Adaptive PID control; Drop-foot; Functional electrical stimulation; Muscle fatigue; Self-tuning gain; Adaptive proportional–integral–derivative control; Control strategies; Drop feet; Functional electri-cal stimulations; Muscle fatigues; Proportional integral derivative control; Proportional-integral-derivatives controllers; Selftuning; Tuning gain; Control and Systems Engineering; Computer Science Applications; Electrical and Electronic Engineering; Applied Mathematics
Abstract :
[en] A robust, adaptive proportional–integral–derivative (PID) control strategy is presented for controlling ankle movement using a functional electrical stimulation (FES) neuroprosthesis. The presented control strategy leverages the structurally simple PID controller. Moreover, the proposed PID controller automatically tunes its gains without requiring prior knowledge of the musculoskeletal system. Thus, in contrast to previously proposed control strategies for FES, the proposed controller does not necessitate time-consuming model identification for each patient. Additionally, the computational cost of the controller is minimized by linking the PID gains and updating only the common gain. As a result, a model-free, structurally simple, and computationally inexpensive controller is achieved, making it suitable for wearable FES-based neuroprostheses. A Lyapunov stability analysis proves uniformly ultimately bounded (UUB) tracking of the joint angle. Results from the simulated and experimental trials indicate that the proposed PID controller demonstrates high tracking accuracy and fast convergence.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Tanhaei, Ghazal; Sports Medicine Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
HABIBI, Hamed ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Automation
Holderbaum, William; School of Biological Sciences, Biomedical Engineering, University of Reading, Reading, United Kingdom
Ansari, Noureddin Nakhostin; Sports Medicine Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran ; Research Center for War-affected People, Tehran University of Medical Sciences, Tehran, Iran ; Department of Physiotherapy, School of Rehabilitation, Tehran University of Medical Sciences, Tehran, Iran
External co-authors :
yes
Language :
English
Title :
Robust adaptive PID control of functional electrical stimulation for drop-foot correction
The authors would like to express their gratitude to the Djavad Mowafaghian Research Center for Intelligent Neuro-Rehabilitation Technologies for their invaluable support and resources, which made this research possible. This work was supported by the Iran's Organization for Development of International Cooperation in Science and Technology.
Ajoudani, A., Erfanian, A., A neuro-sliding-mode control with adaptive modeling of uncertainty for control of movement in paralyzed limbs using functional electrical stimulation. IEEE Transactions on Biomedical Engineering 56:7 (2009), 1771–1780.
Barrett, C., Taylor, P., The effects of the odstock drop foot stimulator on perceived quality of life for people with stroke and multiple sclerosis. Neuromodulation: Technology at the Neural Interface 13:1 (2010), 58–64.
Benoussaad, M., Mombaur, K., Azevedo-Coste, C., Nonlinear model predictive control of joint ankle by electrical stimulation for drop foot correction. 2013 IEEE/RSJ international conference on intelligent robots and systems, 2013, IEEE, 983–989.
Błażkiewicz, M., Wiszomirska, I., Kaczmarczyk, K., Brzuszkiewicz-Kuźmicka, G., Wit, A., Mechanisms of compensation in the gait of patients with drop foot. Clinical Biomechanics 42 (2017), 14–19.
Cao, Y., Song, Y.-D., Adaptive PID-like fault-tolerant control for robot manipulators with given performance specifications. International Journal of Control 93:3 (2020), 377–386.
Don, R., Serrao, M., Vinci, P., Ranavolo, A., Cacchio, A., Ioppolo, F., et al. Foot drop and plantar flexion failure determine different gait strategies in charcot-marie-tooth patients. Clinical Biomechanics 22:8 (2007), 905–916.
Ekinci, S., Izci, D., Al Nasar, M.R., Abu Zitar, R., Abualigah, L., Logarithmic spiral search based arithmetic optimization algorithm with selective mechanism and its application to functional electrical stimulation system control. Soft Computing 26:22 (2022), 12257–12269.
Esnouf, J., Taylor, P., Mann, G., Barrett, C., Impact on activities of daily living using a functional electrical stimulation device to improve dropped foot in people with multiple sclerosis, measured by the Canadian occupational performance measure. Multiple Sclerosis Journal 16:9 (2010), 1141–1147.
Feiereisen, P., Duchateau, J., Hainaut, K., Motor unit recruitment order during voluntary and electrically induced contractions in the tibialis anterior. Experimental Brain Research 114 (1997), 117–123.
