This article investigates the problem of simultaneous attitude and vibration control of a flexible spacecraft to perform high precision attitude maneuvers and reduce vibrations caused by the flexible panel excitations in the presence of external disturbances, system uncertainties, and actuator faults. Adaptive integral sliding mode control is used in conjunction with an attitude actuator fault iterative learning observer (based on sliding mode) to develop an active fault tolerant algorithm considering rigid-flexible body dynamic interactions. The discontinuous structure of fault-tolerant control led to discontinuous commands in the control signal, resulting in chattering. This issue was resolved by introducing an adaptive rule for the sliding surface. Furthermore, the utilization of the sign function in the iterative learning observer for estimating actuator faults has not only enhanced its robustness to external disturbances through a straightforward design, but has also led to a decrease in computing workload. The strain rate feedback control algorithm has been employed with the use of piezoelectric sensor/actuator patches to minimize residual vibrations caused by rigid-flexible body dynamic interactions and the effect of attitude actuator faults. Lyapunov's law ensures finite-time overall system stability even with fully coupled rigid-flexible nonlinear dynamics. Numerical simulations demonstrate the performance and advantages of the proposed system compared to other conventional approaches.

A novel nonlinear controller is proposed to track active and reactive power for a Brushless Doubly-Fed Induction Generator (BDFIG) wind turbine. Due to nonlinear dynamics and the presence of parametric uncertainties and perturbations in this system, sliding mode control is employed. To generate a smooth control signal, dynamic sliding mode method is used. Uncertainties bound is not required in the suggested algorithm, since the adaptive gain in the controller relation is used in this study. Convergence of the sliding variable to zero and adaptive gain to the uncertainty bound are verified using Lyapunov stability theorem. The proposed controller is evaluated in a comprehensive simulation on the BDFIG model. Moreover, output performance of the proposed control algorithm is compared to the conventional and second-order sliding mode and proportional-integral-derivative (PID) controllers.

In this paper, a new guidance law for yaw channel of homing interceptors is designed. Because of using the sliding mode theory, the nonlinear equations of motion are used and the target acceleration is considered as an uncertainty. Therefore, the precise measuring or estimating of target acceleration is not required and only the upper bound of target maneuvers is used. A sliding surface is defined using the angle rate of the interceptor-target line of sight. For producing a smooth control signal and removing the chattering of the guidance commands, the discontinuous term of guidance law has been approximated with a continuous function. Adjusting the parameter of sliding term leads to decreasing the missile control effort, the time of flight and velocity loses. Simulation results in the presence of a real control system dynamics of a homing interceptor show the effectiveness and robustness of the designed guidance law against maneuvering target in comparison with the proportional navigation algorithm.

In this paper at first the chaotic behavior of a spur gear system is investigated by the use of numerical tools including phase plane trajectories, Poincare’ section and bifurcation diagrams. in order to eliminate the chaotic oscillations, a novel controller on the basis of the predictive sliding mode control is proposed in which the sliding surface is predicted using the model predictive control theory and the control input is obtained. The simulation results of the feedback system depict the effectiveness of the controller in elimination of the chaotic vibrations along with the reduction of settling time, overshoots, and energy consumption.

In this paper, an adaptive neuro fuzzy sliding mode based genetic algorithm (ANFSGA) control system is proposed for a pH neutralization system. In pH reactors, determination and control of pH is a common problem concerning chemical-based industrial processes due to the non-linearity observed in the titration curve. An ANFSGA control system is designed to overcome the complexity of precise control of pH. In the proposed control system the genetic algorithm is employed to do the crossover and mutation operation in adaptive neuro fuzzy inference system (ANFIS) mechanism. In this way, on-line learning ability is employed to deal with external disturbance by adjusting the control parameters.  The control objective is to drive the system state to the original equilibrium point or to track the set point.

modeling and control of Unmanned Aerial Vehicle is undoubtedly one of the most active areas in the field of control engineering. The characteristics of aerial vehicles such as nonlinear dynamics, time variability and the structural and parametric uncertainties make flight control issue relatively a complex and important subject in their design. One of the widely used methods in this area is sliding mode control technique. This paper proposes the design, the simulation, and the analysis of two controllers namely PID and sliding mode in order to optimally control the pitch angle of an unmanned aircraft. Initially, in order to dynamically model the system, an appropriate mathematical model is presented to describe the longitudinal motion of aircraft. Subsequently, a robust sliding mode controller is designed using particle swarm optimization (PSO) algorithm to control the pitch angle of an aircraft against the uncertainties and the external disturbances. The optimal parameters are determined by minimizing both the control signal and tracking error. Then, the performance quality of the proposed method was compared with the results of the optimal PID controller in terms of transient response characteristics. Finally, simulation results indicated that the proposed sliding mode controller can reduce the overshoot of system response and yield more robust performance than PID for the control of pitch angle.