Abstract
This paper deals with a motion and force control scheme for underwater robots, each of which is equipped with a manipulator. Several motion and force controllers for this type of underwater robot have been developed. Most of them were designed under the assumption that the control capability of each robot body is the same as that of each manipulator. However, it has been pointed out in the literature that for a real underwater robot, its robot body control is more challenging than its manipulator control, because the robot body has much larger inertia, and many more inaccurate position sensors and actuators than the manipulator. Therefore, even if an advanced control law with good performance is implemented in the vehicle controller of each control system, its original control performance may not be achieved. In this paper, we develop a motion and force controller for the manipulator under the condition that the robot body is independently controlled by a motion controller with poor performance. Its features are (1) to be designed in consideration of the dynamics of the robot body including its actuators (i.e., marine thrusters), (2) to ensure the stability properties in the presence of bounded disturbances, and (3) to include a linear force error filter, which can facilitate the stability analysis in comparison with existing nonlinear force error filters. Furthermore, the theoretical results were supported by those obtained in numerical simulations.







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Acknowledgements
This work was supported by JSPS KAKENHI Grant Number JP21K04503.
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This work was presented in part at the 26th International Symposium on Artificial Life and Robotics (Online, January 21–23, 2021).
Appendices
Appendix 1: Derivation of (24)
Differentiating (3) with respect to time, and then using (5), we have
Applying the relation \(R(\phi _{V})R(\phi _{V})^{\mathrm {T}} =I_{3}\) to (70), then multiplying both its sides by \(1/\Vert n_{C}(t)\Vert\), and then using the fourth equation of (21), we obtain
It should be noted that \(n_{C}(t)\) is a nonzero vector. Substituting the equation
into (71), then using the relations \(R(\phi _{V})^{\mathrm {T}} R(\phi _{V})=I_{3}\) and \(R(\phi _{V})S(\bar{a})\bar{b}=S(R(\phi _{V})\bar{a})R(\phi _{V})\bar{b}\) for any vectors \(\bar{a},\;\bar{b}\in R^{3}\), and then utilizing the first equation of (25), we can derive (24). It should be noted that (72) is an original form of (11).
Appendix 2: Derivation of third inequality of (26)
Differentiating the fourth equation of (21) with respect to time, and then using the sixth and seventh inequalities of (22), we can write the norm of \(\dot{a}_{CM}(t)\) as
where \(c_{C1}=\max \{ 1/ \Vert n_{C}(t)\Vert \}\). It should be noted that \(c_{C1}\) is a bounded positive constant, because \(n_{C}(t)\) is a nonzero vector. Utilizing (4) and (5), we obtain the inequality \(\Vert \dot{n}_{C}(t)\Vert \le c_{C2}\Vert \dot{p}_{M}(t)\Vert\), where \(c_{C2}\) is a positive constant. Applying this inequality to (73), then substituting (11) into it, and then using the first, second and sixth inequalities of (22), and the inequalities \(\Vert \dot{x}_{V}(t)\Vert \le \Vert \dot{u}(t)\Vert\) and \(\Vert \dot{q}(t)\Vert \le \Vert \dot{u}(t)\Vert\), we can derive the third inequality of (26).
Appendix 3: Derivations of (30) and (32)
For simplicity, we use the expression \(e^{\bar{x}}\) instead of the expression \(\exp (\bar{x})\) for any scalar \(\bar{x}\) in this appendix. In the derivation of (30), we utilize the inequalities
where \(\bar{c} _{1}\) to \(\bar{c}_{16}\) are positive constants.
