JP2016016712A - Automatic steering device for ship - Google Patents

Abstract

PROBLEM TO BE SOLVED: To identify a parameter in a ship which does not comprise a log speed meter.SOLUTION: An automatic steering device comprises an identification calculation part 12 for identifying a ship body parameter. The identification calculation part 12 comprises: an identification model 123 for outputting model output data from predetermined input data which is acquired in the automatic steering device for ship, and including a ship body model having a yaw identification model related to yaw motion of the ship body, and a sway identification model related to a sway motion of the ship body; a parameter adjustment part 125 for adjusting and identifying the ship body parameter, based on a comparison result of the model output data from the identification model 123 and output data being a measurement value related to the ship body; and a speed calculation part 126 for calculating surge speed of the ship body, based on a bow azimuth, ground speed, and ground azimuth detected for the ship body. The input data is the surge speed calculated by the speed calculation part 126, bow azimuth detected for the ship body, and a command steering angle outputted by the automatic steering device for ship.SELECTED DRAWING: Figure 2

Description

  The present invention relates to a marine vessel automatic steering apparatus that identifies identification parameters in an identification model.

  The automatic steering device for a ship is a device that controls the rudder so that the direction from the gyrocompass follows the set course, and the control system obtains the deviation and the turning angular velocity from the input of the set course and the heading, The control gain is multiplied to output a command steering angle, which is a control amount, to the steering machine. The steering machine moves the rudder, induces a turning angular velocity in the hull, and changes the direction. More specifically, the command steering angle is calculated by adding the output of the feedback controller that multiplies the deviation by the control gain and the output of the feedforward controller. The identified hull parameters are input to the trajectory calculation unit, the feedback controller, and the feedforward controller that calculate the reference direction based on the trajectory plan from the set course, and the hull parameters are input to the trajectory calculation unit, the feedback controller, and the feedforward. Used for each calculation and control in the controller.

  The hull parameter is a parameter constituting a hull model of a hull that is controlled by the marine vessel automatic steering apparatus. Since this hull parameter is unknown in most cases, it is obtained by parameter identification. For example, a ship such as a cargo ship or a tanker changes the draft of the hull due to the loading and unloading of luggage and changes the hull characteristics. Therefore, when a control gain based on a hull parameter in a state where a load is loaded on a hull loaded with a load is used, the closed loop stability of the steering system may be lowered and a yawing phenomenon may occur. In order to avoid such a situation, the marine vessel automatic steering apparatus identifies the hull parameters. That is, the marine vessel automatic steering apparatus improves the controllability of the hull by appropriately identifying the hull parameters.

  Further, when the ship model includes a sway identification model related to the ship movement, in addition to the yard identification model related to the ship movement, the ship identification speed requires the hull speed to identify the parameters. To do.

  In addition, as a technique related to parameter identification, input data (command rudder angle) and output data (heading orientation) are accumulated in the output of the command rudder angle based on the reference direction and the heading direction using the hull parameters. There is known a marine vessel automatic steering apparatus that outputs model output data from input data and adjusts hull parameters based on a comparison result between the model output data and the output data (see Patent Document 1).

  Further, in the adjustment of the hull parameters based on the comparison result between the model output data and the output data, the hull parameters are adjusted on the basis of the plurality of input data and the plurality of output data at the time of the change for each change of course. There is known an automatic steering device for a ship that sorts and stores the hull parameters adjusted according to the direction of change of the course, and outputs the identification value of the stored hull parameters corresponding to the direction of change when the set course changes. (See Patent Document 2).

JP 2006-321455 A JP 2008-137545 A

  However, compass and GNSS sensors are standard equipment among the navigation sensors required for the route control system in medium-sized or small-sized ships, but it is necessary to process the bottom of the log speedometer for installation. Because there is a cost that does not match the size of the hull to equip it, it is not necessarily equipped. That is, there is a problem that parameter identification cannot be performed on a ship not equipped with a log speedometer.

  Embodiments of the present invention have been made to solve the above-described problems, and an object of the present invention is to provide a marine vessel automatic steering apparatus that can perform parameter identification in a ship not equipped with a log speedometer. .

  In order to solve the above-described problem, the marine vessel automatic steering apparatus according to the present embodiment is a marine vessel automatic steering apparatus that outputs a command rudder angle using a hull parameter based on a reference azimuth and a bow azimuth. An identification calculation unit for identifying a parameter, wherein the identification calculation unit outputs model output data from predetermined input data obtained by the marine vessel automatic steering apparatus, a yaw identification model relating to yaw motion of a hull, and a sway of the hull An identification model including a hull model having a sway identification model relating to motion is identified by adjusting the hull parameters from a comparison result of model output data from the identification model and output data which is an actual measurement value of the hull. Based on the parameter adjustment unit and the heading, ground speed, and local position detected for the hull, A speed calculation unit for calculating a degree, and the input data is a surge speed of the hull calculated by the speed calculation unit, the heading, and a command steering angle output by the marine vessel automatic steering device. It is characterized by.

  According to the embodiment of the present invention, parameter identification can be performed in a ship not equipped with a log speedometer.

1 is a block diagram illustrating a system including an automatic marine steering apparatus according to an embodiment. It is a block diagram which shows the structure of an identification calculating part. It is explanatory drawing which shows the coordinate system used with a route control system. It is the schematic which shows the control method of the changing course in an automatic ship maneuvering. It is a graph which shows the time change of a reference direction and a reference rudder angle. It is a figure which shows the route before and behind a course change. It is a flowchart which shows operation | movement of a speed calculation process. It is a graph which shows the time series data of a needle-change response in case a tidal current component is zero. It is a graph which shows the relationship between the delay time with respect to a detection direction with respect to a local position, and its evaluation amount. It is a block diagram which shows the structure of a yaw identification model and a sway identification model. It is a block diagram which shows the structure of an azimuth | direction control loop and a route control loop. It is a plot figure which shows the root locus of a route control closed loop. It is the schematic explaining a yaw identification and a sway identification. It is a figure which shows a stable ship and an unstable ship. It is a flowchart which shows operation | movement of an identification process.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

1.1 Configuration of Ship Automatic Steering Device First, a system including the boat automatic steering device of the present invention will be described. FIG. 1 is a block diagram illustrating a system including the marine vessel automatic steering apparatus according to the embodiment.

