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Nonholonomic Systems (nonholonomic + system)
Selected AbstractsApplications of Sinusoidal Neural Network and Momentum Genetic Algorithm to Two-wheel Vehicle Regulating ProblemIEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, Issue 1 2008Duong Chau Sam Non-member Abstract In an attempt to enhance the performance of neural network (NN), we propose a sinusoidal activation function for NN and apply a fast genetic algorithm (GA) with uses of momentum offspring (MOS) and constant-range mutation (CRM) for training the NN. The proposed methods are aimed at designing a neurocontroller (NC) for regulating a two-wheel vehicle system, known as nonholonomic system, in the viewpoint that it is necessary to improve the control process of the system even though several control methods, including applications of NN and GAs, have been developed. The learning performances of NCs are evaluated through the successful evolutionary rates of the control process based on the values of the squared errors. In order to compare the conventional methods with our proposed approaches and verify the effects of momentum GA on NC training, various numerical simulations will be carried out with different numbers of generations in GAs and different activation functions of NCs. Finally, the controllability of NC is investigated with certain sets of initial states. The simulations show that sinusoidal NC trained by momentum GA has a good performance regardless of the small values of population size and generations in GA. Copyright © 2007 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [source] Discontinuous feedbacks, discontinuous optimal controls, and continuous-time model predictive controlINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 3-4 2003Fernando A. C. C. Fontes Abstract It is known that there is a class of nonlinear systems that cannot be stabilized by a continuous time-invariant feedback. This class includes systems with interest in practice, such as nonholonomic systems, frequently appearing in robotics and other areas. Yet, most continuous-time model predictive control (MPC) frameworks had to assume continuity of the resulting feedback law, being unable to address an important class of nonlinear systems. It is also known that the open-loop optimal control problems that are solved in MPC algorithms may not have, in general, a continuous solution. Again, most continuous-time MPC frameworks had to artificially assume continuity of the optimal controls or, alternatively, impose some demanding assumptions on the data of the optimal control problem to achieve the desired continuity. In this work we analyse the reasons why traditional MPC approaches had to impose the continuity assumptions, the difficulties in relaxing these assumptions, and how the concept of ,sampling feedbacks' combines naturally with MPC to overcome these difficulties. A continuous-time MPC framework using a strictly positive inter-sampling time is argued to be appropriate to use with discontinuous optimal controls and discontinuous feedbacks. The essential features for the stability of such MPC framework are reviewed. Copyright © 2003 John Wiley & Sons, Ltd. [source] Adaptive robust stabilization of dynamic nonholonomic chained systemsJOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 3 2001S. S. Ge In this article, the stabilization problem is investigated for dynamic nonholonomic systems with unknown inertia parameters and disturbances. First, to facilitate control system design, the nonholonomic kinematic subsystem is transformed into a skew-symmetric form and the properties of the overall systems are discussed. Then, a robust adaptive controller is presented in which adaptive control techniques are used to compensate for the parametric uncertainties and sliding mode control is used to suppress the bounded disturbances. The controller guarantees the outputs of the dynamic subsystem (the inputs to the kinematic subsystem) to track some bounded auxiliary signals which subsequently drive the kinematic subsystem to the origin. In addition, it can also be shown all the signals in the closed loop are bounded. Simulation studies on the control of a unicycle wheeled mobile robot are used to show the effectiveness of the proposed scheme. © 2001 John Wiley & Sons, Inc. [source] Stabilization of uncertain chained nonholonomic systems using adaptive output feedback,ASIAN JOURNAL OF CONTROL, Issue 6 2009Z. P. Yuan Abstract In this paper, adaptive output feedback control is presented to solve the stabilization problem of nonholonomic systems in chained form with strong nonlinear drifts and uncertain parameters using output signals only. The objective is to design adaptive nonlinear output feedback laws which can steer the closed-loop systems to globally converge to the origin, while the estimated parameters remain bounded. The proposed systematic strategy combines input-state scaling with backstepping technique. Motivated from a special case, adaptive output feedback controllers are proposed for a class of uncertain chained systems. The simulation results demonstrate the effectiveness of the proposed controllers. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [source] SINGULARITY COMPUTATION FOR ITERATIVE CONTROL OF NONLINEAR AFFINE SYSTEMSASIAN JOURNAL OF CONTROL, Issue 2 2000Dan O. Popa ABSTRACT This paper considers a gradient type of iterative algorithm applied to the open loop control for nonlinear affine systems. The convergence of the algorithm relies on the control signal in each iteration be nonsingular. We present an algorithm for computing the singular control for a general class of nonlinear affine systems. Various nonlinear mechanical systems, including nonholonomic systems, are included as examples. [source] | ||||||||||