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Compensation control of hydraulic manipulator under pressure shock disturbance

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Abstract

This study aims to develop an advanced controller for high-accuracy tracking control ofhydraulic manipulators. The primary technical challenges identified in previous research are friction, leakage, external disturbance, and modelling uncertainties. However, this study for the first time discovers that pressure shock disturbance generated by the supply pump significantly impairs the tracking performance of the hydraulic robotic arm. To address these issues, a shock disturbance compensation controller (SDCC) based on backstepping is proposed in this research. A newly developed adaptive controller and compensation controller are used to handling uncertainties and pressure shock disturbance in the hydraulic system, respectively. The controller theoretically guarantees the asymptotic tracking performance of the hydraulic manipulator under uncertainties and mixed disturbances. Extensive comparative experimental results show that the addition of SDCC reduces the maximum tracking error and variance of PID by an average of 68.7\(\%\) and 68.55\(\%\), respectively.

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Data availibility

The datasets of the current study are available from the corresponding author on reasonable request.

References

  1. Koivumäki, J., Mattila, J.: Stability-guaranteed force-sensorless contact force/motion control of heavy-duty hydraulic manipulators. IEEE Trans. Rob. 31(4), 918–935 (2015)

    Article  Google Scholar 

  2. Ding, R., Cheng, M., Jiang, L., Hu, G.: Active fault-tolerant control for electro-hydraulic systems with an independent metering valve against valve faults. IEEE Trans. Industr. Electron. 68(8), 7221–7232 (2020)

    Article  Google Scholar 

  3. Guo, K., Li, M., Shi, W., Pan, Y.: Adaptive tracking control of hydraulic systems with improved parameter convergence. IEEE Trans. Ind. Electr. 69(7), 7140–7150 (2021)

    Article  Google Scholar 

  4. Li, C., Lyu, L., Helian, B., Chen, Z., Yao, B.: Precision motion control of independent metering hydraulic system with nonlinear flow modeling and compensation. IEEE Trans. Ind. Electr. 69(7), 7088–7098 (2021)

    Article  Google Scholar 

  5. Koivumäki, J., Zhu, W.-H., Mattila, J.: Energy-efficient and high-precision control of hydraulic robots. Control. Eng. Pract. 85, 176–193 (2019)

    Article  Google Scholar 

  6. Sirouspour, M.R., Salcudean, S.E.: Nonlinear control of hydraulic robots. IEEE Trans. Robot. Autom. 17(2), 173–182 (2001)

    Article  Google Scholar 

  7. Mohanty, A., Yao, B.: Indirect adaptive robust control of hydraulic manipulators with accurate parameter estimates. IEEE Trans. Control Syst. Technol. 19(3), 567–575 (2010)

    Article  Google Scholar 

  8. Yao, J., Jiao, Z., Ma, D., Yan, L.: High-accuracy tracking control of hydraulic rotary actuators with modeling uncertainties. IEEE/ASME Trans. Mechatron. 19(2), 633–641 (2013)

    Article  Google Scholar 

  9. Ma, H., Li, Y.: A novel dead zone reaching law of discrete-time sliding mode control with disturbance compensation. IEEE Trans. Industr. Electron. 67(6), 4815–4825 (2019)

    Article  Google Scholar 

  10. Guo, Q., Yin, J., Yu, T., Jiang, D.: Saturated adaptive control of an electrohydraulic actuator with parametric uncertainty and load disturbance. IEEE Trans. Industr. Electron. 64(10), 7930–7941 (2017)

    Article  Google Scholar 

  11. Wang, Z., Qian, Z., Lu, J., Wu, P.: Effects of flow rate and rotational speed on pressure fluctuations in a double-suction centrifugal pump. Energy 170, 212–227 (2019)

    Article  Google Scholar 

  12. Zhao, X., Xiao, Y., Wang, Z., Luo, Y., Cao, L.: Unsteady flow and pressure pulsation characteristics analysis of rotating stall in centrifugal pumps under off-design conditions. J. Fluids Eng. 140(2), 021105 (2018)

    Article  Google Scholar 

  13. González, J., Parrondo, J., Santolaria, C., Blanco, E.: Steady and unsteady radial forces for a centrifugal pump with impeller to tongue gap variation. J. Fluids Eng. 128(3), 454–462 (2006)

    Article  Google Scholar 

  14. Van de Ven, J.D.: Constant pressure hydraulic energy storage through a variable area piston hydraulic accumulator. Appl. Energy 105, 262–270 (2013)