  As shown in FIG. 1, the system in the present embodiment includes a marine vessel automatic steering apparatus 1 and a hull plant 2 that is a control target thereof. Here, the hull plant 2 is a combination of a steering machine 21, a hull 22, and sensors 23. The marine vessel automatic steering apparatus 1 includes a trajectory calculation unit 11, an identification calculation unit 12, a subtractor 13, a feedback controller 14, a feedforward controller 15, and an adder 16.

Trajectory calculation unit 11 inputs the preset course [psi _S, is intended for calculating the reference azimuth [psi _R based on the trajectory plan from preset course [psi _S. The identification calculation unit 12 identifies the hull parameters and outputs the identified hull parameters to the trajectory calculation unit 11, the feedback controller 14, and the feedforward controller 15. The subtracter 13 outputs the difference e between heading [psi reference azimuth [psi _R and hull 22 that is output from the track calculation unit 11. The feedback controller 14 multiplies the deviation e output from the subtractor 13 by the control gain and outputs a feedback steering angle δ _FB . Feedforward controller 15 outputs the feed-forward steering angle [delta] _FF based on the reference orientation [psi _R output by the trajectory calculation unit 11. The adder 16 adds the feedback steering angle δ _FB output by the feedback controller 14 and the feedforward steering angle δ _FF output by the feedforward controller 15, and gives a command steering angle to the steering machine 21. δ _C is output.

The sensors 23 of the hull plant 2 include a gyro compass 231 that detects the heading ψ of the hull 22 and a GNSS sensor 232 that detects a hull position (x, y) from a satellite positioning system (GNSS) such as GPS. . In addition to the hull position (x, y), the GNSS sensor 232 outputs the ground speed U _g and the local position ψ _g of the hull 22. It is assumed that the heading azimuth ψ, the hull position (x, y), the ground speed U _g and the local position ψ _g detected by the sensors 23 are input to the identification calculation unit 12. Here, the hull position (x, y) is a hull position in a local horizontal coordinate system to be described later.

  Next, the configuration of the identification calculation unit will be described. FIG. 2 is a block diagram illustrating a configuration of the identification calculation unit.

As shown in FIG. 2, the identification calculation unit 12 includes an output data storage unit 121, an input data storage unit 122, an identification model 123, a subtractor 124, a parameter adjustment unit 125, and a speed calculation unit 126. The output data storage unit 121 accumulates the heading ψ and the hull position (x, y) of the hull 22 as output data in time series. The input data storage unit 122 accumulates the command steering angle δ _C output from the adder 16, the heading ψ output from the sensors 23, the ground speed U _g, and the local position ψ _g as input data in time series. . Note that both the output data storage unit 121 and the input data storage unit 122 can be ring buffer memories. The speed calculation unit 126 inputs the reference azimuth ψ _R output from the trajectory calculation unit 11, the bow azimuth ψ as input data stored in the input data storage unit 122, the ground speed U _g, and the local position ψ _g , Based on these, the surge speed u is calculated. A method for calculating the surge speed u will be described in detail later. The identification model 123 includes a hull model, an initial value, and an offset component. The command rudder angle δ _C as the input data stored in the input data storage unit 122, the heading ψ, and the surge calculated by the speed calculation unit 126. The speed u is input, and the model heading and model hull position are output as model output data. The subtractor 124 calculates an identification error that is a difference between the model output data output from the identification model 123 and the output data stored in the output data storage unit 121. The parameter adjustment unit 125 adjusts parameters constituting the identification model 123 based on the identification error calculated by the subtractor 124. The adjustment of this parameter will be described in detail later.

1.2 Hull Motion Equation Here, the hull motion equation will be described. FIG. 3 is an explanatory diagram showing a coordinate system used in the route control system.

As shown in FIG. 3, the coordinate system used in route control system consists local horizontal coordinate system O-XY and body coordinate system G-X _B Y _B, both of which are right-handed three-axis orthogonal coordinate system. In the coordinate system, the Z-axis is positive in the direction of gravity, and the rotation polarity is positive in the right-hand screw direction. Since the coordinate system uses two dimensions, the X axis and the Y axis, the Z axis is omitted in FIG. Also, local horizontal coordinate system northward the X axis, the Y-axis is taken up eastward, the body coordinate system takes surge direction _{X B} axis, the _{Y B} axis sway direction. Further, in FIG. 3, u is surge velocity, v is sway velocity, r is the turning angular velocity, [psi is _heading, u x, _{v y} is to water velocity, beta oblique domestic angle, _{U c} is tidal velocity, _{u c} load flow velocity, v _c in the X direction indicates the forward flow velocity, [psi _c load flow direction of the Y-direction.

  The linear hull motion equation is based on the hull center of gravity G from the coupled motion of the sway motion and the yaw motion, with the constant speed.

になる。ここでｔは時間、ｖは横流れ速度、ｒは旋回角速度、δは舵角を示し、ξ＝［ｖｒ］＾Ｔ、Ｔは転置行列を示し、

become. Where t is time, v is transverse flow velocity, r is turning angular velocity, δ is rudder angle, ξ = [vr] ^ T, T is transposition matrix,

である。

It is.

Formula (1) consists of 14 derivatives and is difficult to handle because of its large number. Therefore, a response model is derived to aggregate the derivatives. To change equation (1) to a response model, Laplace transform and apply M ^-1 on both sides

を得る。ここでＰ_ｖ２（ｓ）はｓｗａｙの２次系の伝達関数モデル、Ｐ_ｒ２（ｓ）はｙａｗの２次系の伝達関数モデル、添字（・）_２は２次系、ｓはラプラス演算子、Ｉは２×２単位行列を示し、

Get. Here, P _v2 (s) is a transfer function model of the second-order system of sway, P _r2 (s) is a transfer function model of the second-order system of yaw, the subscript (·) ₂ is the second-order system, s is the Laplace operator, I denotes a 2 × 2 unit matrix,

である。ここでｄｅｔは行列式を示し、さらに行列式は次の関係をもつ。

It is. Here, det indicates a determinant, and the determinant has the following relationship.

