CN110531615A - A kind of underwater robot roll angle control method - Google Patents
A kind of underwater robot roll angle control method Download PDFInfo
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- CN110531615A CN110531615A CN201910885327.4A CN201910885327A CN110531615A CN 110531615 A CN110531615 A CN 110531615A CN 201910885327 A CN201910885327 A CN 201910885327A CN 110531615 A CN110531615 A CN 110531615A
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- 238000000034 method Methods 0.000 title claims abstract description 48
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- 238000007781 pre-processing Methods 0.000 claims abstract description 5
- 230000004044 response Effects 0.000 claims description 20
- 230000008859 change Effects 0.000 claims description 10
- 230000005484 gravity Effects 0.000 claims description 8
- 238000012545 processing Methods 0.000 claims description 6
- 238000005070 sampling Methods 0.000 claims description 6
- 238000001914 filtration Methods 0.000 claims description 5
- 230000005540 biological transmission Effects 0.000 claims description 4
- 238000009825 accumulation Methods 0.000 claims description 3
- 230000009514 concussion Effects 0.000 claims description 3
- 238000005457 optimization Methods 0.000 claims description 3
- 238000011160 research Methods 0.000 abstract description 4
- 238000012360 testing method Methods 0.000 abstract description 3
- 238000010586 diagram Methods 0.000 description 8
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- 238000007405 data analysis Methods 0.000 description 1
- 230000009699 differential effect Effects 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 230000005764 inhibitory process Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 230000010355 oscillation Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 238000005096 rolling process Methods 0.000 description 1
- 239000013535 sea water Substances 0.000 description 1
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- 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
- G05B11/00—Automatic controllers
- G05B11/01—Automatic controllers electric
- G05B11/36—Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential
- G05B11/42—Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential for obtaining a characteristic which is both proportional and time-dependent, e.g. P. I., P. I. D.
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Abstract
The invention discloses a kind of underwater robot roll angle control method, include the following steps: that (1) inputs preprocessing process；(2) fuzzy logic controller treatment process；(3) PID controller treatment process is exported to executing agency.The present invention is with the artificial research object of underwater, by testing and emulating, PID control is combined with fuzzy control, the method for having obtained fuzzy self-turning PID control underwater robot roll angle, to improve the control precision and stability in roll angle.
Description
Technical field
The present invention relates to underwater control technical field, especially a kind of underwater robot roll angle control method.
Background technique
It carries out mainly influencing to have existing for accurate control when moving underwater robot in water: mechanical during task
The various movements that hand carries out may cause whole center of gravity and centre of buoyancy offset to influence machine body movement；It can during task
The article that can be carried out is collected or release is so that machine entirety gravity and buoyancy generate variation to influence machine movement；Underwater
People under water in motion process caused ambient water and underwater existing water flow itself interference；Hydrodynamic force coefficient not really
It is qualitative；The non-linear and time variation of underwater robot movement.
The control method of underwater robot mainly includes PID control, fuzzy control, Self tuning control etc..PID control conduct
The advantages of one traditional control method is simple, clear, reliable and stable actual parameter, but it the shortcomings that be that must be set up one
More accurate mathematical model.And for the posture position control system of underwater robot, due to its vulnerable to peripheral environment such as
The influence of the variations such as ocean current, density of sea water, whole system are nonlinear time_varying system, and different moments need to select different PID
Parameter using traditional PID controller is difficult that whole service process is made to have preferable operational effect.Fuzzy control does not need
The accurate model of controlled device, but which also limits the sensibility of control system and stability.And it is most of to underwater
The research of people's control is concentrated in positioning, orientation, constant speed and depthkeeping, less to gesture stability especially roll angle control research.
Summary of the invention
Technical problem to be solved by the present invention lies in provide a kind of underwater robot roll angle control method, Neng Gouti
Control precision and stability in high roll angle.
In order to solve the above technical problems, the present invention provides a kind of underwater robot roll angle control method, including walk as follows
It is rapid:
(1) preprocessing process is inputted；
(2) fuzzy logic controller treatment process；
(3) PID controller treatment process is exported to executing agency.
