This paper presents the modelling of a four rotor vertical take-off and landing (VTOL) unmanned air vehicle known as the quadrotor aircraft. The paper presents a new model design method for the flight control of an autonomous quad rotor. The paper describes the controller architecture for the quadrotor as well. The dynamic model of the quad-rotor, which is an under actuated aircraft with fixed four pitch angle rotors, will be described. The Modeling of a quadrotor vehicle is not an easy task because of its complex structure. The aim is to develop a model of the vehicle as realistic as possible. The model is used to design a stable and accurate controller. This paper explains the developments of a PID (proportional-integral-derivative) control method to obtain stability in flying the Quad-rotor flying object. The model has four input forces which are basically the thrust provided by each propeller connected to each rotor with fixed angle. Forward (backward) motion is maintained by increasing (decreasing) speed of front (rear) rotor speed while decreasing (increasing) rear (front) rotor speed simultaneously which means changing the pitch angle. Left and right motion is accomplished by changing roll angle by the same way. The front and rear motors rotate counter-clockwise while other motors rotate clockwise so that the yaw command is derived by increasing (decreasing) counter-clockwise motors speed while decreasing (increasing) clockwise motor speeds.

This paper presents an adaptive fuzzy sliding-mode controller (AFSMC) based on the boundary layer approach for speed control of an indirect field-oriented control (IFOC) of an induction motor (IM) drive. In general, the boundary layer approach leads to a tradeoff between control performances and chattering elimination. To improve the control performances, a fuzzy system is assigned as reaching control part of the fuzzy sliding-mode so that it eliminates the chattering completely in spite of the large uncertainties in the system. The applied fuzzy controller acts like a saturation function with a nonlinear slope inside thin boundary layer near the sliding surface to guarantee the stability of the system. Moreover, an adaptive law is implemented to estimate the unknown bound of uncertainty, which is obtained in the sense of Lyapunov stability theorem to minimize the control effort. The proposed AFSMC-based IM drive is implemented in real-time using DSP board TI TMS320F28335. The experimental and simulation results show the effectiveness of the proposed AFSMC-based IM drive at different operating conditions.

The nonlinear effect in the control system is so important and it may have a hard or soft effect on the electrical, mechanical, biological, and many other systems. This paper analyzes the describing function (DF) which is the transfer function of the nonlinear (NL) control systems of many NL elements found such as saturation, and backlash. The effect of the NL on the third-order delayed system is considered. The PID controller is considered the heart of the control system and continuously finds the error between input and output, and formulates the desired signal for the actuator to control the plant. Experimental tanning of PID controller with the saturation NL as a case study with buffer Operation Amplifier (Op-Amp) to maintain the gain and phase shift. In addition, a low pass filter (LPF) is used in the feedback to minimize and attenuate the effect of the NL in the closed-loop control system. The Fourier series is used to analyze the DF. The results show the effectiveness of the proposed algorithm.

Fault Tolerant Control (FTC) systems are crucial in industry to ensure safe and reliable operation, especially of motor drives. This paper proposes the use of multiple controllers for a FTC system of an induction motor drive, selected based on a switching mechanism. The system switches between sensor vector control, sensorless vector control, closed-loop voltage by frequency (V/f) control and open loop V/f control. Vector control offers high performance, while V/f is a simple, low cost strategy with high speed and satisfactory performance. The faults dealt with are speed sensor failures, stator winding open circuits, shorts and minimum voltage faults. In the event of compound faults, a protection unit halts motor operation. The faults are detected using a wavelet index. For the sensorless vector control, a novel Boosted Model Reference Adaptive System (BMRAS) to estimate the motor speed is presented, which reduces tuning time. Both simulation results and experimental results with an induction motor drive show the scheme to be a fast and effective one for fault detection, while the control methods transition smoothly and ensure the effectiveness of the FTC system. The system is also shown to be flexible, reverting rapidly back to the dominant controller if the motor returns to a healthy state.

This article covers the latest fault-tolerant control system (FTCS) developments and applications. FTCSs aim to maintain stability, minimize performance degradation, and compensate for system component faults. These systems benefit from and mission-critical applications where service continuity is crucial. This article describes several sensor and actuator errors. Fault Tolerant Control (FTC) includes active, passive, and hybrid approaches and the latest design techniques. Finally, FTCS stability and reliability analysis and research gaps were reviewed. This study provides current and future FTCS researchers with the latest trends and applications. This study's contribution. System component failures and instability are two major causes of control performance decline. Fault-tolerant control, or FTC, was developed in recent decades to improve control system resiliency. Active and passive FTC techniques exist. This paper examines control system faults, failure causes, and the latest resilience solutions. Fault detection and isolation (FDI) and active fault tolerance control (FTC) advances were examined. Encouraging FTC and FDI research, a comprehensive comparison of several aspects is performed to understand the pros and cons of various FTC techniques.