よってＰ_ｖ２（ｓ），Ｐ_ｒ２（ｓ）を整理するため、

Therefore, to organize P _v2 (s) and P _r2 (s),

を用いて、

Using,

と定める。ここでＫ_ｖ ^＊は横流れゲイン、Ｋ_ｒ ^＊は旋回力ゲイン、Ｔ_１，Ｔ_２，Ｔ_ｖ３ ^＊，Ｔ_ｒ３ ^＊はいずれも時定数を示し、

It is determined. Here, K _v ^* is a lateral flow gain, K _r ^* is a turning force gain, T ₁ , T ₂ , T _v3 ^* , and T _r3 ^* are all time constants,

である。

It is.

Therefore, the number of parameters of the response model is six of K _v ^* , K _r ^* , T ₁ , T ₂ , T _v3 ^* , T _r3 ^* , which is smaller than 14 of the derivative of the equation (1). This is the reason why the response model is used in autopilot. In practical use, handling is easy due to less parameter identification. The response model has a common denominator and a different numerator in equation (6). Also, steering engine models the transfer function of the steering angle and the command steering angle [delta] _c,

に近似する。ここでＴ_Ｅは時定数を示す。このＴ_Ｅは、実用時において、Ｔ_１，Ｔ_２に比べ十分に小さいので省略して、δ_ｃ≒δと扱う。

To approximate. Here, _TE represents a time constant. Since _TE is sufficiently smaller than T ₁ and T ₂ in practical use, it is omitted and treated as δ _c ≈δ.

1.3 Needle-change control Since the signal-change response has a larger signal dynamic range and a larger S / N ratio than the hand-holding response, in this embodiment, parameter identification uses time-series data of the needle-change response in the automatic boat maneuvering. Note that the time-series data may be time-series data of a response to a course change during manual boat maneuvering. Here, a method for controlling the course change in the automatic boat maneuvering will be described. FIG. 4 is a schematic diagram showing a method of controlling the course change in the automatic boat maneuvering. FIG. 5 is a graph showing temporal changes in the reference direction and the reference rudder angle.

As shown in FIG. 4, in the control of the course change in the automatic boat maneuvering, the trajectory calculation unit 11 generates the reference direction ψ _R (s) based on the course change condition described later, and the feedforward controller 15 is the inverse model of the hull model. To generate a feedforward steering angle Δ _FF (s). In addition, by introducing a azimuth initial value that realizes a continuous course changing operation and a steering machine constraint that prevents the steering machine from being saturated, the reference direction is a quaternary time function.

になる。ここでη_ｉは係数を示す。フィードフォワード舵角（参照舵角）は、船体モデルの逆モデルを用いて、

become. Here, η _i represents a coefficient. The feedforward rudder angle (reference rudder angle) is the inverse model of the hull model,

になる。このとき船首方位は

become. At this time, the heading is

になり、参照方位に一致する。

And coincides with the reference orientation.

Referring orientation [psi _R and the reference steering angle [delta] _R is used as a pair in the veering controlled as shown in FIG. In time series of such reference azimuth [psi _R and the reference steering angle [delta] _R, reference azimuth [psi _R is veering conditions (veering amount [Delta] [phi] _0, designated turning angular velocity r _0), the steering motor condition (steering angle set value [delta] _0, the steering It is determined by the speed set value δ ^· ₀ ) and the initial azimuth value C _1a = ψ ^· _R (0), C _2a = ψ ^· _R (0) (see Japanese Patent Application Laid-Open No. 2007-290695). Wherein _{r R} reference angular velocity, subscript _{a, v, d} acceleration respectively, constant speed, the mode of the reduction, T is time, eta denotes a constant.

2.1 Surge Speed Calculation Method Next, the principle for calculating the surge speed will be described. FIG. 6 is a diagram showing the route before and after the course change.

  Ground speed component consists of hull velocity component and tidal velocity component in local horizontal coordinates.

と定める。ここでψ：船首方位、ｕ_ｇ，ｖ_ｇ：それぞれｘ方向、ｙ方向の対地速度、ｕ，ｖ：それぞれｓｕｒｇｅ方向、ｓｗａｙ方向の船体速度、ｕ_ｃ，ｖ_ｃ：それぞれｘ方向、ｙ方向の潮流速度、Ｍ：座標変換行列。また、対地速度はＧＮＳＳセンサ２３２により出力される信号を用いて、

It is determined. Here [psi: _heading, u g, _{v g:} each x-direction, y-direction of the ground speed, u, v: each surge direction, sway direction of the hull _speed, u c, _{v c:} each x direction, the y-direction Tidal velocity, M: Coordinate transformation matrix. The ground speed is calculated using the signal output from the GNSS sensor 232.

として得られる。ここでＵ_ｇ：対地速度（ＳＯＧ：ｓｐｅｅｄ ｏｆ ｇｒｏｕｎｄ）、ψ_ｇ：対地方位（ＣＯＧ：ｃｏｕｒｓｅ ｏｆ ｇｒｏｕｎｄ）。

As obtained. Here, U _g : speed of ground (SOG), ψ _g : course of ground (COG).

  In the equation (12), if the hull speed and tidal current speed are substantially constant before and after the course change, the ground speed will change due to the direction change angle. When changing the track as shown in Fig. 6, the ground speed before and after the change is

になる。ここで添字_１，_２：それぞれ変針の前後。（１５）、（１６）式の差をとると

become. Here, subscripts ₁ and ₂ : before and after the change, respectively. Taking the difference between (15) and (16)

になるので、船体速度は

So the hull speed is

から求まる。潮流速度は上式を、時間的に新しい条件を用いるため、（１６）式に代入すると

Obtained from For the tidal velocity, the above equation is used in a new condition in time.

から求まる。したがって、ｓｕｒｇｅ速度ｕは（１８）式から求まり、ｕを用いることで、船体パラメータ同定が実現できる。

Obtained from Accordingly, the surge speed u is obtained from the equation (18), and hull parameter identification can be realized by using u.

