On bandwidth-constrained disturbance rejection control
暂无分享,去创建一个
[1] A. M. Acosta,et al. of the 23 rd Annual EMBS International Conference , October 25-28 , Istanbul , Turkey MODEL-BASED DEVELOPMENT OF NEUROPROSTHESES FOR RESTORING PROXIMAL ARM FUNCTION , 2004 .
[2] Mary Jane Mulcahey,et al. Technical Perspective Functional Electrical Stimulation For Augmented Walking In Adolescents With Incomplete Spinal Cord Injury , 2003 .
[3] C. D. Johnson,et al. Accomodation of external disturbances in linear regulator and servomechanism problems , 1971 .
[4] M. Clerc,et al. The swarm and the queen: towards a deterministic and adaptive particle swarm optimization , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).
[5] Zhu Hong. Delay Margin for Predictive PI Control System , 2005 .
[6] O Smith,et al. CLOSER CONTROL OF LOOPS WITH DEAD TIME , 1957 .
[7] I-Lung Chien,et al. Simple control method for integrating processes with long deadtime , 2002 .
[8] Yi Huang,et al. An alternative paradigm for control system design , 2001 .
[9] Hassan K. Khalil,et al. Full-order high-gain observers for minimum phase nonlinear systems , 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.
[10] Julio E. Normey-Rico,et al. Smith Predictor-Based Control Schemes for Dead-Time Unstable Cascade Processes , 2010 .
[11] Thomas Bäck,et al. Evolutionary Algorithms in Theory and Practice , 1996 .
[12] Zhiqiang Gao,et al. Active disturbance rejection control: a paradigm shift in feedback control system design , 2006, 2006 American Control Conference.
[13] P H Peckham,et al. Functional neuromuscular stimulation for combined control of elbow extension and hand grasp in C5 and C6 quadriplegics. , 1998, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[14] I. Horowitz,et al. Superiority of transfer function over state-variable methods in linear time-invariant feedback system design , 1975 .
[15] Zhiqiang Gao,et al. On the enhanced ADRC design with a low observer bandwidth , 2013, Proceedings of the 32nd Chinese Control Conference.
[16] M. de Mathelin,et al. Robust control of robot manipulators: A survey , 1999 .
[17] Janis J Daly,et al. Feasibility of gait training for acute stroke patients using FNS with implanted electrodes , 2000, Journal of the Neurological Sciences.
[18] R. E. Kalman,et al. On the general theory of control systems , 1959 .
[19] Hassan K. Khalil,et al. Robust stabilization of non-minimum phase nonlinear systems using extended high gain observers , 2011, 2008 American Control Conference.
[20] L. Martins,et al. Analysis of the results of functional electrical stimulation on hemiplegic patients' upper extremities using the Minnesota manual dexterity test , 2005, International journal of rehabilitation research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue internationale de recherches de readaptation.
[21] S. McLean,et al. Development and validation of a 3-D model to predict knee joint loading during dynamic movement. , 2003, Journal of biomechanical engineering.
[22] Si-Zhao Joe Qin,et al. A two-stage iterative learning control technique combined with real-time feedback for independent disturbance rejection , 2004, Autom..
[23] Yuanqing Xia,et al. Active disturbance rejection control for uncertain multivariable systems with time-delay , 2007 .
[24] Riccardo Poli,et al. Particle swarm optimization , 1995, Swarm Intelligence.
[25] R Riener,et al. Patient-driven control of FES-supported standing up and sitting down: experimental results. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.
[26] Yahya Rahmat-Samii,et al. Particle swarm optimization for reconfigurable phase‐differentiated array design , 2003 .
[27] D J Ewins,et al. Practical low cost stand/sit system for mid-thoracic paraplegics. , 1988, Journal of biomedical engineering.
[28] B. N. Petrov,et al. The invariance principle and the conditions for its application during the calculation of linear and non-linear systems , 1960 .
[29] O. J. M. Smith,et al. A controller to overcome dead time , 1959 .
[30] P.E. Crago,et al. Reciprocal EMG control of elbow extension by FES , 2001, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[31] Aidan O'Dwyer,et al. Handbook of PI and PID controller tuning rules , 2003 .
[32] Toshiyuki Kondo,et al. Biological arm motion through reinforcement learning , 2004, Biological Cybernetics.
[33] Derek P. Atherton,et al. Use of Smith Predictor in the Outer Loop for Cascaded Control of Unstable and Integrating Processes , 2008 .
[34] M. H. Mickle,et al. Disturbance estimation and compensation in linear systems , 1990 .
[35] R. Stein,et al. Multicenter evaluation of electrical stimulation systems for walking. , 1999, Archives of physical medicine and rehabilitation.
[36] R. Thomsen. Flexible ligand docking using differential evolution , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..
[37] Jingqing Han,et al. From PID to Active Disturbance Rejection Control , 2009, IEEE Trans. Ind. Electron..
[38] Maarten J. IJzerman,et al. The orthotic effect of functional electrical stimulation on the improvement of walking in stroke patients with a dropped foot: a systematic review. , 2004, Artificial organs.
[39] Tao Liu,et al. IMC-Based Control Strategy for Open-Loop Unstable Cascade Processes , 2005 .
[40] Dan Simon,et al. Evolutionary Optimization Algorithms , 2013 .
[41] Milan S. Matijevic,et al. A robust Smith predictor modified by internal models for integrating process with dead time , 2001, IEEE Trans. Autom. Control..
[42] C. D. Johnson,et al. Disturbance-Accommodating Control; An Overview , 1986, 1986 American Control Conference.
[43] Qing-Chang Zhong,et al. Control of integral processes with dead time. Part IV: various issues about PI controllers , 2006 .