Ferrarin, M., Palazzo, F., Riener, R., Quintern, J., Model-based control of FES-induced single joint movements. IEEE Transactions on Neural Systems and Rehabilitation Engineering 9:3 (2001), 245–257.
Ferrarin, M., Pedotti, A., The relationship between electrical stimulus and joint torque: A dynamic model. IEEE Transactions on Rehabilitation Engineering 8:3 (2000), 342–352.
Ge, S.S., Hong, F., Lee, T.H., Adaptive neural control of nonlinear time-delay systems with unknown virtual control coefficients. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 34:1 (2004), 499–516.
Guo, X.-G., Ahn, C.K., Adaptive fault-tolerant pseudo-PID sliding-mode control for high-speed train with integral quadratic constraints and actuator saturation. IEEE Transactions on Intelligent Transportation Systems 22:12 (2020), 7421–7431.
Habibi, H., Nohooji, H.R., Howard, I., Adaptive PID control of wind turbines for power regulation with unknown control direction and actuator faults. IEEE Access 6 (2018), 37464–37479.
Henneman, E., Somjen, G., Carpenter, D.O., Functional significance of cell size in spinal motoneurons. Journal of Neurophysiology 28:3 (1965), 560–580.
Hodgins, L., Freeman, C.T., A hybrid orthosis combining functional electrical stimulation and soft robotics for improved assistance of drop-foot. Medical Engineering & Physics, 115, 2023, 103979.
Izci, D., Ekinci, S., Eker, E., Abualigah, L., Opposition-based arithmetic optimization algorithm with varying acceleration coefficient for function optimization and control of fes system. Proceedings of international joint conference on advances in computational intelligence: IJCACI 2021, 2022, Springer, 283–293.
Izci, D., Ekinci, S., Eker, E., Demirören, A., Multi-strategy modified INFO algorithm: Performance analysis and application to functional electrical stimulation system. Journal of Computer Science, 64, 2022, 101836.
Izci, D., Ekinci, S., Eker, E., Demirören, A., Biomedical application of a random learning and elite opposition-based weighted mean of vectors algorithm with pattern search mechanism. Journal of Control, Automation and Electrical Systems 34:2 (2023), 333–343.
Jacquelin Perry, M., Gait analysis: normal and pathological function. 1992, SLACK, New Jersey.
Jacquelin Perry, M., Gait analysis: normal and pathological function. 2010, SLACK, New Jersey.
Johnson, C.A., Burridge, J.H., Strike, P.W., Wood, D.E., Swain, I.D., The effect of combined use of botulinum toxin type a and functional electric stimulation in the treatment of spastic drop foot after stroke: A preliminary investigation. Archives of Physical Medicine and Rehabilitation 85:6 (2004), 902–909.
Johnson, C.O., Nguyen, M., Roth, G.A., Nichols, E., Alam, T., Abate, D., et al. Global, regional, and national burden of stroke, 1990–2016: A systematic analysis for the global burden of disease study 2016. The Lancet Neurology 18:5 (2019), 439–458.
Jung, P.-G., Huo, W., Moon, H., Amirat, Y., Mohammed, S., A novel gait phase detection algorithm for foot drop correction through optimal hybrid FES-orthosis assistance. 2021 IEEE international conference on robotics and automation, 2021, IEEE, 10391–10397.
Khalil, H.K., Universal integral controllers for minimum-phase nonlinear systems. IEEE Transactions on Automatic Control 45:3 (2000), 490–494.
Kirsch, N., Alibeji, N., Sharma, N., Nonlinear model predictive control of functional electrical stimulation. Control Engineering Practice 58 (2017), 319–331.
Kobravi, H.-R., Erfanian, A., Decentralized adaptive robust control based on sliding mode and nonlinear compensator for the control of ankle movement using functional electrical stimulation of agonist–antagonist muscles. Journal of Neural Engineering, 6(4), 2009, 046007.
Lynch, C.L., Popovic, M.R., Functional electrical stimulation. IEEE Control Systems Magazine 28:2 (2008), 40–50.
Lyons, G.M., Sinkjær, T., Burridge, J.H., Wilcox, D.J., A review of portable FES-based neural orthoses for the correction of drop foot. IEEE Transactions on Neural Systems and Rehabilitation Engineering 10:4 (2002), 260–279.