2.2 Speed Calculation Process Next, a speed calculation process will be described as a specific method for calculating the surge speed. Since the sway speed is generated when turning, the position ψ _g with respect to the local position has a delay time t _delay with respect to the heading ψ. For this reason, in the speed calculation process, the delay time is taken into consideration for the time zone of the time series data used for the surge speed calculation. FIG. 7 is a flowchart showing the operation of the speed calculation process. FIG. 8 is a graph showing time-series data of the needle changing response when the tidal component is zero. FIG. 9 is a graph showing the relationship between the delay time of the local position with respect to the detected direction and the evaluation amount. Note that the speed calculation process is performed after a predetermined time from the end of the course change.

As shown in FIG. 7, first, the speed calculation unit 126, based on the reference orientation [psi _R, acquires veering state time _{t change} (step S101). Here veering state time _{t change} indicates a time reference orientation [psi _R is in veering state.

Next, the speed calculation unit 126 calculates the acquisition time _tstore (step S102). Here, the acquisition time t _store indicates a time zone of time series data used for speed calculation processing among time series data accumulated in the output data storage unit 121 and the input data storage unit 122. As shown in FIG. 8, the acquisition time t _store is

とする。ここでｔ_{ｓｔｏｒｅ}：取得時間、ｔ_{ｓｅｔｔｌｅ}：変針前後の静定時間、ｔ_{ｃｈａｎｇｅ}：変針状態時間で変針条件に依存、ｔ_{ｄｅｌａｙ０}：遅れ時間の初期値。標本時間はＧＮＳＳセンサ２３２の出力レートに連動し、本実施の形態においてはデフォルト１秒にする。

And Here, t _store : acquisition time, t _settle : _settling time before and after changing the needle, t _change : changing state time and depending on the changing condition, t _delay0 : initial value of delay time. The sample time is linked to the output rate of the GNSS sensor 232, and is set to a default of 1 second in this embodiment.

After calculating the acquisition time, the speed calculation unit 126 acquires the detected direction ψ ^{か ら} from the output data storage unit 121 as time series data within the acquisition time, and the ground speed U _g and the local position ψ from the input data storage unit 122. _g is acquired (step S103). Then, the speed calculation unit 126 for determining the time allocation of [psi _g, calculates the delay time _{t delay} (step S104). The delay time t _delay is a value that minimizes the evaluation amount J _delay as shown in FIG. Ie

になる。ここで_ｉ：時系列データの指数、ｉ_{ｓｅｔｔｌｅ}＝（２×ｔ_{ｓｅｔｔｌｅ}＋ｔ_{ｃｈａｎｇｅ}）／（出力レート）、出力レート１回／１秒。上式はψ^￣（ｔ_ｉ）を固定して、ψ_ｇ（ｔ_ｉ＋ｔ_{ｄｅｌａｙ}）をｔ_{ｄｅｌａｙ}だけ進ませて、両者を一致させるｔ_{ｄｅｌａｙ}を求める。すなわち１変数に対する最小値探索に相当するので、黄金分割算法を用いる。

become. Where _i : index of time series data, i _settle = (2 × t _settle + t _change ) / (output rate), output rate 1 time / 1 second. Above equation fixed [psi ^¯ a _{(t i),} ψ _g a _(t i _{+ t delay)} by advanced by _{t delay,} obtaining the _{t delay} to match the two. That is, since it corresponds to the minimum value search for one variable, the golden section calculation method is used.

Next, the speed calculation unit 126 sets ψ ^￣ (t _i ), ψ _g (t _i + t _delay ), U _g (t _i ) for each of the settling time before the change and the settling time after the change in the time series data. Each average value of + t _delay ) is calculated (step S105). Specifically, the speed calculation unit 126, before veering, within between respective settling time after veering, the average value of [psi ^¯ within a predetermined time period relative to the t _i, a predetermined time relative to the t i ₊ t _delay The average value of ψ _g and U _g is calculated. By calculating the average value in this way, the disturbance included in each parameter is removed. Next, the speed calculation unit 126 obtains the hull speed from the equation (18) and the tidal speed from the equation (19) based on the calculated six average values (step S106).

3.1 Hull model setting Next, the hull model used for parameter identification will be described. It is extremely difficult to obtain the derivative of equation (1) during navigation in practical use. Although the number of parameters in equation (6) is less than the number of derivatives, it is also difficult to obtain six parameters. Therefore, the hull model uses a response model in which the order is further reduced. In equation (6), the hull model relating to yaw and sway motion that approximates the transfer function in the low frequency range is called Nomoto's primary model (hereinafter referred to as Nomoto model). For each of yaw and sway,

として知られている。ここでＴ_ｒ ^＊＝Ｔ_１+Ｔ_２−Ｔ_ｒ３ ^＊，Ｔ_ｖ ^＊=Ｔ_１+Ｔ_２−Ｔ_ｖ３ ^＊である。上式において分母は１次系に低減し、分子は時定数がなくなる。これはＴ_１＞Ｔ_ｒ３＞Ｔ_２，Ｔ_ｖ３≒０．３Ｔ_ｒ３の条件を用い、Ｔ_ｒ ^＊，Ｔ_ｖ ^＊はＴ_１が支配的になる。また、船首方位は、旋回角速度の積分値であるので、（２４）式より

Known as. Here, T _r ^* = T ₁ + T ₂ −T _r3 ^* and T _v ^* = T ₁ + T ₂ −T _v3 ^* . In the above equation, the denominator is reduced to the primary system, and the numerator has no time constant. This uses the conditions of T ₁ > T _r3 > T ₂ , T _v3 ≈0.3T _r3 , and T ₁ is dominant in T _r ^* and T _v ^* . Also, because the heading is an integral value of the turning angular velocity, from equation (24)

になる。

become.

As described above, in the present embodiment, veering in the automatic steering using the reference azimuth [psi _R feedforward steering angle [delta] _FF. The feed forward rudder angle is

になり、そのとき船首方位は（６）式を用いて、

At that time, the heading is calculated using equation (6).

と近似すると、Ｔ_ｒ３ ^＊による過渡現象を生じる。

And a transient phenomenon due to T _r3 ^* occurs.

This indicates that not be excluded from the large _{T r3} ^* is [delta] _FF in the second time constant of equation (6). On the other hand, since T _v3 ^* is sufficiently smaller than T _r3 ^* , it is omitted. Therefore, the hull model is a yaw identification model and a sway identification model, instead of P _r ^* (s) in equation (24) and P _v ^* (s) in equation (25).

