Abstract
A day-by-day increase in applications of robotic manipulators has led to an era when a variety of tasks are expected from a system with the consumption of least possible resources. One recent application is in cyber-physical space. Resource limitation is a problem, particularly when working in a cyber-physical architecture. With this in mind, aperiodic control techniques were introduced and developed upon. This was based on the fact that there always exists some redundancy in control signal generation which can be avoided. In this paper, we have introduced an event-triggered control technique for trajectory tracking by robotic manipulators. This technique is superior to uniform-interval controller as control computations are done only at instances when the system needs attention. This event-triggered approach is applied to a learning-based incremental PID controller to demonstrate the simplicity in application. Simulation results show the effectiveness of the proposed methodology for trajectory tracking.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wang, Y., Wang, S., Wei, Q., Tan, M., Zhou, C., Yu, J.: Development of an underwater manipulator and its free-floating autonomous operation. IEEE/ASME Trans. Mechatron. 21(2), 815–824 (2016)
Kim, D.J., Wang, Z., Paperno, N., Behal, A.: System design and implementation of ucf-manus x2014; an intelligent assistive robotic manipulator. IEEE/ASME Trans. Mechatron. 19(1): 225–237 (2014)
Zanchettin, A.M., Bascetta, L., Rocco, P.: Achieving humanlike motion: resolving redundancy for anthropomorphic industrial manipulators. IEEE Robot. Autom. Mag. 20(4), 131138 (2013)
Karayiannidis, Y., Smith, C., Barrientos, F.E.V., Ogren, P., Kragic, D.: An adaptive control approach for opening doors and drawers under uncertainties. IEEE Trans. Robot. 32(1), 161175 (2016)
Ajwad, S.A., Ullah, M.I., Khelifa, B., Iqbal, J.: A comprehensive state-of-the-art on control of industrial articulated robots. J. Balkan Tribological Assoc. 20(4), 499–521 (2014)
Kar, A.K., Dhar, N.K., Chandola, R., Nawaz, S.S.F., Verma, N.K.: Trajectory tracking by automated guided vehicle using GA optimized sliding mode control. In: 11th International Conference on Industrial and Information Systems (ICIIS) (2016). https://doi.org/10.1109/ICIINFS.2016.8262910
Kar, A.K., Dhar, N.K., Nawaz, S.S.F., Chandola, R., Verma, N.K.: Automated guided vehicle navigation with obstacle avoidance in normal and guided environments. In: 11th International Conference on Industrial and Information Systems (ICIIS) (2016). https://doi.org/10.1109/ICIINFS.2016.8262911
Rajurkar, S.D., Kar, A.K., Goswami, S., Verma, N.K.: Optimal path estimation and tracking for an automated vehicle using GA optimized fuzzy controller. In: 11th International Conference on Industrial and Information Systems (ICIIS) (2016). https://doi.org/10.1109/ICIINFS.2016.8262967
Craig, J.J.: Introduction to Robotics: Mechanics and Control. Addison-Wesley Longman, Boston (1989)
Spong, M.W., Vidyasagar, M.: Robot dynamics and control. Wiley, Hoboken (2008)
Kelly, R.: Global positioning of robot manipulators via PD control plus a class of nonlinear integral actions. IEEE Trans. Autom. Control 47(7), 934–938 (1998)
Khalil, H.K., Grizzle, J.W.: Nonlinear Systems, vol. 3. Prentice hall, Upper Saddle River (1996)
Mustafa, A., Tyagi, C., Verma, N.K.: Inverse kinematics evaluation for robotic manipulator using support vector regression and Kohonen self organizing map. In: IEEE International Conference on Industrial and Information Systems (ICIIS), India (In proceedings) (2016)
Utkin, V.: Sliding mode control design principles and applications to electric drives. IEEE Trans. Ind. Electron. 40(1), 23–36 (1993)
Hung, J., Gao, W., Hung, J.: Variable structure control: a survey. IEEE Trans. Ind. Electron. 40(1), 2–22 (1993)
Verma, N.K., Dhar, N.K., Kar, A.K., Dev, R., Nawaz, S.S.F., Salour, A.: Internet of things based framework for trajectory tracking control. IEEE World Forum on Internet of Things. USA (2016). https://doi.org/10.1109/WF-IoT.2016.7845460