Using the third equation of (17), we can write the norm of the solution of \(z_{VF}(t)\) as
where \(\bar{z}_{VF}(\bar{\tau })\in R^{6}\) is given by
Using the first inequality of (26), the first to eighth inequalities of (74), and the inequalities \(\Vert \dot{x}_{V}(t)\Vert \le \Vert \dot{u}(t)\Vert\) and \(\Vert \dot{q}(t)\Vert\) \(\le \Vert \dot{u}(t)\Vert\), we can rewrite (75) as
where \(\bar{c}_{VF1}\in R^{+}\) is given by
Comparing the solution of the first-order filter (31) with (76), we have
Using the first equation of (16), we can write the norm of \(z_{C}(t)\) as
Using the first inequality of (26), the first, third and fifth inequalities of (74), and the inequalities \(\Vert \dot{x}_{V}(t)\Vert \le \Vert \dot{u}(t)\Vert\) and \(\Vert \dot{q}(t)\Vert \le \Vert \dot{u}(t)\Vert\), we can rewrite (78) as
Utilizing the second equation of (19), we can write the norm of the solution of \(z_{Q}(t)\) as
Using the third, eleventh and twelfth inequalities of (74), we can rewrite (80) as
Utilizing the second equation of (21), we can write the norm of \(z_{P}(t)\) as
Utilizing (23), the first equation of (19), the third inequality of (22), the third, ninth and eleventh inequalities of (74), and the inequality \(\Vert \dot{q}(t)\Vert \le \Vert \dot{u}(t)\Vert\), we can rewrite (82) as
Applying (77), (79) and (81), to (83), we can derive (30).
In view of the condition that the disturbances \(d_{V}(t)\) and \(d_{M}(t)\) are bounded, we obtain the inequalities
where \(c_{D1}\) and \(c_{D2}\) are positive constants. Using the first equation of (17), we can write the norm of the solution of \(w_{VF1}(t)\) as
Similarly, utilizing the second equation of (17), and then applying the first inequality of (84) to it, we can write the norm of the solution of \(w_{VF2}(t)\) as
Using the third equation of (21), we can write the norm of \(w_{P}(t)\) as
Substituting the third equation of (19) and the second equation of (16) into (87), and then using (23), (85), (86), the third and eleventh inequality of (74), and the first and second inequalities of (84), we can derive (32).
Appendix 4: Derivation of (48)
The motion error \(e_{P}(t)\) with respect to \(\varSigma _{I}\) is parallel to the tangent plane \(g_{C}(p_{M})=0\), because the positions \(p_{M}(t)\) and \(p_{MRC}(t)\) are points on the plane. Therefore, the following relation holds:
Applying the relation \(R(\phi _{V})R(\phi _{V})^{\mathrm {T}}=I_{3}\) to (88), then multiplying both its sides by \(1/\Vert n_{C}(t)\Vert\), and then using the fourth equation of (21), we obtain
Using (47), and then multiplying both its sides by \(\alpha _{M}\), we have
Subtracting each side of (42) from the corresponding side of (24), and then utilizing the second equation of (45), we obtain
Finally, adding (90) to (91), and then using the first equation of (45), we can derive (48).
Appendix 5: Derivation of (54)
Using (53), and then applying the first and second inequalities of (28) to it, we can write the norm of \(f_{P1}(t)\) as
Applying the inequality \(\Vert S(\bar{x})\Vert \le 6\Vert \bar{x}\Vert\) [\(\bar{x}\in R^{3}\)] (derived from the skew-symmetric property) to (92), and then using the second and fourth inequalities of (27), we obtain
Using (52), and then applying the second inequality of (22), the second equation of (26), and the first inequality of (34) to it, we can write the norm of \(\tau _{M}(t)\) as
Applying (93) to (94), and then defining the positive constants \(\bar{c}_{T1}\) to \(\bar{c}_{T3}\) as
we can derive (54).
Appendix 6: Derivation of (55)
Differentiating (44) with respect to time, then multiplying both its sides by \(M_{P}(\phi )\), and then using the first and second equations of (45), we have
Substituting (20) into (96), and then using (53) and (57), we obtain
Substituting (52) into (97), and then using (50), we can derive (55).
Appendix 7: Proof of Theorem 1
We choose the positive definite function
Differentiating (98) with respect to time, and then substituting the error models (49), (56) and (58) into it, we have
Substituting (44) into (99), then applying (48) and the skew-symmetric property \(e_{P}^{V}(t)^{\mathrm {T}}S(\omega _{V}^{V})e_{P}^{V}(t)=0\) to it, and then defining \(W(t)\in R\) as
we obtain
It follows from (98) and (101) that the signals \(V_{1}(t)\), \(e_{H}(t)\), \(e_{P}^{V}(t)\) and \(e_{F}(t)\) are bounded. Using their bounded properties, the inequalities in the properties P1 to P6 and P9, and the assumptions A2, A3 and A9, we can prove that the other closed-loop signals are bounded.