を採用する。

Is adopted.

Here, K _r ≠ K _r ^* , T _v3 ≠ T _v3 ^* , T _r ≠ T _r ^* , K _v ≠ K _v ^* , T _v3 = 0, T _v = T _r . The relationship T _v = T _r is due to the common denominator of the equation (24). _Tv is used for convenience. P _r (s) includes a direct term and does not include P _v (s). The hull model has a model error because it is reduced from a linear secondary system to a primary system. Therefore, the hull parameter or maneuverability index becomes [K _r , T _r , T _r3 , K _v ], which are estimated by the identification method.

Since the yaw model can directly use the heading signal, it can be identified by three parameters. On the other hand, since the sway model cannot directly use the sway speed, it is convenient to set T _v = T _r and it is effective not only for parameter reduction but also for signal processing. The sway speed is about an order of magnitude smaller than the surge speed. Therefore, the smaller the sway parameter, the better the identification accuracy. In addition, the way speed uses the yaw angular speed,

になる。

become.

3.2 Identification Model Setting Next, an identification model including the hull model described above will be described. FIG. 10 is a block diagram illustrating a configuration of a yaw identification model and a sway identification model. In FIG. 10, (a) shows a yaw identification model, and (b) shows a sway identification model. Hereinafter, the yaw identification model will be described first, and then the sway identification model will be described.

As shown in FIG. 10, the identification model 123 includes a hull model, an initial value, and an offset component. The initial value is the initial value of the integrator, and the offset component is the offset component of the state quantity, which serve to match the response of the hull model with the actual response. Specifically, fluctuations in the initial response are captured by setting initial values r ₀ and v ₀ of the hull motion as initial values. As the offset component, a steering angle offset component and a velocity offset component of the local horizontal coordinate system are used. Here, the rudder angle offset component represents the moment that acts on the superstructure of the hull 22 due to the constant wind force, by the rudder angle conversion value,

と設定する。ここで添字（・）_ｏはオフセットを示す。また、局地水平座標系の速度オフセット成分は潮流成分や船体を移動させる成分からなり、

And set. Here, the subscript (•) _o indicates an offset. In addition, the velocity offset component of the local horizontal coordinate system consists of a tidal component and a component that moves the hull,

と設定する。ｙａｗ同定モデルの方位出力は、検出された船首方位と直接に比較できるので、図１０（ａ）に示すように、

And set. Since the bearing output of the yaw identification model can be directly compared with the detected heading, as shown in FIG.

と定める。これより同定するパラメータは、

It is determined. The parameter to identify from this is

になる。

become.

Here, the yaw identification model in the present invention is compared with the conventional yaw identification model. Specifically, when the conventional yaw identification model is used, the cause of the parameter identification value fluctuation during a wave disturbance is shown. The parameter of the conventional yaw identification model is compared with the steering angle offset δ _ro described above,

というように、方位変化に連動する舵角オフセットを加えた形になる。ここで、δ_ｒψは風などに起因するｙａｗまわりモーメントを舵角換算した方位係数を示し、ψ^￣は検出された船首方位、ψ_０は変針前の船首方位である初期方位を示す。このときパラメータは、

In this way, the steering angle offset linked to the direction change is added. Here, δ _rψ represents an azimuth coefficient obtained by converting a yaw moment caused by wind or the like into a rudder angle, ψ ^￣ represents a detected bow direction, and ψ ₀ represents an initial direction which is a bow direction before a change. At this time, the parameter is

になり、（３８）式に比べて１つ多い。δ_ｒψは変針後の舵角オフセット変動による同定誤差を防止するが、波浪外乱成分がδ_ｒψを介して同定値に影響を与える。この同定値への影響について説明する。まず、（３６），（３７）と（４０）式から、

It is one more than the equation (38). Although δ _rψ prevents an identification error due to the steering angle offset variation after the change of needle, the wave disturbance component affects the identification value via _δrψ . The influence on the identification value will be described. First, from equations (36), (37) and (40),

を定める。ここで簡単化のためＴ_ｒ３＝０，δ_ｒｏ＝０，ｒ_０＝０，ψ_０＝０として、上式をラプラス変換して、同定誤差を求めると、

Determine. Here, for simplification, when T _r3 = 0, δ _ro = 0, r ₀ = 0, and ψ ₀ = 0, the above equation is Laplace transformed to obtain an identification error.

を得る。ここで、Ψ^￣（ｓ）＝Ψ_２（ｓ）+Ψ_ｗ（ｓ），Ψ_２（ｓ）は２次船体モデルの方位、Ψ_ｗ（ｓ）は波浪外乱を示す。

Get. Here, ψ ^￣ (s) = ψ ₂ (s) + ψ _w (s), ψ ₂ (s) represents the orientation of the secondary hull model, and ψ _w (s) represents the wave disturbance.

From the above equation, the identification error by the conventional yaw identification model is affected by the wave disturbance. On the other hand, since the yaw identification model in the present invention does not have δ _rψ , the identification error is

になり、波浪外乱から直接影響されない。

And is not directly affected by wave disturbances.

  As described above, the yaw identification model in the present invention ignores the identification error caused by the change in the steering angle offset after the course change, and prioritizes a measure for reducing the fluctuation of the identification value. It is assumed that the steering angle offset change is small if the amount of change in needle is small.

  Next, the sway identification model will be described. This sway identification model does not include an offset that is linked to the direction in the steering angle offset for the same reason as the above yard identification model. The sway speed cannot be detected, and the position component is detected by converting the velocity component of the body coordinate system into the velocity component of the local horizontal coordinate system and integrating it. Therefore, as shown in FIG.