Sage, H.G., De, Mathelin M.F., Ostertag, E.: Robust control of robot manipulators: a survey. Int. J. Control 72(16), 1498–1522 (1999)
Hu, Q., Xiao, B.: Robust adaptive backstepping attitude stabilization and vibration reduction of flexible spacecraft subject to actuator saturation. J. Vib. Control 17(11), 1657–1671 (2011)
Chen, G., Lewis, F.L.: Distributed adaptive tracking control for synchronization of unknown networked Lagrangian systems. IEEE Trans. Syst. Man Cybern. 41(3), 805–816 (2011)
Mustafa, A., Dhar, N.K., Agarwal, P., Verma, N.K.: Adaptive backstepping sliding mode control based on nonlinear disturbance observer for trajectory tracking of robotic manipulator. In: 2nd International Conference on Control and Robotics Engineering (ICCRE) (2017). https://doi.org/10.1109/ICCRE.2017.7935036
Ullah, M.I., Ajwad, S.A., Irfan, M., Iqbal, J.: Non-linear control law for articulated serial manipulators: simulation augmented with hardware implementation. Elektronika Ir Elektrotechnika 22(1), 3–7 (2016)
Dhar, N.K., Verma, N.K., Behera, L., Jamshidi Mo, M.: On an integrated approach to networked climate control of a smart home. IEEE Syst. J. 12(2), 1317–1328 (2018)
Dhar, N.K., Verma, N.K., Behera, L.: Evolutionary algorithm tuned fuzzy PI controller for a networked HVAC system. Recent developments and the new direction in soft-computing foundations and applications. Studies in Fuzziness and Soft Computing, vol. 361, pp. 319–334, Springer, Cham ( 2018). https://doi.org/10.1007/978-3-319-75408-6_25
Dhar, N.K., Verma, N.K., Behera, L.: Intelligent controller design coupled in a communication framework for a networked HVAC system. In: IEEE Congr. Evol. Comput., pp. 5325–5332, Vancouver, BC, Canada (2016). https://doi.org/10.1109/CEC.2016.7748367
Yook, J., Tilbury, D., Soparkar, N.: Trading computation for bandwidth: reducing communication in distributed control systems using state estimators. IEEE Trans. Control Syst. Technol. 10(4), 503–518 (2002)
Tabuada, P.: Event-triggered real-time scheduling of stabilizing control tasks. IEEE Trans. Autom. Control 52(9), 1680–1685 (2007)
Dhar, N.K., Verma, N.K., Behera, L.: Adaptive critic based event-triggered control for HVAC system. IEEE Transactions on Industrial Informatics. 14(1), 171–188 (2018)
Li, H., Chen, Z., Wu, L., Wu, L., Lam, H.-K.: Event-triggered control for nonlinear systems under unreliable communication links. IEEE Trans. Fuzzy Syst. 25(4), 813–824 (2016)
Ma, L., Wang, Z., Lam, H.-K.: Event-triggered mean-square consensus control for time-varying Stochastic multi-agent system with sensor saturations. IEEE Trans. Autom. Control 62(7), 3524–3531 (2016)
Zhang, Q., Zhao, D., Zhu, Y.: Event-triggered H control for continuous-time nonlinear system via concurrent learning. IEEE Trans. Syst. Man Cybern.: Syst. 47(7), 1071–1081 (2016)
Dong, L., Zhong, X., Sun, C., He, H.: Adaptive event-triggered control based on Heuristic dynamic programming for nonlinear discrete-time systems. IEEE Trans. Neural Netw. Learn. Syst. 28(7), 1594–1605 (2016)
Tripathy, N.S., Kar, I.N., Paul, K.: An event-triggered based robust control of robot manipulator. In: 13th International Conference on Control Automation Robotics & Vision (ICARCV) (2014). https://doi.org/10.1109/ICARCV.2014.7064343
Baldi, P.: Gradient descent learning algorithm overview. IEEE Trans. Neural Netw. 6(1), 182–195 (1995)
Arzen, K.E.: A Simple event-based PID controller. In: 14th IFAC World Congress (1999)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Kamboj, A., Dhar, N.K., Verma, N.K. (2019). Event-Triggered Control for Trajectory Tracking by Robotic Manipulator. In: Verma, N., Ghosh, A. (eds) Computational Intelligence: Theories, Applications and Future Directions - Volume I. Advances in Intelligent Systems and Computing, vol 798. Springer, Singapore. https://doi.org/10.1007/978-981-13-1132-1_13
Download citation
DOI: https://doi.org/10.1007/978-981-13-1132-1_13
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-1131-4
Online ISBN: 978-981-13-1132-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)