn> <mo>-</mo> <msub> <mi>&delta;</mi> <mi>i</mi> </msub> </mrow> </mfrac> <mo>,</mo> <msub> <mover> <mi>u</mi> <mo>&CenterDot;</mo> </mover> <mi>i</mi> </msub> <mo>></mo> <mn>0</mn> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mn>0</mn> <mo>,</mo> </mrow> </mtd> <mtd> <mrow> <mn>0</mn> <mo>&le;</mo> <mrow> <mo>|</mo> <msub> <mi>u</mi> <mi>i</mi> </msub> <mo>|</mo> </mrow> <mo><</mo> <mfrac> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>min</mi> </mrow> </msub> <mrow> <mn>1</mn> <mo>+</mo> <msub> <mi>&delta;</mi> <mi>i</mi> </msub> </mrow> </mfrac> <mo>,</mo> <msub> <mover> <mi>u</mi> <mo>&CenterDot;</mo> </mover> <mi>i</mi> </msub> <mo><</mo> <mn>0</mn> <mo>,</mo> <mi>o</mi> <mi>r</mi> <mfrac> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>min</mi> </mrow> </msub> <mrow> <mn>1</mn> <mo>+</mo> <msub> <mi>&delta;</mi> <mi>i</mi> </msub> </mrow> </mfrac> <mo>&le;</mo> <mrow> <mo>|</mo> <msub> <mi>u</mi> <mi>i</mi> </msub> <mo>|</mo> </mrow> <mo><</mo> <msub> <mi>u</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>min</mi> </mrow> </msub> <mo>,</mo> <msub> <mover> <mi>u</mi> <mo>&CenterDot;</mo> </mover> <mi>i</mi> </msub> <mo>></mo> <mn>0</mn> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>q</mi> <mrow> <mo>(</mo> <msub> <mi>u</mi> <mi>i</mi> </msub> <mo>(</mo> <msup> <mi>t</mi> <mo>-</mo> </msup> <mo>)</mo> <mo>)</mo> </mrow> <mo>,</mo> </mrow> </mtd> <mtd> <mrow> <msub> <mover> <mi>u</mi> <mo>&CenterDot;</mo> </mover> <mi>i</mi> </msub> <mo>=</mo> <mn>0</mn> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>,</mo> </mrow>WhereinRepresent q (ui) the ＜ ρ of deadzone parameter 0i＜ 1, δi=(1- ρi)/(1 +ρi)；Constant ρi∈ (0,1) is estimating for quantization resolution, that is to say, that ρiSmaller, quantizer is more coarse；And Qi(ui) can divide Solve and non-linear do not sealed for a linear segment and one.
- 4. the adaptive quantizing fault tolerant control method of underwater robot according to claim 2, it is characterised in that the step The failure of executing agency includes in rapid 3：Executing agency's output failure, the shift fault and executing agency's gain faults of executing agency Yardstick.
- 5. the adaptive quantizing fault tolerant control method of the underwater robot according to any one of claim 2 or 4, its feature It is, the type of the failure of executing agency includes in the step 3：Fault-free type, partial fault type and total failure type.
- 6. the adaptive quantizing fault tolerant control method of underwater robot according to claim 2, it is characterised in that the step Also include design inner ring virtual controlling rule in rapid 4.
- 7. the adaptive quantizing fault tolerant control method of the underwater robot according to any one of claim 2 or 6, its feature It is, also includes approaching inner ring tracking error by fuzzy logic in the step 4.
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| CN112327622A (en) * | 2020-11-02 | 2021-02-05 | 西北工业大学 | Consistency fault-tolerant control method for neutral buoyancy robot |
| CN115357037A (en) * | 2022-09-14 | 2022-11-18 | 中国科学院声学研究所 | Self-adaptive quantitative control method and system for underwater vehicle |
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