と定める。ここでｘ，ｙはそれぞれｎｏｒｔｈ方向、ｅａｓｔ方向の船体位置を示し、ψ^￣は検出方位を示す。これより同定するパラメータは、

It is determined. Here x, y each represent a north direction, east direction of the hull position, [psi ^¯ denotes the detection direction. The parameter to identify from this is

になる。ここで、検出方位に含まれる波浪外乱が船体位置に与える影響を示す。検出方位を

become. Here, the influence of the wave disturbance included in the detected direction on the hull position is shown. Detect direction

とおく。ここでψ_ｗは波浪外乱を示す。微小の波浪振幅としてａ_ｗ，波浪周波数としてω_ｗ，ψ＝０（簡単化のため）およびψ_ｗ=ａ_ｗｓｉｎω_ｗｔを（４６）式に代入すると、

far. Here, ψ _w indicates a wave disturbance. Substituting ω _w , ψ = 0 (for simplification) and ψ _w = a _w sin ω _w t as the minute wave amplitude as _{w w} , as the wave frequency into the equation (46),

になる。ｖ_ｙを積分すると、

become. Integrating _vy gives

になる。ここでＣは積分定数を示す。上式の係数は、

become. Here, C represents an integral constant. The coefficient of the above formula is

になる。ここでｐｅｒｉｏｄ_ｗは波浪周期を示す。

become. Here, period _w indicates the wave period.

As a numerical _{example, u = 20kn, a w =} 2deg, when the period w = 10sec, coefficient becomes 0.57 _m, when the period w = 20sec, factor becomes 1.14. Therefore, the wave disturbance is smaller than the sway velocity integral value in the equation (51), and its influence can be ignored in practice.

3.3 Identification Value Evaluation Method Next, a method for evaluating the identified parameter will be described. The evaluation method is based on a tracking error and a closed loop characteristic. More specifically, the evaluation method is based on a closed loop composed of a feedback gain calculated based on an identification parameter and a control specification of the marine vessel automatic steering device and a secondary hull model. This is performed based on a comparison between the closed loop characteristic and the closed loop characteristic by the closed loop constituted by the primary hull model.

  First, the following error will be described. The tracking error is the sum of squares of the response errors between the output of the controlled object and the output of the identification model for each of the yaw identification model and the sway identification model.

によって定める。ここでｅは追従誤差量、添字（・）^￣は検出量、ｎはデータ数を示す。また、（５３）式はｙａｗ同定モデルを示し、（５４）式はｓｗａｙ同定モデルを示す。

Determined by. Here, e is the tracking error amount, the suffix (·) ^￣ is the detection amount, and n is the number of data. Moreover, Formula (53) shows a yaw identification model, and Formula (54) shows a sway identification model.

  Next, the closed loop characteristic will be described. Since the model error is positive, the identification parameter cannot be directly compared with the secondary hull parameter in equation (6). Therefore, a feedback gain is obtained from the identification parameter and the control specification, and a closed loop including the secondary hull model is constructed, and the closed loop characteristic is evaluated. Here, the direction control loop and the route control loop will be described. FIG. 11 is a block diagram showing the configuration of the direction control loop and the route control loop. FIG. 12 is a plot diagram showing the root locus of the route control closed loop.

  As shown in FIG. 11A, the azimuth control loop is composed of an azimuth model and feedback control.

になる。ここで添字（・）_ｈは方位制御ループ、Ｋ_ｄは微分ゲイン、Ｋ_ｐは比例ゲインを示す。上式より

become. Here, the subscript (·) _h is an azimuth control loop, K _d is a differential gain, and K _p is a proportional gain. From the above formula

になる。よって、特性多項式Ｄ_ｈ（ｓ）は上式より

become. Therefore, the characteristic polynomial D _h (s) is

になる。ここでζ_ｈは減衰係数、ω_ｈは固有周波数を示す。設計パラメータをＫ_ｐとζ_ｈとし、上式に与えると、

become. Here, ζ _h is an attenuation coefficient, and ω _h is a natural frequency. If the design parameters are K _p and ζ _h and given in the above equation,

が求まり、制御ゲインが確定する。

And the control gain is determined.

When the control gain is applied to the azimuth quadratic model, the closed loop characteristic differs from the specification due to the influence of the model error. The amount of change is used as an evaluation amount of identification error. When P _r (s) in the equation (55) is replaced with P _r2 (s) in the equation (6),

になるから、特性多項式Ｄ_ｈ２（ｓ）は、

_Therefore , the characteristic polynomial D _h2 (s) is

になる。ここで添字（・）_ｈ２は方位２次モデルを利用した場合、ａ_ｈ２は実数、ｓ＝−１／Ｔ_２から派生したものを示す。

become. Here the subscript _{(·) h2} When using the azimuth quadratic _{model, a h2} denotes those derived real, from s = -1 / _{T 2.}

Therefore, the identification parameter is evaluated by comparing the attenuation coefficient ζ _h and natural frequency ω _h of the azimuth model with the attenuation coefficient ζ _h2 and natural frequency ω _h2 of the secondary azimuth model. Closed loop stability affects the variation of ζ _h2 .

  In addition, as shown in FIG. 11B, the route control loop is composed of a sway model and feedback control with an azimuth control loop,

になる。ここで添字（・）_ｔは航路制御ループ、Ｋ_ｔは航路ゲインを示す。（３１）式を用いて、

become. Here, the subscript (•) _t indicates the channel control loop, and K _t indicates the channel gain. Using equation (31),

とし、（６３）式から（６５）式を整理すると、

And organizing from (63) to (65),

になる。よって特性多項式Ｄ_t（ｓ）は、

become. Therefore, the characteristic polynomial D _t (s) is

になる。ここで

become. here

である。

It is.

The first term of the right side of the above equation _{K v <0, K r>} 0 < becomes 0, the second term _T r3> _K v _{/ K} r than (in the case of stable vessels) 0, u> 0 than T _r3 u> 0. From this C _K are the increases in proportion to the u not reach exactly. Therefore zero point

はｕに比例して大きくなり、原点から右方向に遠ざかる。

Increases in proportion to u and moves away from the origin in the right direction.

Next, the channel gain _Ky is obtained. The characteristic polynomial of the specification

に定める。２つのＤ_t（ｓ）において、ｓの係数を比べると

Stipulated in Comparing the coefficients of s for two D _t (s)

になる。上式よりω_ｔに関して解くと３次方程式

become. Solving for ω _t from the above equation, cubic equation

が得られる。上式の３次と０次の係数は負になるので、少なくとも上式の根のひとつは負になる。

Is obtained. Since the third and zeroth order coefficients of the above equation are negative, at least one of the roots of the above equation is negative.

