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Feedforward Control (feedforward + control)
Selected AbstractsStochastic stability of a neural-net robot controller subject to signal-dependent noise in the learning ruleINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 6 2010Abraham K. Ishihara Abstract We consider a neural network-based controller for a rigid serial link manipulator with uncertain plant parameters. We assume that the training signal to the network is corrupted by signal-dependent noise. A radial basis function network is utilized in the feedforward control to approximate the unknown inverse dynamics. The weights are adaptively adjusted according to a gradient descent plus a regulation term (Narendra's e -modification). We prove a theorem that extends the Yoshizawa D-boundedness results to the stochastic setting. As in the deterministic setting, this result is particularly useful for neural network robot control when there exists bounded torque disturbances and neural net approximation errors over a known compact set. Using this result, we establish bounds on the feedback gains and learning rate parameters that guarantee the origin of the closed-loop system is semi-globally, uniformly bounded in expected value. Copyright © 2009 John Wiley & Sons, Ltd. [source] Adaptive model predictive control for co-ordination of compression and friction brakes in heavy duty vehiclesINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 10 2006Ardalan Vahidi Abstract In this paper, an adaptive model predictive control scheme is designed for speed control of heavy vehicles. The controller co-ordinates use of compression brakes and friction brakes on downhill slopes. Moreover, the model predictive controller takes the actuator constraints into account. A recursive least square scheme with forgetting is used in parallel with the controller to update the estimates of vehicle mass and road grade. The adaptation improved the model predictive controller. Also online estimation of the road grade enhanced the closed-loop performance further by contributing through feedforward control. Simulations of realistic driving scenarios with a validated longitudinal vehicle model are used throughout this paper to illustrate the benefits of co-ordinating the two braking mechanisms and influence of unknown vehicle mass and road grade. Copyright © 2006 John Wiley & Sons, Ltd. [source] Robust ,2 -gain feedforward control of uncertain systems using dynamic IQCsINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 11 2009I. E. Köse Abstract We consider the problem of robust ,2 -gain disturbance feedforward control for uncertain systems described in the standard LFT form. We use integral quadratic constraints (IQCs) for describing the uncertainty blocks in the system. For technical reasons related to the feedforward problem, throughout the paper, we work with the duals of the constraints involved in robustness analysis using IQCs. We obtain a convex solution to the problem using a state-space characterization of nominal stability that we have developed recently. Specifically, our solution consists of LMI conditions for the existence of a feedforward controller that guarantees a given ,2 -gain for the closed-loop system. We demonstrate the effectiveness of using dynamic IQCs in robust feedforward design through a numerical example. Copyright © 2008 John Wiley & Sons, Ltd. [source] The pathophysiology of tremorMUSCLE AND NERVE, Issue 6 2001Günther Deuschl MD Abstract Tremor is defined as rhythmic oscillatory activity of body parts. Four physiological basic mechanisms for such oscillatory activity have been described: mechanical oscillations; oscillations based on reflexes; oscillations due to central neuronal pacemakers; and oscillations because of disturbed feedforward or feedback loops. New methodological approaches with animal models, positron emission tomography, and mathematical analysis of electromyographic and electroencephalographic signals have provided new insights into the mechanisms underlying specific forms of tremor. Physiological tremor is due to mechanical and central components. Psychogenic tremor is considered to depend on a clonus mechanism and is thus believed to be mediated by reflex mechanisms. Symptomatic palatal tremor is most likely due to rhythmic activity of the inferior olive, and there is much evidence that essential tremor is also generated within the olivocerebellar circuits. Orthostatic tremor is likely to originate in hitherto unidentified brainstem nuclei. Rest tremor of Parkinson's disease is probably generated in the basal ganglia loop, and dystonic tremor may also originate within the basal ganglia. Cerebellar tremor is at least in part caused by a disturbance of the cerebellar feedforward control of voluntary movements, and Holmes' tremor is due to the combination of the mechanisms producing parkinsonian and cerebellar tremor. Neuropathic tremor is believed to be caused by abnormally functioning reflex pathways and a wide variety of causes underlies toxic and drug-induced tremors. The understanding of the pathophysiology of tremor has made significant progress but many hypotheses are not yet based on sufficient data. Modern neurology needs to develop and test such hypotheses, because this is the only way to develop rational medical and surgical therapies. © 2001 John Wiley & Sons, Inc. Muscle Nerve 24: 716,735, 2001 [source] Trajectory planning for boundary controlled parabolic PDEs with varying parameters defined on a parallelepipedPROCEEDINGS IN APPLIED MATHEMATICS & MECHANICS, Issue 1 2009Thomas Meurer The trajectory planning and feedforward tracking control problem is considered for a boundary controlled diffusion-reaction system with a spatially and time varying reaction parameter defined on a 3-dimensional parallelepiped. For this, an implicit state and input parametrization in terms of a basic output via a Volterra-type integral equation with operator kernel is determined, which is solved recursively by means of a series ansatz. The absolute and uniform convergence of the resulting series is verified by restricting the reaction parameter and the basic output to a certain but broad Gevrey class. Hence, assigning an admissible desired trajectory for the basic output directly yields the respective feedforward control, which is required to realize a desired spatio-temporal transition path. (© 2009 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] Robust iterative learning control design for batch processes with uncertain perturbations and initializationAICHE JOURNAL, Issue 6 2006Jia Shi Abstract A robust iterative learning control (ILC) scheme for batch processes with uncertain perturbations and initial conditions is developed. The proposed ILC design is transformed into a robust control design of a 2-D Fornasini,Marchsini model with uncertain parameter perturbations. The concepts of robust stabilities and convergences along batch and time axes are introduced. The proposed design leads to nature integration of an output feedback control and a feedforward ILC to guarantee the robust convergence along both the time and the cycle directions. This design framework also allows easy enhancement of the feedback and/or feedforward controls of the system by extending the learning information along the time and/or the cycle directions. The proposed analysis and design are formulated as matrix inequality conditions that can be solved by an algorithm based on linear matrix inequality. Application to control injection packing pressure shows the proposed ILC scheme and its design are effective. © 2006 American Institute of Chemical Engineers AIChE J, 2006 [source] | ||||||||||