Johansen T A, Fossen T I, Berge S P. Constrained nonlinear control allocation with singularity avoidance using sequential quadratic programming[J]. IEEE Transactions on Control Systems Technology, 2004, 12(1): 211-216. Grudinin N. Reactive power optimization using successive quadratic programming method[J]. IEEE Transactions on Power Systems, 1998, 13(4): 1219-1225. Wang J, Zhang Y N. Recurrent neural network for real-time computation of inverse kinematics of redundant manipulators[M]. Machine Intelligence: Quo-Vadis? (eds: P. Sincak, J. Vascak, and K. Hirota), World Scientific, Singapore, 2004, 299-319. Leithead W E, Zhang Y N. O(N^2)-operation approximation of covariance matrix inverse in gaussian process regression based on Quasi-Newton BFGS method[J]. Communications in Statistics -- Simulation and Computation, 2007, 36(2): 367-380. Zhang Y N. Towards piecewise-linear primal neural networks for optimization and redundant robotics[C]//MengChu Zhou, Proceedings of IEEE International Conference on Networking, Sensing and Control, Florida: IEEE Press, 2006, 374-379. Zhang Y N, Ge S S, Lee T H. A unified quadratic programming based dynamical system approach to joint torque optimization of physically constrained redundant manipulators[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B, 2004, 34(5): 2126-2132. Zhang Y N, Wang J. A dual neural network for constrainted torque optimization of kinematically redundant manipulators[J]. IEEE Transactions on Systems, Man and Cybernetics, Part B, 2002, 32(5): 654-662. Zhang Y N, Wang J. Obstacle avoidance of kinematically redundant manipulators using a dual neural network[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part B, 2004, 34(1): 752-759. Powell M J D. A method for nonlinear constraints in minimization problems[M]. Optimization (ed: R. Fletcher), Academic Press, London, 1969. Hestens M R. Multiplier and Gradient Methods[J]. Journal of optimization theory and applicatuins, 1969, 4(5): 303-320. Fletcher R. A general quadratic programming algorithm[J]. IMA Journal of Applied Mathematics, 1971, 7(1): 76-91. Jin Z J, Bai Y Q, Han B S. A weighted-path-following interior-point algorithm for convex quadratic optimization[J]. Operations Research Transactions, 2010, 14(1): 55-65. Zhao S F, Fei P S, Li J. A projection and contraction method for convex quadratic programming[J]. Journal of Wuhan University, 2001, 47(1): 22-24. He B S. A new method for a class of linear variational inequalities[J]. Mathematical Programming, 1994, 66(1-3): 137-144. Zhang Y N. On the LVI-based primal-dual neural network for solving online linear and quadratic programming problems[C]//Suhada Jayasuriya, Proceedings of American Control Conference, Portland: IEEE Press, 2005, 1351-1356. Zhang Y N, Cai B H, Zhang L, Li K N. Bi-criteria velocity minimization of robot manipulators using a linear variational inequalityes-based primal-dual neural network and PUMA560 example[J]. Advanced Robotics, 2008, 22(13-14): 1479-1496. He B S. Solving a class of linear projection equations[J]. Numerische Mathematik, 1994, 68(1): 71-80. He B S. A projection and contraction method for a class of linear complementarity problem and its application in convex quadratic programming[J]. Applied Mathematics and Optimization, 1992, 25(3): 247-262. |