Autonomous system (mathematics)

About: Autonomous system (mathematics) is a(n) research topic. Over the lifetime, 1648 publication(s) have been published within this topic receiving 38373 citation(s).

Learning from delayed rewards

Abstract: The invention relates to a circuit for use in a receiver which can receive two-tone/stereo signals. This circuit is intended to make a choice between mono or stereo reproduction of signal A or of signal B and vice versa. The circuit comprises two bistable multivibrator circuits which are controlled by a common, user-operable switch and by characteristic signals which are derived from the characteristic frequencies relevant to the different types of programs. The control is such that when the switch is operated only one bistable multivibrator circuit can be changed over (namely the bistable multivibrator circuit associated with the relevant characteristic frequency received.) A logic circuit which is controlled by the bistable multivibrator circuit as well as by the characteristic signals operates a change-over switch for switching to the desired reproduction.

Yet another chaotic attractor

Abstract: This Letter reports the finding of a new chaotic at tractor in a simple three-dimensional autonomous system, which resembles some familiar features from both the Lorenz and Rossler at tractors.

A new chaotic attractor coined

Abstract: This letter reports the finding of a new chaotic attractor in a simple three-dimensional autonomous system, which connects the Lorenz attractor and Chen's attractor and represents the transition from one to the other.

Predictive Active Steering Control for Autonomous Vehicle Systems

Abstract: In this paper, a model predictive control (MPC) approach for controlling an active front steering system in an autonomous vehicle is presented. At each time step, a trajectory is assumed to be known over a finite horizon, and an MPC controller computes the front steering angle in order to follow the trajectory on slippery roads at the highest possible entry speed. We present two approaches with different computational complexities. In the first approach, we formulate the MPC problem by using a nonlinear vehicle model. The second approach is based on successive online linearization of the vehicle model. Discussions on computational complexity and performance of the two schemes are presented. The effectiveness of the proposed MPC formulation is demonstrated by simulation and experimental tests up to 21 m/s on icy roads

Cooperative Control of Dynamical Systems: Applications to Autonomous Vehicles

Abstract: In this paper, a new framework based on matrix theory is proposed to analyze and design cooperative controls for a group of individual dynamical systems whose outputs are sensed by or communicated to others in an intermittent, dynamically changing, and local manner. In the framework, sensing/communication is described mathematically by a time-varying matrix whose dimension is equal to the number of dynamical systems in the group and whose elements assume piecewise-constant and binary values. Dynamical systems are generally heterogeneous and can be transformed into a canonical form of different, arbitrary, but finite relative degrees. Utilizing a set of new results on augmentation of irreducible matrices and on lower triangulation of reducible matrices, the framework allows a designer to study how a general local-and-output-feedback cooperative control can determine group behaviors of the dynamical systems and to see how changes of sensing/communication would impact the group behaviors over time. A necessary and sufficient condition on convergence of a multiplicative sequence of reducible row-stochastic (diagonally positive) matrices is explicitly derived, and through simple choices of a gain matrix in the cooperative control law, the overall closed-loop system is shown to exhibit cooperative behaviors (such as single group behavior, multiple group behaviors, adaptive cooperative behavior for the group, and cooperative formation including individual behaviors). Examples, including formation control of nonholonomic systems in the chained form, are used to illustrate the proposed framework.