Fangzheng Gao

Adaptive stabilization for a class of stochastic nonholonomic systems with nonlinear parameterization

In this paper, the adaptive stabilization problem is investigated for a class of stochastic nonholonomic systems in chained form with nonlinear parameterization. A parameter separation technique is introduced to transform the nonlinear parameterized nonholonomic system into a linear-like parameterized one. Then, using input-state-scaling and integrator backstepping techniques, an adaptive asymptotical control law is obtained. Based on switching strategy to eliminate the phenomenon of uncontrollability, the proposed controller could ensure that the state of closed-loop system is globally asymptotically regulated to zero in probability.

H ∞ control of networked control systems with stochastic time delay and packet dropout

This note is concerned with robust H∞ control of linear uncertain networked control systems with stochastic network induced delay and data packet dropout. The stochastic delay and data packet dropout are viewed as equivalent delay which is modeled as a binary switching sequence satisfying a interval Bernoulli distribution. A new approach is given to model the networked control systems. Based on the Lyapunov stability theory, and with the linear matrix inequality approach, a sufficient condition is presented for the existence of H∞ controller. With the H∞ controller, the networked control systems is exponentially mean-square stable. A numerical example is provided to demonstrate the validity of the proposed design approach.

Robust stabilization of nonholonomic systems with time delays

This paper investigates the problem of state-feedback stabilization for a class of nonholonomic systems in chained form with time delays. By using input-state-scaling technique and backstepping recursive approach, and choosing an appropriate Lyapunov-Krasoviskii functional, a state-feedback controller is constructed. Based on switching strategy to overcome the uncontrollability, global asymptotic regulation of the closed-loop system is achieved. A simulation example is provided to show the effectiveness of the proposed method.

Adaptive exponential regulation of nonlinearly parameterized chained form systems

This paper deals with nonholonomic systems in chained form with nonlinear parameterization. The objective is to design adaptive nonlinear state feedback laws such that the closed-loop systems are globally exponentially regulated at the origin, while the estimated parameters remain bounded. The systematic strategy combines the parameter separation, input-state-scaling technique and integrator backstepping procedure. The efficiency and feasibility of the proposed method are demonstrated by practical example.

Finite-time stabilization of high order nonholonomic systems in power chained form

In this paper, a finite-time control strategy is presented for a class of high order nonholonomic systems in power chained form with strong nonlinear drifts. The robust control laws are developed by the use of input-state-scaling and adding a power integrator backstepping technique. Based on switching strategy to overcome the uncontrollability problem associated with x0(0) = 0, the solution of the resulting closed-loop system is globally finite-time regulated at origin.

Adaptive finite-time stabilization of nonholonomic systems with nonlinear parameterization

In this paper, adaptive finite-time control is presented for a class of uncertain nonholonomic systems in chained form with nonlinear parameterization. Using parameter separation, state scaling and backstepping, an adaptive finite-time control law is obtained in the form of continuous time-invariant feedback. Both Lyapunov stability and finite time convergence are guaranteed by appropriately choosing the design parameters. An adaptive control based switching strategy is used to overcome the uncontrollability problem associated with x0 (0) = 0. Simulation example demonstrates the effectiveness and the robust features of the proposed controller.