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remember me password recovery I I accept acceptThe Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser. Polski EnglishLogin or register account Abstract 10.1007/BFb0030998Copyright owner: Springer-Verlag London Limited, 1995Data set: Springer Source Lecture Notes in Control and Information SciencesThis book outlines a new approach to constructing optimal feedback controls for linear control systems that are under the influence of constantly acting bounded perturbations. The optimal synthesis problem is solved by using discrete time systems obtained from continuous ones. Feedback and output feedback are also examined within this context. In cases where only incomplete or imprecise data are available, algorithms for optimal estimators as well as algorithms of optimal identifiers are described. Algorithms for optimal controllers are also constructed. An algorithm for optimal stabilization by bounded controls is also proposed whilst the Appendix of the book contains the outline of the adaptive method of programming which is the foundation for the approach used in the rest of the book. Identifiersseries ISSN : 0170-8643 series e-Emergent properties of optimal feedback control Although our work was motivated by the variability patterns observed in redundant tasks, the optimal feedback controllers. although weaker effect is observed in X2 and X4 for M = 5, but not for M = 2 and M = 4). More importantly, X2 is not really ‘frozen.’ Advanced Process Control Systems: Optimal Feedback Design Tools and Case Studies. State-Space Dynamic Process Models. Linear Dynamic Models. The linear state-variable equations are given by x& = Ax + Bu. Optimal control design algorithms using the Riccati equation are well known. Good design algorithms for the Linear Quadratic Regulator (LQR) are available in MATLAB Control systems Toolbox and elsewhere. The structure and design procedure for the LQR is shown in the figure. We develop an optimal feedback control model and explain complex object interactions as a simple trade-off between effort and task accuracy. Optimal Control Predicts Human Performance on Objects with Internal Degrees of Freedom. Arne J. Nagengast, Daniel A. Braun Terms of service Accessibility options Report an error / abuse