Melo, P., Silva, M., Martins, J., Newman, D., Technical developments of functional electrical stimulation to correct drop foot: sensing, actuation and control strategies. Clinical Biomechanics 30:2 (2015), 101–113.
Meng, Y., Jiang, B., Qi, R., Adaptive fault-tolerant attitude tracking control of hypersonic vehicle subject to unexpected centroid-shift and state constraints. Aerospace Science and Technology, 95, 2019, 105515.
Nekoukar, V., Erfanian, A., A decentralized modular control framework for robust control of FES-activated walker-assisted paraplegic walking using terminal sliding mode and fuzzy logic control. IEEE Transactions on Biomedical Engineering 59:10 (2012), 2818–2827.
Oliveira, T.R., Costa, L.R., Catunda, J.M.Y., Pino, A.V., Barbosa, W., de Souza, M.N., Time-scaling based sliding mode control for neuromuscular electrical stimulation under uncertain relative degrees. Medical Engineering & Physics 44 (2017), 53–62.
Page, A., Freeman, C., Point-to-point repetitive control of functional electrical stimulation for drop-foot. Control Engineering Practice, 96, 2020, 104280.
Paz, P., Oliveira, T.R., Pino, A.V., Fontana, A.P., Model-free neuromuscular electrical stimulation by stochastic extremum seeking. IEEE Transactions on Control Systems Technology 28:1 (2019), 238–253.
Peng, C., Tian, E., Zhang, J., Du, D., Decentralized event-triggering communication scheme for large-scale systems under network environments. Information Sciences 380 (2017), 132–144.
Radák, Z., Chapter 2 - skeletal muscle, function, and muscle fiber types. Radák, Z., (eds.) The physiology of physical training, 2018, Academic Press, 15–31, 10.1016/B978-0-12-815137-2.00002-4 URL https://www.sciencedirect.com/science/article/pii/B9780128151372000024.
Roche, A., Laighin, G.ó., Coote, S., Surface-applied functional electrical stimulation for orthotic and therapeutic treatment of drop-foot after stroke–A systematic review. Physical Therapy Reviews 14:2 (2009), 63–80.
Seel, T., Werner, C., Raisch, J., Schauer, T., Iterative learning control of a drop foot neuroprosthesis—Generating physiological foot motion in paretic gait by automatic feedback control. Control Engineering Practice 48 (2016), 87–97.
Singh, M., Sharma, N., Data-driven model predictive control for drop foot correction. 2023 American control conference, 2023, IEEE, 2615–2620.
Song, Y., Huang, X., Wen, C., Tracking control for a class of unknown nonsquare MIMO nonaffine systems: A deep-rooted information based robust adaptive approach. IEEE Transactions on Automatic Control 61:10 (2015), 3227–3233.
Song, Y., Huang, X., Wen, C., Robust adaptive fault-tolerant PID control of MIMO nonlinear systems with unknown control direction. IEEE Transactions on Industrial Electronics 64:6 (2017), 4876–4884.
Taylor, P., Humphreys, L., Swain, I., The long-term cost-effectiveness of the use of functional electrical stimulation for the correction of dropped foot due to upper motor neuron lesion. Journal of Rehabilitation Medicine 45:2 (2013), 154–160.
Van, M., An enhanced robust fault tolerant control based on an adaptive fuzzy PID-nonsingular fast terminal sliding mode control for uncertain nonlinear systems. IEEE/ASME Transactions on Mechatronics 23:3 (2018), 1362–1371.
Von Schroeder, H.P., Coutts, R.D., Lyden, P.D., Billings, E., Nickel, V.L., Gait parameters following stroke: A practical assessment. Journal of Rehabilitation Research and Development 32 (1995), 25–31.
Wang, Y., Mukaino, M., Ohtsuka, K., Otaka, Y., Tanikawa, H., Matsuda, F., et al. Gait characteristics of post-stroke hemiparetic patients with different walking speeds. International Journal of Rehabilitation Research 43:1 (2020), 69–75.
Zhang, Q., Lambeth, K., Iyer, A., Sun, Z., Sharma, N., Ultrasound imaging-based closed-loop control of functional electrical stimulation for drop foot correction. IEEE Transactions on Control Systems Technology 31:3 (2022), 989–1005.
Zhao, K., Song, Y., Wen, C., Computationally inexpensive fault tolerant control of uncertain non-linear systems with non-smooth asymmetric input saturation and undetectable actuation failures. IET Control Theory & Applications 10:15 (2016), 1866–1873.