    Article  Google Scholar 

  15. Honkakorpi, J., Vihonen, J., Mattila, J.: Sensor module for hydraulic boom state feedback control. Int. J. Fluid Power 13(3), 15–23 (2012)

    Article  Google Scholar 

  16. Ding, R., Xu, B., Zhang, J., Cheng, M.: Self-tuning pressure-feedback control by pole placement for vibration reduction of excavator with independent metering fluid power system. Mech. Syst. Signal Process. 92, 86–106 (2017)

    Article  Google Scholar 

  17. Bianchi, R., Ritelli, G.F., Vacca, A.: Payload oscillation reduction in load-handling machines: A frequency-based approach. In: Proceedings of the institution of mechanical engineers, Part I: Journal of Systems and Control Engineering 231(3), 199–212 (2017)

  18. Cheng, M., Luo, S., Ding, R., Xu, B., Zhang, J.: Dynamic impact of hydraulic systems using pressure feedback for active damping. Appl. Math. Model. 89, 454–469 (2021)

    Article  MATH  Google Scholar 

  19. Deng, W., Yao, J.: Asymptotic tracking control of mechanical servosystems with mismatched uncertainties. IEEE/ASME Trans. Mechatron. 26(4), 2204–2214 (2020)

    Article  Google Scholar 

  20. Guo, Q., Yin, J.-M., Yu, T., Jiang, D.: Coupled-disturbance-observer-based position tracking control for a cascade electro-hydraulic system. ISA Trans. 68, 367–380 (2017)

    Article  Google Scholar 

  21. Guo, Q., Zuo, Z., Ding, Z.: Parametric adaptive control of single-rod electrohydraulic system with block-strict-feedback model. Automatica 113, 108807 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  22. Zhang, J., Liu, J., Ding, F.: Collaborative optimization design framework for hierarchical filter barrier control suspension system with projection adaptive tracking hydraulic actuator. Nonlinear Dyn. 108(4), 3417–3434 (2022)

    Article  Google Scholar 

  23. Yin, X., Pan, L.: Enhancing trajectory tracking accuracy for industrial robot with robust adaptive control. Robotics Comput-Integr. Manuf. 51, 97–102 (2018)

    Article  Google Scholar 

  24. Ma, H., Guo, J., Wu, J., Xiong, Z., Lee, K.-M.: An active control method for chatter suppression in thin plate turning. IEEE Trans. Industr. Inf. 16(3), 1742–1753 (2019)

    Article  Google Scholar 

  25. Ma, H., Li, Y., Xiong, Z.: Discrete-time sliding-mode control with enhanced power reaching law. IEEE Trans. Industr. Electron. 66(6), 4629–4638 (2018)

    Article  Google Scholar 

  26. Ma, H., Wu, J., Xiong, Z.: A novel exponential reaching law of discrete-time sliding-mode control. IEEE Trans. Industr. Electron. 64(5), 3840–3850 (2017)

  27. Alleyne, A., Liu, R.: On the limitations of force tracking control for hydraulic servosystems. J. Dyn. Sys. Meas. Control. 121(2), 184–190 (1999)

    Article  Google Scholar 

  28. Lischinsky, P., Canudas-de-Wit, C., Morel, G.: Friction compensation for an industrial hydraulic robot. IEEE Control Syst. Mag. 19(1), 25–32 (1999)

    Article  Google Scholar 

  29. Yao, J.: Model-based nonlinear control of hydraulic servo systems: challenges, developments and perspectives. Front. Mech. Eng. 13(2), 179–210 (2018)

    Article  MathSciNet  Google Scholar 

  30. Arteaga-Peréz, M.A., Pliego-Jiménez, J., Romero, J.G.: Experimental results on the robust and adaptive control of robot manipulators without velocity measurements. IEEE Trans. Control Syst. Technol. 28(6), 2770–2773 (2019)

    Article  Google Scholar 

  31. Battarra, M., Mucchi, E.: On the relation between vane geometry and theoretical flow ripple in balanced vane pumps. Mech. Mach. Theory 146, 103736 (2020)

    Article  Google Scholar 

  32. Manring, N.D., Fales, R.C.: Hydraulic Control Systems. John Wiley & Sons, New Jersey (2019)

    Google Scholar 

  33. Spong, M.W.: On the robust control of robot manipulators. IEEE Trans. Autom. Control 37(11), 1782–1786 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  34. Gao, Z.: On the centrality of disturbance rejection in automatic control. ISA Trans. 53(4), 850–857 (2014)