ω _t can be obtained by an algebraic solution when the design parameter ζ _t is given in the above equation. Here, how to select ζ _t will be described with reference to FIG. A quadratic expression obtained by deleting the zero point from the expression (68) is indicated by a dotted line. FIG. 12A shows a state of 0 <K _t <∞, and the characteristics of both are similar in the vicinity of the pole (x symbol). Note that this is the case where K _p = 1.5, ζ _h = 1 / √2, u = 10 kn.

FIG. 12B is an enlarged view of the vicinity of the origin. The root locus attenuation coefficient ζ _t starts from 1 / √2 when there is no zero point and then decreases, and when there is a zero point (third-order equation), it starts from 1 / √2 and further increases and then decreases. Therefore, since the attenuation coefficient ζ _t of the cubic equation becomes 1 / √2 in this process, ζ _t = 1 / √2 is used. The black spot in the figure is the root to be found.

From FIG. 12, there are three conjugate roots where ζ _t = 1 / √2, which corresponds to the case of pole x with K _t = 0, the above case, and the case of the right half plane (unstable root). Ω _{t in} each case is smaller in the above case than in the case of the pole ×, and negative in the case of unstable roots.

Therefore, the minimum positive ω _t is solved from the equation (75), and

が順次求まる。

Are obtained sequentially.

The evaluation amount of the identification error in the route control loop is determined in the same manner as in the direction control loop. In the channel control loop using the control gains K _p , K _d , and K _t using the directional secondary model and the sway secondary model, the closed loop characteristics are compared with the specifications. Applying P _r2 (s) and P _v2 (s) of equation (6) to equations (63) and (64), respectively,

になるから、特性多項式Ｄ_t（ｓ）は、

Therefore, the characteristic polynomial D _t (s) is

になる。ここで添字（・）_ｔ２は方位２次モデルおよびｓｗａｙ２次モデルを利用した場合、ｂ_ｔ２は実数、ｓ＝−１／Ｔ_２から派生したものを示す。よって、同定パラメータは航路モデルのζ_ｔ，ω_ｔと航路２次モデルのζ_ｔ２，ω_ｔ２との比較から評価する。閉ループ安定性はζ_ｔ２の変動に影響する。

become. Here, the subscript (·) _t2 indicates that the azimuth secondary model and the sway secondary model are used, and b _t2 is derived from a real number, s = −1 / T ₂ . Therefore, the identification parameter is evaluated from a comparison between ζ _t and ω _t of the channel model and ζ _t2 and ω _t2 of the channel secondary model. Closed loop stability affects the variation of ζ _t2 .

4.1 Identification Processing Next, parameter identification processing will be described. FIG. 13 is a schematic diagram illustrating yaw identification and sway identification. FIG. 14 is a diagram showing a stable ship and an unstable ship. FIG. 15 is a flowchart showing the operation of the identification process.

As shown in FIG. 13, the parameter adjustment unit 125 performs yaw identification based on the time series data at the time of the needle change response, and performs the swaya identification based on the identification value (T _r ) identified in the yaw identification and the time series data. Do. Here, the parameter adjustment unit 125 refers to the identification value identified by the yaw identification in the sway identification, but otherwise the yaw identification and the sway identification do not interfere with each other. By setting the control gain in the azimuth control and the route control based on the hull parameter identification value identified in this way, an adaptive autopilot that is more practical than the conventional one is realized.

  Here, an identification process for performing yaw identification and sway identification will be described. This identification process is performed in substantially the same procedure for the yaw identification and the sway identification, and the identification value is obtained from a single needle change response. First, the output data storage unit 121 and the input data storage unit 122 store output data and input data, respectively, as time-series data at the time of needle change (S201). Here, the output data are the heading and hull position detected by the sensors 23, the heading is used for yaw identification, and the hull position is used for sway identification. Further, in the yaw identification, the input data is a command rudder angle, and in the sway identification, the input data is a command rudder angle, a heading, and a surge speed calculated by the speed calculation unit 126. After changing the course, calculation conditions and input data are given to the identification model 123, and model output data is output (S202). Here, the model output data is the heading in the yaw identification as shown in FIG. 10 (a), and the hull position in the sway identification as shown in FIG. 10 (b). After the model output data is output, the parameter adjustment unit 125 calculates an evaluation amount of an error (identification error) between the output data calculated by the subtractor 124 and the model output data (S203). A minimum value is calculated (S204), a minimum value is selected from the calculated minimum values (S205), and a parameter having a minimum evaluation value is output as an identification value (S206). The calculation of the evaluation amount, the calculation of the minimum value, and the selection of the minimum value will be described in the section of the identification algorithm described later.

  Thus, the parameter adjustment unit 125 obtains an identification value by causing the output from the yaw identification model to follow the heading direction in the yaw identification, and identifies by making the output from the sway identification model follow the hull position in the sway identification. Find the value. Further, the parameter adjustment unit 125 determines the parameter ranges of the stable ship and the unstable ship shown in FIG. 14 in order to determine whether the hull plant 2 to be controlled by the boat automatic steering apparatus 1 is a stable ship or an unstable ship. The identification error is obtained and the identification errors are compared, and it is determined to which parameter range the smaller identification error belongs. This will also be explained in the section on the identification algorithm.

4.2 Identification Algorithm Next, an algorithm for identifying parameters in the above-described identification process will be described. Since the identification algorithm needs to be calculated from a single needle change response, SQP (Sequential Quadratic Programming) is used to determine the minimum value by reducing the parameter identification to a minimum value problem of a multivariable function. To do. By adopting this SQP, it is possible to adjust parameters using data repeatedly to reduce identification errors, and to provide hull parameter restrictions for stable and unstable ships.

  First, calculation of the evaluation amount will be described. The evaluation amount of the identification error is obtained from the difference between the output of the identification model and the output of the target, the evaluation amount is the sum of squares of the identification error,

になる。ここでＪ_ｒはｙａｗ同定における同定誤差の評価量、Ｊ_ｖはｓｗａｙ同定における同定誤差の評価量、添字（・）^￣は検出量、ｎはデータ数を示す。なお、同定モデルの出力ψ，ｘ，ｙはパラメータの初期値Ｘ_ｒ０，Ｘ_ｖ０から計算する。評価量は誤差の２乗和で定めるので、その特性は最小二乗法に準じる。

become. Here _{J r} evaluation of the identifying error in the yaw identification, _{J v} evaluation of the identifying error in the sway identified subscript (·) ^¯ is detectable amount, n represents indicates the number of data. The output ψ, x, y of the identification model is calculated from the initial values X _r0 , X _v0 of the parameters. Since the evaluation amount is determined by the sum of squares of errors, the characteristics conform to the least square method.