Preferably, in step (1), preprocessing process is inputted specifically:
(11) Kalman filtering is carried out to the collected data of attitude transducer；
(12) timing of setting timer calculates error e and error change ec.
Kalman filtering can smoothly attitude transducer be read, and accurately be estimated in easy changing environment under water underwater
Robot current pose, timer make e consistent with the calculating time interval of ec, facilitate the meter of subsequent discrete type PID controller
It calculates.
Preferably, in step (2), fuzzy logic controller treatment process specifically comprises the following steps:
(21) setting inputs subordinating degree function to input parameter fuzzy according to the actual situation；
(22) fuzzy reasoning is carried out according to the fuzzy rule of optimization；
(23) output subordinating degree function is adjusted according to the actual situation using Ziegler-Nichols algorithm；
(24) de-fuzzy is carried out using gravity model appoach according to the output subordinating degree function in step (23).
Preferably, in step (23), output degree of membership letter is adjusted according to the actual situation using Ziegler-Nichols algorithm
Number specifically: establish underwater robot roll angle kinematics naive model, the transmission function of this model is as follows:
Parameter tuning is carried out using Ziegler-Nichols method, carries out frequency domain using the closed-loop system of only proportional control
Response adjusting, frequency domain response setting empirical formula are as follows:
KP=0.6Km,
When Km is about 15 or so, curve concussion is the most frequent, by Ziegler-Nichols empirical equation three obtained
Parameter is KP=9, KI=0.88, KD=2.25.
Preferably, in step (24), the deblurring method used is gravity model appoach, expression formula are as follows:
In formula: z0For the exact value after fuzzy controller output quantity deblurring；ziFor the value in fuzzy control quantity domain；μc
(z ziBe subordinate to angle value.
Preferably, in step (3), PID controller processing specifically: exported according to fuzzy logic controller in step (2)
Tri- coefficients of PID, history error accumulation, error change and sampling time carry out discrete type PID arithmetic, obtained output quantity warp
Output is to electric machine controller after crossing dead zone processing；The expression formula of discrete type PID are as follows:
In formula: u (k) is that PID controller kth time calculates output quantity；KPFor proportionality coefficient；TIFor integral coefficient；TDFor differential
Coefficient；T is that sampling period e (k) is kth subsystem deviation.
The invention has the benefit that the present invention is with the artificial research object of underwater, by testing and emulating, by PID
Control is combined with fuzzy control, the method for having obtained fuzzy self-turning PID control underwater robot roll angle, to improve rolling
Control precision and stability on angle.
Detailed description of the invention
Fig. 1 is flow diagram of the invention.
Fig. 2 is control structure schematic diagram of the invention.
Fig. 3 is the input subordinating degree function schematic diagram that the present invention uses.
Fig. 4 (a) is K of the present inventionPThe output subordinating degree function schematic diagram used when=9.
Fig. 4 (b) is K of the present inventionIThe output subordinating degree function schematic diagram used when=0.88.
Fig. 4 (c) is K of the present inventionDThe output subordinating degree function schematic diagram used when=2.25.
Fig. 5 is the present invention and traditional PID control algorithm contrast simulation result schematic diagram.
Specific embodiment
As shown in Figure 1, a kind of underwater robot roll angle control method, includes the following steps:
(1) input pretreatment；
(2) fuzzy logic controller treatment process；
(3) PID controller treatment process is exported to executing agency.
In step (1), preprocessing process is inputted specifically:
(11) Kalman filtering is carried out to the collected data of attitude transducer
(12) timing of setting timer calculates error e and error change ec.
Kalman filtering can smoothly attitude transducer be read, and accurately be estimated in easy changing environment under water underwater
Robot current pose, timer make e consistent with the calculating time interval of ec, facilitate the meter of subsequent discrete type PID controller
It calculates.
