In this paper, we deal with a control problem of 4-wheeled mobile vehicle that is a typical example of nonholonomic systems. We introduce a coordinates transformation that is valid for almost all state to have a chained form like system. To control the derived system, we transform it again to a hybrid time-state form, which has a non-decreasing variable as a time axis and the order part is a switched linear controllable system with a binary discrete variable. We propose a simple control scheme described by hybrid automata to control the system to the origin and extend the control scheme to restrict the behavior of a state variable by a supervisory controller.
We propose a rate based flow control method in single-bottleneck communication networks in order to suppress a transient behavior of a queue length at a bottleneck node when a number of connections change. Although the existing feedback control algorithms easily guarantee stability of the queue length of the bottleneck node, it is difficult to suppress oscillations of the length caused by abrupt changes of the number of connections. The proposed method incorporated with feedback control adopts a bias adjustment and a feedforward compensation. The control input is applied in accordance with the detection of the change of connections. In addition, the feedforward control input is designed to optimally improve the transient responses of the queue length.
We present a new approach for the swing-up and stabilizing control of the Acrobot, a planar, two-link, underactuated robot which is used for illustrating nonlinear control techniques. We develop a swing-up control stratgy based on a nonnegative function like the mechanical energy of the Acrobot. The swing-up controller is designed with a servo system that consists of a 2nd-order lag and a sinusoidal input obtained from the phase-plane trajectory of the center of mass of the Acrobot. The proposed balancing control law is a linear one designed by applying block control methods to the linearized model about an unstable equilibrium point, which can stabilize the whole system as keeping the amplitude of the 2nd joint angle small. Simulation results are given to show the performance of the controller.
In this paper, we develop two controllers to control simplified dynamic models of three unmanned aerial vehicles (UAVs) in formation. The formation control scheme is constructed in a hybrid system fashion, i.e., switching between two stable systems with state-dependent (collision-detection based) switching logic. Main Formation Controller (MFC) is designed based on Lyapunov direct method and integrator backstepping techniques playing the role of formation hold between two UAVs. Collision Avoidance Controller (CAC) gives benefit to the short range collision avoidance using polar coordinate instead of traditional relative model to capture motions between two UAVs. The proposed collision avoidance control uses the sliding mode control with better choices of sliding surfaces to effectively establish the desired collision avoidance behavior. Fusion of both controllers establishes stability and convergence to the reference formation by means of switching control. The numerical simulation results prove the validity of the proposed control scheme.
This paper considers vision-based motion control with the manipulator dynamics using position measurements and visual information, which we term dynamic visual feedback control. Firstly the visual feedback system of rigid body motion is described in order to derive the dynamic visual feedback system. Secondly we propose a dynamic visual feedback control law which guarantees local asymptotic stability of the overall closed-loop system using a Lyapunov function. L2-gain performance analysis for the proposed control law has been discussed using the energy function which plays the role of a storage function. Next, we show that the control law is based on passivity and the dynamic visual feedback system is constructed from two passive systems. Finally simulation results confirm the effectiveness of the dynamic visual feedback control law.
In this paper, an adaptive predistortion scheme is proposed to compensate nonlinearity of high power amplifiers (HPA) in OFDM systems. A complex Wiener model is adopted to describe the input-output relationship of HPA, where a linear dynamics is followed by a memoryless nonlinear static element approximated by using complex power series expression. In order to compensate the linear and nonlinear distortions in the HPA, a predistorter (PD) is constructed by directly adjusting a Hammerstein model which is an inverse of HPA. To update parameters of the PD, an efficient adaptive identification algorithm using real number calculation is given. Furthermore an adaptive algorithm updating the parameters in every one symbol-interval is also developed in the frequency-domain. The effectiveness of the proposed adaptive schemes is validated by numerical simulations treating HPA in 64QAM-OFDM transmitter.
This paper treats linear systems which include autonomous jumps of the state trajectories and investigates their basic properties. First, we derive a necessary and sufficient condition for the system to be well-posed in terms of an algebraic expression. Second, we give a condition that the system provides an invariant set, and show that a condition under which the origin is asymptotically stable in the invariant set can be reduced to LMIs. Finally, a numerical example is given to illustrate the effectiveness of the proposed analysis method.