Next, calculation of the minimum value will be described. The above-described evaluation quantities J _r and J _v are multivariable functions having the parameters X _r and X _v as functions. The minimum value (this minimum value indicates the minimum value in step S204) is a value when the deviating coefficient related to the parameter becomes zero. That is,

になる。ここで∂ψ_ｉ／∂Ｘ_ｒ，∂ｘ_ｉ／∂Ｘ_ｖ，∂ｙ_ｉ／∂Ｘ_ｖは勾配ベクトル、０はゼロベクトルを示す。勾配ベクトルがゼロになるパラメータを探索する算法として、上述したＳＱＰ技法を用いる。

become. Here, ∂ψ _i / ∂X _r , ∂x _i / ∂X _v , ∂y _i / ∂X _v are gradient vectors, and 0 is a zero vector. The SQP technique described above is used as an algorithm for searching for a parameter for which the gradient vector becomes zero.

  Next, introduction of the parameter constraint described above will be described. Lagrange's undetermined multiplier method is used to incorporate the hull parameter constraint, initial value, and offset component constraint of the stable ship / unstable ship shown in FIG. 14 into the identification calculation. At this time, the evaluation amount is

となる。ここでΛ_ｒ，Λ_ｖはラグランジェの未定乗数の横ベクトル、Ｂ_ｒ，Ｂ_ｖはパラメータ制約の横ベクトルを示す。パラメータ制約内の同定値はＪ_ｒ，Ｊ_ｖの代わりに上式のＪ_ｒλ，Ｊ_ｖλによって求められる。そのためΛ_r，Λ_vが同定変数として追加される。

It becomes. Here, Λ _r , Λ _v are Lagrange's undetermined multiplier horizontal vectors, and B _r , B _v are parameter constraint horizontal vectors. The identification value within the parameter constraint is obtained by J _rλ and J _vλ in the above formula instead of J _r and J _v . Therefore, Λ _r and Λ _v are added as identification variables.

  Next, selection of the minimum value will be described. The minimum value is calculated by searching for the minimum value of the evaluation amount from the initial value of the parameter. For this reason, the local minimum is a local minimum because the minimum value depends on the initial value and may not necessarily be the minimum value. Therefore, the minimum value of the global minimum is selected from the minimum value of the local minimum relative to the initial value, and the identification value is a parameter that gives the minimum value of the global minimum,

になる。ここでＸ^〜 _ｒはｙａｗ同定の同定値、Ｘ^〜 _ｖはｓｗａｙ同定の同定値、添字（・）_ｉ，（・）_ｊは初期値の指標を示す。

become. Here, X ^to _r are identification values of yaw identification, X ^to _v are identification values of sway identification, and subscripts (·) _i and (·) _j are indices of initial values.

  As described above, the surge speed is calculated based on the detected heading, ground speed, and local position, and the hull parameters of the hull model including the yaw identification model and the sway identification model are calculated based on the surge speed. By identifying, parameter identification can be performed on a ship that cannot be equipped with a log speedometer.

  The embodiments of the present invention are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the scope of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are included in the invention described in the claims and the equivalents thereof.

DESCRIPTION OF SYMBOLS 1 Automatic ship steering device 12 Identification calculation part 122 Input data storage part 123 Identification model 125 Parameter adjustment part 126 Speed calculation part 22 Hull

Claims (5)

An automatic steering device for a ship that outputs a command rudder angle using a hull parameter based on a reference direction and a heading,
An identification calculation unit for identifying the hull parameters;
The identification calculation unit
An identification model including a hull model, which outputs model output data from predetermined input data obtained by the marine vessel automatic steering device, and includes a yaw identification model relating to the yaw motion of the hull and a sway identification model relating to the sway motion of the hull;
A parameter adjustment unit that adjusts and identifies the hull parameters from a comparison result between model output data from the identification model and output data that is actual measurement values related to the hull;
A speed calculation unit for calculating a hull speed of the hull based on the heading, ground speed, and local position detected for the hull;
The marine vessel automatic steering apparatus, wherein the input data includes a surge speed of the hull calculated by the velocity calculating unit, a heading, and a command steering angle output by the marine vessel automatic steering apparatus.   2. The speed calculation unit calculates a surge speed based on a heading, a ground speed, and a local position before and after the course change according to the course change of the hull. Automatic ship steering system. The identification calculation unit
An input data storage unit for storing the heading, the ground speed, and the local position as time series data;
The speed calculation unit includes a timing at which the hull changes the time point, and a timing after the time at which the change is made in the time series data to the local position where the difference between the heading direction at the time of changing the needle and the heading at the time of changing the needle is minimum. Of the time series data accumulated in the input data storage unit before the change, after the change, and after the delay time from before the change, and after the delay time after the change, respectively. 3. The marine vessel automatic steering apparatus according to claim 2, wherein the surge speed is calculated on the basis of a ground speed and a local position.   The speed calculation unit is based on the heading within a predetermined time with the first time point before the change as a reference, and the second time point after the change in the time series data accumulated in the input data storage unit. The heading within a predetermined time, the ground speed within a predetermined time based on the third time after the delay time from the first time, and the fourth time after the delay time from the second time An average value is calculated for each of a ground speed within a predetermined time, a relative position within a predetermined time with respect to the third time point, and a relative position within a predetermined time with the fourth time point as a reference. 4. The marine vessel automatic steering apparatus according to claim 3, wherein the surge speed is calculated on the basis of the speed. The transfer function of the yaw identification model is
_Let s be the Laplace operator, K _r , T _r , T _r3 as the hull parameters to be identified,

Represented by
The transfer function of the sway identification model has s as a Laplace operator, K _v , and T _v as hull parameters to be identified.

The marine vessel automatic steering apparatus according to claim 1, wherein T _v = T _r .

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