In step (2), fuzzy logic controller treatment process specifically comprises the following steps:
(21) setting inputs subordinating degree function to input parameter fuzzy according to the actual situation；
Subordinating degree function is inputted as shown in figure 3, emulating the domain range used as [- 1,1], can be carried out according to the actual situation
It is flexible.Error e and error change ec are obscured by this subordinating degree function and turned to P (Positive), Z (Zero), N
(Negative), it and writes down and is respectively subordinate to angle value.
(22) fuzzy reasoning is carried out according to the fuzzy rule of optimization；
The present invention designs fuzzy rule with system features of response according to the specific effect of three parameters of PID controller.
Proportional coefficient KPEffect be to speed up the response speed of system, improve the degree of regulation of system.KPBigger, system is rung
It answers speed faster, therefore too big value cannot be taken, in order to avoid causing ultraharmonic oscillation, or even cause system unstable.It is worth smaller, tune
Whole precision is lower, and response speed is slower, longer so as to cause adjustment time, and the static and dynamic c haracteristics of system are poor.Ratio system
Number fuzzy rule such as following table improves K when response rises (e P)P, accelerate response speed, when response overshoots (e N), drop
Low KP, reduce overshoot.
1 proportionality coefficient fuzzy reasoning table of table
| e\ec | N | Z | P |
| N | N | N | N |
| Z | N | P | P |
| P | P | P | P |
Integral coefficient KIEffect be elimination system steady-state error.KIBigger, integrating rate is faster.But the value cannot take
It is too much, so as not to cause in the initial stage of response process and transient process system integral saturation and, thus in response process
In bring biggish overshoot, deteriorate dynamic property.If this value is too small, integral action can be weaker, can be difficult to remove static miss
Difference can not be rapidly achieved stable state to keep the transient time of system elongated, influence the degree of regulation and dynamic property of system.Product
Divide coefficient fuzzy rule such as following table, integration control is only enabled when error is near expectation, is avoided while reducing static error
Control initial stage history error interference.
2 integral coefficient fuzzy reasoning table of table
| e\ec | N | Z | P |
| N | Z | Z | Z |
| Z | P | P | P |
| P | Z | Z | Z |
Differential coefficient KDEffect is the dynamic property of raising system.It is inclined that the differential element of PID controller can only influence system
The change rate of difference stops change of error so its major function is the change of error of any direction during inhibition response in advance,
Overshoot is reduced, system stability is increased.If the too big response process of this value stops too early, adjustment time is elongated, system rejection to disturbance
It is less able.When response rises (e P), reduce KD, the differential action is reduced, response speed is accelerated, when response overshoots (e N)
When, improve KD, increase damping, reduce overshoot.
3 differential coefficient fuzzy reasoning table of table
| e\ec | N | Z | P |
| N | P | P | P |
| Z | P | Z | P |
| P | N | N | N |
(23) output subordinating degree function is adjusted according to the actual situation using Ziegler-Nichols algorithm；
It is tested using water tank, the kinematic data of underwater robot is acquired by sensor.By dividing experimental data
Analysis and processing, we establish underwater robot roll angle kinematics naive model.The transmission function of this model is as follows:
Parameter tuning is carried out using Ziegler-Nichols method.Due to the transmission function unit-step nsponse curve without
Method use experience tuning formulae, therefore the closed-loop system of only proportional control is used to carry out frequency domain response adjusting.Frequency domain response adjusting
Empirical equation is as follows:
KP=0.6Km,
By testing repeatedly, when Km is about 15 or so, curve concussion is the most frequent.By Ziegler-Nichols experience
Formula three obtained parameter is KP=9, KI=0.88, KD=2.25.With output subordinating degree function such as Fig. 4 of this parameter designing
(a), shown in Fig. 4 (b) and Fig. 4 (c).
(24) de-fuzzy is carried out using gravity model appoach according to the output subordinating degree function in step (23)；
The deblurring method that the present invention uses is gravity model appoach, expression formula are as follows:
In formula: z0For the exact value after fuzzy controller output quantity deblurring；ziFor the value in fuzzy control quantity domain；μc
(z ziBe subordinate to angle value.
