this paper studies output Feedback control of pure-Feedback systems with immeasurable states and completely non-affine property. Since availability of all the states is usually impossible in the actual process, we assume that just the system output is measurable and the system states are not available. First, to estimate the immeasurable states a state observer is designed. Relatively fewer results have been proposed for pure Feedback systems because the cascade and non-affine properties of pure-Feedback systems make it difficult to find the explicit virtual controls and actual control. Therefore, by employing the singular perturbation theory in back-stepping control procedure, the virtual/actual control inputs are derived from the solutions of a series of fast dynamical equations which can avoid the “explosion of complexity’’ inherently existing in the conventional back-stepping design. The stability of the resulting closed-loop system is proved by Tikhonov’s theorem in the singular perturbation theory. Finally, the detailed simulation results are provided to demonstrate the effectiveness of the proposed controller, which can overcome the non-affine property of pure-Feedback systems with lower complexity and fewer design parameters.

In this paper, the total stability of specific fuzzy control systems is studied. The plant of the system is assumed to be a linear system and the fuzzy controller is of Sugeno type. The stability analysis is based on some newly developed theorems that guarantee sufficient conditions for the total stability of the system. The analysis results are applied to the stabilization problem of an unstable plant.

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.

Performance and improvement of flight efficiency at various velocities for flight systems, in particular, rotorcrafts, with specific complexities in motion and its nonlinear equations are always of particular interest to researchers in the aerial and control domains. In this research, a new control algorithm is addressed based on the complete nonlinear Unmanned Rotorcraft (UR) model and its four main inputs. Exploiting state Feedback and Polytopic Linear Parameter Varying (PLPV) modeling and using Linear Matrix Inequality (LMI), the velocity control problem is investigated. The trim points of the system are produced under different velocity control conditions. State Feedback control gain matrix which plays a main role in producing the ultimate control signal, is computed by solving a set of LMIs under various conditions. Finally, instead of using a Nonlinear model, a Polytopic model is used for controller synthesis. With this goal, different scenarios for the proposed flight velocity control (in different dynamic ranges, minimum velocity to maximum velocity) are implemented. The simulation results demonstrate a very good performance of the proposed controller in the basis of PLPV modelling. It can be concluded that the proposed manner is useful to overcome the disruptions imposed on the flight system due to the changes in the equilibrium points and the uncertainties of the parameters and/or possible errors due to the unwanted possibilities in the system.

Homogenous Charge Compression Ignition (HCCI) engines hold promise of high fuel efficiency and low emission levels for future green vehicles. But in contrast to gasoline and diesel engines, HCCI engines suffer from lack of having direct means to initiate combustion. A combustion timing controller with robust tracking performance is the key requirement to leverage HCCI application in production vehicles. In this paper, a two-state control-oriented model is developed to predict HCCI combustion timing for a range of engine operation. The experimental validation of the model confirms the accuracy of the model for HCCI control applications. An optimal integral state Feedback controller is designed to control the combustion timing by modulating the ratio of two fuels. Optimization methods are used in order to determine the controller’s parameters. The results demonstrate the designed controller can reach optimal combustion timing within about two engine cycles, while showing good robustness to physical disturbances.