This article deals with the design of an adaptive controller for Switched non-strict feedback nonlinear systems. In the studied system, the switching signal is arbitrary, the states are not measurable, and the signs of the control gain functions that describe the control directions are completely unknown. First, the unknown nonlinear functions in the Switched system are approximated using the universal approximation theorem. Then, the unmeasured states are estimated using the linear state observer, and the controller is designed through an adaptive back-stepping design procedure. Due to the appropriate change of coordinates, 1) neither fuzzy nor radial basis function is used in the design of the controller, 2) only one adaptation law is designed to estimate the unknown parameters in the Switched non-strict feedback nonlinear system, and 3) there is no Nussbaum function in the proposed adaptive controller so, the large control signal in the initial stages and the consequent damage to the actuators can be prevented. These features can lead to the simplicity of controller design and the reduction of computational burden. Therefore, the proposed method can be used for practical systems. The stability of the closed-loop system is proved using Lyapunov stability theory. It is shown that, in addition to the semi-globally uniformly ultimately boundedness of all closed loop signals, the tracking error converges to a small neighborhood around zero. In the end, the efficiency of the proposed control method is confirmed through the simulation results of an example.

This paper is concerned with developing an adaptive method on the basis of a nonlinear disturbance observer (NDO) in order to control a Switched nonlinear system in the presence of unknown functions and external disturbances, and under arbitrary switching signals. The proposed approach employs an adaptive backstepping technique, NDO, a fuzzy logic system (FLS), and the particle swarm optimization (PSO) algorithm. Based on a common Lyapunov function (CLF), the adaptive backstepping technique is used to design a nonlinear state-feedback controller. Also, NDO and FLS are stated to estimate the disturbances and the unknown nonlinear functions, respectively. In addition, to improve the performance of the closed-loop system, the PSO algorithm is used to optimize the controller parameters. Finally, simulation examples are taken into account to demonstrate the effectiveness of the proposed strategy.

In this paper, the problems of control and stabilization of Switched nonlinear cascade systems is investigated. The so called simultaneous domination limitation (SDL) is introduced in previous works to assure the existence of a common quadratic Lyapunov function (CQLF) for Switched nonlinear cascade systems. According to this idea, if all subsystems of a Switched system satisfy the SDL, a CQLF can be constructed by employing the back-stepping approach. The major shortcoming of the SDL is that this limitation cannot be satisfied for complicated Switched nonlinear systems. Therefore, a CQLF cannot be constructed by employing the back-stepping approach. Moreover, if SDL is satisfied, only stabilization problem can be solved. In this paper, a new approach based on state conversion is introduced to solve the stabilization and control problems of Switched nonlinear cascade systems without any limitation. Several simulation and experimental studies are provided to show the effectiveness of the proposed approach.

This paper presents robust optimal control of an uncertain nonlinear Switched system with forced subsystems. The uncertainties include external disturbance and parametric uncertainties. Switching signal and control input are designed to minimize a given cost function. Approximate dynamic programming (ADP) has been efficiently applied to certain Switched systems as an optimal control strategy. Since approximate dynamic programming method is model based, there would seem to be some difficulties to apply approximate dynamic programming to uncertain Switched system. To overcome these mentioned problems, this paper presents an appropriate model. In order to apply proposed control approach, robust time-delay controller is added with ADP control. At first uncertainties are compensated by robust time-delay controller. Then the switching signal and the control input are design by approximate dynamic programming that provides a feedback solution for unspecified initial conditions. The discussing boundedness of states and simulation results verify the effectiveness of the proposed control approach.