    Article  Google Scholar 

  35. Petrović, G.R., Mattila, J.: Mathematical modelling and virtual decomposition control of heavy-duty parallel-serial hydraulic manipulators. Mech. Mach. Theory 170, 104680 (2022)

    Article  Google Scholar 

  36. Zhu, W.-H., Lamarche, T., Dupuis, E., Jameux, D., Barnard, P., Liu, G.: Precision control of modular robot manipulators: the vdc approach with embedded fpga. IEEE Trans. Rob. 29(5), 1162–1179 (2013)

    Article  Google Scholar 

  37. Humaloja, J.-P., Koivumäki, J., Paunonen, L., Mattila, J.: Decentralized observer design for virtual decomposition control. IEEE Trans. Autom. Control 67(5), 2529–2536 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  38. Zhu, W.-H.: Virtual Decomposition Control: Toward Hyper Degrees of Freedom Robots, vol. 60. Springer, New Jersey (2010)

  39. Yao, J., Jiao, Z., Ma, D.: Extended-state-observer-based output feedback nonlinear robust control of hydraulic systems with backstepping. IEEE Trans. Industr. Electron. 61(11), 6285–6293 (2014)

    Article  Google Scholar 

  40. Baek, J., Jin, M., Han, S.: A new adaptive sliding-mode control scheme for application to robot manipulators. IEEE Trans. Industr. Electron. 63(6), 3628–3637 (2016)

    Article  Google Scholar 

Download references

Funding

This work was supported in part by the National Natural Science Foundation of China under Grant 51975336, in part by the Key Research and Development Program of Shandong Province under Grant 2020JMRH0202, and in part by Shandong Province New Old Energy Conversion Major Industrial Tackling Projects under Grant 2021-13.

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Correspondence to Yi Wan.

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Appendices

Appendix A Proof of Theorem 1

Given (23) (24) and (25), we have

$$\begin{aligned} \begin{aligned} e_{2}^T {m} \dot{e_{2}}=\,&e_{2}^T\left( e_3{-}k_pe_1{-}k_v{{\dot{e}}}_1{+}{\varvec{\Phi }}\widetilde{{{\varvec{P}}}}{+}u{-}\varvec{{c}}e_{2}{-}d\right) \\&\quad {-}\varvec{{c}}\,e_{2}^Te_{2} \end{aligned} \end{aligned}$$
(45)

Then, we can transform (33) as follows

$$\begin{aligned} \begin{aligned} {{\dot{V}}}_1\left( t\right) =&\frac{1}{2}e_{2}^T\dot{\varvec{{m}}}e_{2}{-}e_{2}^T\varvec{{c}}e_{2}{+}e_1^T\left( k_{p1}{+}\gamma _1k_{v1}\right) \dot{e_1}{+}e_{2}^Te_3\\&{+}e_{2}^T\left( {-}k_pe_1{-}k_v{{\dot{e}}}_1\right) \\&+e_{2}^T{\varvec{\Phi }}\widetilde{{{\varvec{P}}}}+{\widetilde{{{\varvec{P}}}}}^T{\varvec{\Gamma }}^{-1}\dot{\widetilde{{{\varvec{P}}}}}+e_{3}^T(u-d)\\&+e_3^T{{\dot{e}}}_3+\lambda _1^{-1}{\widetilde{d}}{\dot{{\widetilde{d}}}}+\lambda _2^{-1}\epsilon {\dot{\epsilon }} \end{aligned} \end{aligned}$$
(46)

According to (29), we have

$$\begin{aligned} \begin{aligned} e_{1}^{T}\left( k_{p 1}+\gamma _{1} k_{v 1}\right) {\dot{e}}_{1}=e_{1}^{T} k_{p} {\dot{e}}_{1}-e_{1}^{T} {\frac{k_{p 2}}{\alpha +\left| e_{1 }\right| }} {\dot{e}}_{1}\\ +e_{1}^{T} \gamma _{1}(k_{v}-{\frac{k_{v 2}}{\beta +\left| {\dot{e}}_{1}\right| }}) \dot{e_{1}} \end{aligned} \end{aligned}$$
(47)

Using Property 1 in [33], the following formula can be obtained

$$\begin{aligned} \frac{1}{2}e_{3}^T\dot{\varvec{{m}}}e_{3}-e_{3}^T\varvec{{c}}e_{3}=0 \end{aligned}$$
(48)