In step (3), PID controller processing specifically: the PID tri- exported according to fuzzy logic controller in step (2)
A coefficient, history error accumulation, error change and sampling time carry out discrete type PID arithmetic, and obtained output quantity is by dead zone
Output is to electric machine controller after processing.
The expression formula of discrete type PID are as follows:
In formula: u (k) is that PID controller kth time calculates output quantity；KPFor proportionality coefficient；TIFor integral coefficient；TDFor differential
Coefficient；T is that sampling period e (k) is kth subsystem deviation.
Establish the simulation model of traditional PI D and fuzzy selftuning PID simultaneously in Simulink, structure chart is shown in Fig. 2, emulates
As a result see Fig. 5.Simulation result can intuitively find out traditional PI D and fuzzy selftuning PID robot roll angle control under water very much
Difference in system.Step response diagram is compared, the curve of fuzzy selftuning PID has a smaller overshoot, higher stability and more
Short adjustment time.Therefore, this Fuzzy Self-Tuning PID Controller is even more ideal to the control of underwater robot roll angle.
Claims (6)
1. a kind of underwater robot roll angle control method, which comprises the steps of:
(1) preprocessing process is inputted；
(2) fuzzy logic controller treatment process；
(3) PID controller treatment process is exported to executing agency.
2. underwater robot roll angle control method as described in claim 1, which is characterized in that in step (1), input pre- place
Reason process specifically:
(11) Kalman filtering is carried out to the collected data of attitude transducer；
(12) timing of setting timer calculates error e and error change ec.
3. underwater robot roll angle control method as described in claim 1, which is characterized in that in step (2), fuzzy logic
Controller treatment process specifically comprises the following steps:
(21) setting inputs subordinating degree function to input parameter fuzzy according to the actual situation；
(22) fuzzy reasoning is carried out according to the fuzzy rule of optimization；
(23) output subordinating degree function is adjusted according to the actual situation using Ziegler-Nichols algorithm；
(24) de-fuzzy is carried out using gravity model appoach according to the output subordinating degree function in step (23).
4. underwater robot roll angle control method as claimed in claim 3, which is characterized in that in step (23), use
Ziegler-Nichols algorithm adjusts output subordinating degree function according to the actual situation specifically: establishes underwater robot roll angle
The transmission function of kinematics naive model, this model is as follows:
Parameter tuning is carried out using Ziegler-Nichols method, carries out frequency domain response using the closed-loop system of only proportional control
Adjusting, frequency domain response setting empirical formula are as follows:
When Km is about 15 or so, curve concussion is the most frequent, by Ziegler-Nichols empirical equation three obtained parameter
For KP=9, KI=0.88, KD=2.25.
5. underwater robot roll angle control method as claimed in claim 3, which is characterized in that in step (24), use
Deblurring method is gravity model appoach, expression formula are as follows:
In formula: z0For the exact value after fuzzy controller output quantity deblurring；ziFor the value in fuzzy control quantity domain；μr(z zi
Be subordinate to angle value.
6. underwater robot roll angle control method as described in claim 1, which is characterized in that in step (3), PID control
Device processing specifically: become according to tri- coefficients of PID of fuzzy logic controller output, history error accumulation, error in step (2)
Change and the sampling time carries out discrete type PID arithmetic, obtained output quantity exports after dead zone is handled to electric machine controller；It is discrete
The expression formula of type PID are as follows:
In formula: u (k) is that PID controller kth time calculates output quantity；KPFor proportionality coefficient；TIFor integral coefficient；TDFor differential system
Number；T is that sampling period e (k) is kth subsystem deviation.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113093527A (en) * | 2021-04-07 | 2021-07-09 | 广东工业大学 | Unmanned ship anti-interference system with improved EKF and fuzzy PID double closed-loop control and use method |
| CN113325857A (en) * | 2021-06-08 | 2021-08-31 | 西北工业大学 | Simulated bat ray underwater vehicle depth control method based on centroid and buoyancy system |
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