The signals \(e_{H}(t)\), \(e_{P}^{V}(t)\) and \(e_{F}(t)\) are uniformly continuous, because their time derivatives \(\dot{e}_{H}(t)\), \(\dot{e}_{P}^{V}(t)\) and \(\dot{e}_{F}(t)\) are bounded. This means that the signal W(t) is uniformly continuous. It follows from (98), (101) and the uniform continuity of W(t) that \(\lim _{t\rightarrow \infty }W(t)=0\) (e.g., Lemma A.6 of [47]). It should be noted that instead of Lemma A.6 of [47], we can use LaSalle-Yoshizawa Theorem A.8 of [48]. In this case, instead of the uniform continuity of W(t) , it is required that the error models (49), (56) and (58) are locally Lipschitz. It follows from the zero convergence of W(t) that the error signals \(e_{P}^{V}(t)\), \(e_{H}(t)\) and \(e_{F}(t)\) are asymptotical stable. Furthermore, using (47) and the sixth inequality of (22), and then applying the asymptotic stability of \(e_{P}^{V}(t)\), we can prove that \(e_{P}(t)\) is asymptotical stable.
Integrating \(\dot{e}_{F}(t)\) from 0 to t with respect to time, and then taking its limit, we have
In the derivation of (102), we use the asymptotic stability of \(e_{F}(t)\). The Eq. (102) means that the limit of the integration of \(\dot{e}_{F}(t)\) exists and is finite. Furthermore, the boundedness of \(\ddot{e}_{F}(t)\) implies that \(\dot{e}_{F}(t)\) is uniformly continuous. Therefore, the conditions of Barbalat Lemma (e.g., Lemma A.6 of [48]) are satisfied, and hence \(\dot{e}_{F}(t)\) is asymptotically stable. Solving (49) for the term \(a_{CM}(t)e_{\varLambda }(t)\), and then applying the asymptotic stabilities of \(e_{P}^{V}(t)\), \(e_{F}(t)\) and \(\dot{e}_{F}(t)\) to it, we obtain
Moreover, it follows from (103) and the second equation of (26) that \(e_{\varLambda }(t)\) is asymptotically stable. The proof is complete.
Appendix 8: Proof of Theorem 2
We choose the positive definite function
Differentiating (104) with respect to time, and then substituting the error models (49), (55) and (56) into it, we have
where \(\dot{V}_{1}(t)\) is given by (99). Moreover, substituting (44) into (106), then applying (48) and the skew-symmetric property \(e_{P}^{V}(t)^{\mathrm {T}}S(\omega _{V}^{V})e_{P}^{V}(t)=0\) to it, and then defining \(Y_{1}(t)\in R\) as
we obtain
We can rewrite (107) as
where \(\bar{c}_{17}\) is a positive constant. In the derivation of (109), we use (32), (57), the first inequality of (28), the sixth inequality of (41), and the inequality \(\bar{a}\bar{b}\le \bar{c}\bar{a}^{2}+\bar{b}^{2}/(4\bar{c})\) [\(\bar{a},\,\bar{b}\in R\); \(\bar{c}\in R^{+}\)]. Applying (29) and (109) to (108), then defining \(\bar{c}_{18}\) and \(\alpha\) as
respectively, and then using (104), we have
Moreover, applying Lemma 3.2.4 of [49] to (110), we obtain
In a way similar to the proof of Theorem 1, except that the “bounded” disturbance term \(f_{P2}(t)\) exists, we can prove that the closed-loop signals are bounded.
In a way similar to the aforementioned analysis of \(\dot{V}_{2}(t)\), we can obtain the time derivative
where \(\bar{c}_{19}=\min \{ 1/c_{M5},\,1\}\), and \(Y_{2}(t)\in R\) is given by
In a way similar to the derivation of (109), we can rewrite (113) as
Applying (109) and (114) to (112), and then applying Lemma 3.2.4 of [49] to it, we have
We can derive (59) and (61) from (115), and furthermore, using (47), (59), and the sixth inequality of (22), we obtain (60). Similarly, we can derive the time derivative
We can derive (62) from (116), and furthermore, using (49) and the second equation of (26), we obtain (63). The proof is complete.
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Taira, Y., Sagara, S. & Oya, M. Motion and force control with a linear force error filter for the manipulator of an underwater vehicle-manipulator system. Artif Life Robotics 27, 90–106 (2022). https://doi.org/10.1007/s10015-021-00708-9
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DOI: https://doi.org/10.1007/s10015-021-00708-9