Then, combining (18) and (31), the following equation can be obtained

$$\begin{aligned} \begin{aligned} e_{3}^T\left( {-}k_pe_1-k_v{{\dot{e}}}_1\right) {=}&{-}e_1^Tk_p\dot{e_1}{-}{{\dot{e}}}_1^Tk_v\dot{e_1}-\gamma _1e_1^Tk_pe_1\\ -\gamma _1e_1^Tk_v{{\dot{e}}}_1 \end{aligned} \end{aligned}$$
(49)

In view of [40], Property 3 in [33] and (27), we have

$$\begin{aligned} \begin{aligned} {\dot{V}}_{1}(t)= {\dot{e}}_{1}^{T} e_{3}-e_{1}^{T} {\frac{k_{p 2}}{\alpha +\left| e_{1}\right| }} {\dot{e}}_{1} -e_{1}^{T} {\frac{\gamma _{1} k_{v 2}}{\beta +\left| {\dot{e}}_{1}\right| }} {\dot{e}}_{1}\\ -{\dot{e}}_{1}^{T} k_{v} {\dot{e}}_{1} -\gamma _{1} e_{1}^{T} k_{p} {\dot{e}}_{1}+\gamma _{1} e_{1}^{T} e_{3} \end{aligned} \end{aligned}$$
(50)

We can obtain the following inequalities by using Theorem 1.

$$\begin{aligned}{} & {} {\gamma _{1}}+0.5\le 0,\ \ \ {\gamma _{1}}\left( 0.5-{k_{p}}\right) \le 0\\\\{} & {} 0.5-{k_{v}} \le 0, \quad -\frac{0.5 {k_{p 2 }}}{\alpha +\left| {e_{1}}\right| } \le 0, \quad -\frac{0.5 {\gamma _{1} k_{v 2}}}{\beta +\left| {{\dot{e}}_{1}}\right| } \le 0 \end{aligned}$$

Then, by using Young’s inequality, (50) can be deduced that \({{\dot{V}}}_1\left( t\right) \le 0\). Appendix 1 is proven.

Appendix B Proof of Theorem 2

Differentiating \(\mathrm {\Xi }\) yields

$$\begin{aligned} {\dot{\Xi }}=-r^{T}\left[ \dot{\Delta _i}(t)-\lambda {\text {sgn}}\left( e_{3}\right) \right] \end{aligned}$$
(51)

Combining (34) and (51), we have

$$\begin{aligned} \begin{aligned} {\dot{V}}_{2}&={\dot{V}}_{1}(t)+e_{3}^{T} {\dot{e}}_{2}+r^{T} {\dot{r}}+{\dot{\Xi }} \\&=e_{1}^{T}\left[ \gamma _{1}\left( 0.5-k_{p}\right) -\frac{0.5 k_{p 2}}{\alpha +\left| e_{1}\right| }-\frac{0.5 \gamma _{1} k_{v 2}}{\beta +\left| {\dot{e}}_{1}\right| }\right] e_{1}\\&\quad +e_{3}^{T}\left( \gamma _{1}-\gamma _{2}+1\right) e_{3}\\&\quad +{\dot{e}}_{1}^{T}\left( 0.5-k_{v}-\frac{0.5 k_{p 2}}{\alpha +\left| e_{1}\right| }-\frac{0.5 \gamma _{1} k_{v 2}}{\beta +\left| {\dot{e}}_{1}\right| }\right) {\dot{e}}_{1}\\&\quad +\left( 0.5-k_{s}\right) r^{T} r \\ \end{aligned}\nonumber \\ \end{aligned}$$
(52)

By reusing Theorem 1, The following inequalities can be obtained.

$$\begin{aligned} \begin{aligned} 0.5-{k_{s}} \le 0, \quad {\gamma _{1}}-{\gamma _{2}}+1 \le 0 \\ {\gamma _{1}}\left( 0.5-{k_{p}}\right) -\frac{0.5 {k_{p 2 }}}{\alpha +\left| {e_{1}}\right| }-\frac{0.5 {\gamma _{1} k_{v 2}}}{\beta +\left| {{\dot{e}}_{1}}\right| } \le 0 \\ 0.5-{k_{v}}-\frac{0.5 {k_{p 2 }}}{\alpha +\left| {e_{1}}\right| }-\frac{0.5 {\gamma _{1} k_{v 2}}}{\beta +\left| {{\dot{e}}_{1}}\right| } \le 0 \end{aligned} \end{aligned}$$

Finally, simplify (52) yields \({{\dot{V}}}_2\le 0\).

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Sun, Y., Wan, Y., Ma, H. et al. Compensation control of hydraulic manipulator under pressure shock disturbance. Nonlinear Dyn 111, 11153–11169 (2023). https://doi.org/10.1007/s11071-023-08425-7

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