[44] Jonathan W. Kimball,et al. Particle swarm optimization of high-frequency transformer , 2010, IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society.
[45] Murat Efe,et al. Stability of the Extended Kalman Filter When the States are Constrained , 2008, IEEE Transactions on Automatic Control.
[46] Kathleen M Jagodnik,et al. Optimization and evaluation of a proportional derivative controller for planar arm movement. , 2010, Journal of biomechanics.
[47] Tao Liu,et al. New modified Smith predictor scheme for integrating and unstable processes with time delay , 2005 .
[48] Evanghelos Zafiriou,et al. Robust process control , 1987 .
[49] B. Widrow,et al. Adaptive inverse control , 1987, Proceedings of 8th IEEE International Symposium on Intelligent Control.
[50] Julio E. Normey-Rico,et al. Dealing with noise in unstable dead-time process control , 2010 .
[51] Eduardo F. Camacho,et al. A unified approach to design dead-time compensators for stable and integrative processes with dead-time , 2002, IEEE Trans. Autom. Control..
[52] Yoshikazu Fukuyama,et al. A particle swarm optimization for reactive power and voltage control in electric power systems , 1999, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).
[53] Ibrahim Kaya,et al. Obtaining Controller Parameters for a New PI-PD Smith Predictor Using Autotuning , 2003 .
[54] Milos R. Popovic,et al. Functional Electrical Stimulation. , 2006, Artificial organs.
[55] Xiao-Feng Xie,et al. DEPSO: hybrid particle swarm with differential evolution operator , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).
[56] Pedro Albertos,et al. Robust tuning of a generalized predictor-based controller for integrating and unstable systems with long time-delay , 2013 .
[57] Chang-Chieh Hang,et al. A modified Smith predictor for a process with an integrator and long dead time , 2003 .
[58] Ian Postlethwaite,et al. Multivariable Feedback Control: Analysis and Design , 1996 .
[59] V. Dietz,et al. Transcutaneous functional electrical stimulation for grasping in subjects with cervical spinal cord injury , 2005, Spinal Cord.
[60] R. Eberhart,et al. Comparing inertia weights and constriction factors in particle swarm optimization , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).
[61] P. Vadstrup,et al. Parameter identification of induction motors using differential evolution , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..
[62] Rainer Storn,et al. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..
[63] Brian A. Garner,et al. Estimation of Musculotendon Properties in the Human Upper Limb , 2003, Annals of Biomedical Engineering.
[64] J. Bobet,et al. Can muscle models improve FES-assisted walking after spinal cord injury? , 1998, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.
[65] ChangKyoo Yoo,et al. Enhanced control of integrating cascade processes with time delays using modified Smith predictor , 2010 .
[66] Zhiqiang Gao,et al. On the centrality of disturbance rejection in automatic control. , 2014, ISA transactions.
[67] P. Crago,et al. Electrically stimulated elbow extension in persons with C5/C6 tetraplegia: a functional and physiological evaluation. , 2000, Archives of physical medicine and rehabilitation.
[68] Leonard A. Gould,et al. Analytical design of linear feedback controls , 1957 .
[69] C. C. Hang,et al. A new Smith predictor for controlling a process with an integrator and long dead-time , 1994, IEEE Trans. Autom. Control..
[70] Bao-Zhu Guo,et al. On the convergence of an extended state observer for nonlinear systems with uncertainty , 2011, Syst. Control. Lett..
[71] Zhiqiang Gao,et al. On Validation of Extended State Observer Through Analysis and Experimentation , 2012 .
[72] Hassan K. Khalil,et al. Closed-Loop Behavior of a Class of Nonlinear Systems Under EKF-Based Control , 2007, IEEE Transactions on Automatic Control.
[73] Richard Bellman,et al. ON THE APPLICATION OF THE THEORY OF DYNAMIC PROGRAMMING TO THE STUDY OF CONTROL PROCESSES , 1956 .
[74] José García-Nieto,et al. Particle swarm hybridized with differential evolution: black box optimization benchmarking for noisy functions , 2009, GECCO '09.
[75] Maurice Clerc,et al. The particle swarm - explosion, stability, and convergence in a multidimensional complex space , 2002, IEEE Trans. Evol. Comput..
[76] Bruce A. Francis,et al. The internal model principle of control theory , 1976, Autom..
[77] P.E. Crago,et al. Functional restoration of elbow extension after spinal-cord injury using a neural network-based synergistic FES controller , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[78] C.E. Shannon,et al. Communication in the Presence of Noise , 1949, Proceedings of the IRE.
[79] Sybert H. Stroeve,et al. Learning combined feedback and feedforward control of a musculoskeletal system , 1996, Biological Cybernetics.
[80] J Esnouf,et al. The functional impact of the Freehand System on tetraplegic hand function. Clinical Results , 2002, Spinal Cord.
[81] Donald C. Wunsch,et al. Modeling of gene regulatory networks with hybrid differential evolution and particle swarm optimization , 2007, Neural Networks.
[82] R. Bellman. The theory of dynamic programming , 1954 .
[83] Yoichi Hori,et al. Robust speed control of DC servomotors using modern two degrees-of-freedom controller design , 1991 .
[84] J J Abbas,et al. New control strategies for neuroprosthetic systems. , 1996, Journal of rehabilitation research and development.
[85] Ning Lan,et al. Analysis of an optimal control model of multi-joint arm movements , 1997, Biological Cybernetics.
[86] R. E. Kalman,et al. When Is a Linear Control System Optimal , 1964 .
[87] Su Whan Sung,et al. Modified Smith Predictors for Integrating Processes: Comparisons and Proposition , 2001 .