Fault tolerant control based on interval type-2 fuzzy sliding mode controller for coaxial trirotor aircraft

Trajectory tracking control of a coaxial rotor drone: Time-delay estimation-based optimal model-free fuzzy logic approach

This paper proposes a control algorithm for controlling the position and attitude of a coaxial rotor drone without knowing the model dynamics. To overcome the major drawback of model-dependent approaches, an optimal model-free fuzzy controller (OMFFC) based on the estimation of the unknown dynamic function of the system is proposed. A time-delay estimation (TDE) technique is effectively exploited to approximate the unknown dynamic function of the system. The estimation error is then offset using a robust adaptive fuzzy logic compensator. Based on Lyapunov stability arguments, the global asymptotic stability of the coaxial rotor drone system is proven. Moreover, a flower pollination-based algorithm is also proposed to generate the optimal parameters to address the trade-off between optimal tracking performance and the design conditions related to the closed-loop stability requirements. The numerical simulations illustrate how the proposed methodology leads to the best performance, as well as less computational complexity compared to the standard proportional-integral-derivative and time-delay estimation-based controllers in the presence of external disturbances.

A Novel Nonsingular Terminal Sliding Mode Control-Based Double Interval Type-2 Fuzzy Systems: Real-Time Implementation

Extensive use of wind turbine (WT) systems brings remarkable challenges to the stability and safety of the power systems. Due to the difficulty and complexity of modeling such large plants, the model-independent strategies are preferred for the control of the WT plants which eliminates the need to model identification. This current work proposes a novel model-independent control methodology in the rotor side converter (RSC) part to ameliorate low voltage ride through (LVRT) ability especially for the doubly-fed induction generator (DFIG) WT. A novel model-independent nonsingular terminal sliding mode control (MINTSMC) was developed based on the principle of the ultra-local pattern. In the suggested controller, the MINTSMC scheme was designed to stabilize the RSC of the DFIG, and a sliding-mode supervisor was adopted to determine the unknown dynamics of the proposed system. An auxiliary dual input interval type 2 fuzzy logic control (DIT2-FLC) was established in a model-independent control structure to remove the estimation error of the sliding mode observer. Real-time examinations have been carried out using a Real-Time Model in Loop (RT-MiL) for validating the applicability of the proposed model-independent control in a real-time platform. To evaluate the usefulness and supremacy of the MINTSMC based DIT2-FLC, the real-time outcomes are compared with outcomes of RSC regulated conventional PI controller and MINTSMC controller.

A Survey on Active Fault-Tolerant Control Systems

Faults and failures in the system components are two main reasons for the instability and the degradation in control performance. In recent decades, fault-tolerant control (FTC) approaches have been introduced to improve the resiliency of control systems against faults and failures. In general, FTC techniques are classified into active and passive approaches. This paper reviews fault and failure causes in control systems and discusses the latest solutions that are introduced to make the control system resilient.The recent achievements in fault detection and isolation (FDI) approaches and active FTC designs are investigated. Furthermore, a thorough comparison of several different aspects is conducted to understand the advantage and disadvantages of various FTC techniques to motivate researchers to further developing FTC and FDI approaches.

Particle swarm-based and neuro-based FOPID controllers for a Twin Rotor System with improved tracking performance and energy reduction

This paper examines two approaches in tuning fractional order proportional-integral-differential (FOPID) control named as neuro-based FOPID (NNFOPID) and particle swarm-based FOPID (PSOFOPID) for pitch control of a Twin Rotor Aerodynamic System (TRAS). For the neuro-based FOPID control, the innovations are the modification of output equation in the artificial neural network and the implementation of the Rectified Linear Unit (ReLU) activation function. The advantages of the proposed approach are a lighter network and the ability to tune more practical controller parameters without a deep knowledge of the system to achieve a satisfying pitch tracking response. As for the particle swarm-based FOPID control, the application of PSO with spreading factor algorithm is extended for tuning the FOPID controller gains and the innovation here is a new procedure in setting the initial search range. The important advantages of this proposed swarm-based algorithm are the avoidance of being trapped in local optima and reduction of the search area respectively. The performances of the proposed controllers are proven by extensive simulations and experimental verifications based on five standard criteria: square-wave characteristics, reference to disturbance ratio, evaluation time, energy consumption of the control signal and tracking performance. The performances of the proposed controllers are compared against an optimised PID control in three system conditions, namely Case I) without coupling effect and wind disturbance, Case II) with coupling effect only and Case III) with wind disturbance only. Together, this study finds that NNFOPID control offers an accurate system positioning by a 34% reduction in steady-state error with the lowest energy consumption and minimum evaluation time in Case II. In terms of the tracking performance and robustness for Case II, the superiority of PSOFOPID control is confirmed by a 27% reduction in the tracking error and the lowest oscillation value. The experimental results also validate the robustness and energy consumption of both controllers in Case III. It is envisaged that the proposed control designs can be very useful in tuning FOPID controller gains for high performance, low energy, and robust aerodynamics systems.

Underactuated robotics: A review

Underactuated robotics is an emerging research direction in the field of robotics. The control input of the underactuated robot is less than the degree of freedom of the system. It has the advantages of lightweight, low energy consumption, excellent performance, and broad development prospects. This article reviews the state of the art on underactuated robotics. On the basis of previous studies, this article takes the non-holonomic constraint equation as the entry point to classify and summarize underactuated robot and their common mechanisms. The controllability of underactuated robot is further discussed. The control flow of underactuated robot is described based on the open–closed control method. In the closed-loop control, the control method based on the fuzzy system is mainly used. Finally, the difficulties in the current research of underactuated robot are summarized, and the future research directions are prospected.

Backstepping Sliding Mode Controller Improved with Interval Type-2 Fuzzy Logic Applied to the Dual Star Induction Motor

This paper proposes Interval type-2 Fuzzy sliding mode controller based on Backstepping (IT2FBSMC), to control the speed of a dual star induction machine (DSIM), in order to get a robust performance machine. An appropriate control strategy based on the coupling of three methods (Backstepping, sliding mode and type-2 Fuzzy controller) is used to build a robust controller used to approximate the discontinuous control eliminating the chattering phenomenon and guaranteeing the stability of the machine. Moreover, it forces the rotor angular speed to follow a desired reference signal. The simulation results obtained using Matlab/Simulink behavior are presented and discussed. The obtained results show that the controller can greatly alleviate the chattering effect and enhance the robustness of control systems with high accuracy.

Optimal interval type-2 fuzzy fractional order super twisting algorithm: A second order sliding mode controller for fully-actuated and under-actuated nonlinear systems

In this paper, a novel interval type-2 fuzzy fractional order super twisting algorithm (IT2FFOSTA) which is essentially a second order sliding mode controller is presented. The proposed IT2FFOSTA enhances fractional order super twisting algorithm (FOSTA) by taking advantage of an interval type-2 fuzzy fractional order sliding surface (IT2FFOSS) for some classes of fully-actuated and under-actuated nonlinear systems in presence of uncertainty. The FOSTA significantly reduces the amount of chattering and the IT2FFOSS results in decreasing the tracking error, control effort, and chattering level. In order to control under-actuated systems, a hierarchical sliding surface is employed. The multi-tracker optimization algorithm is utilized to adjust the controller's parameters; this leads to an optimal performance for the IT2FFOSTA. To examine the performance of the IT2FFOSTA, some simulation and experimental tests on three examples of different classes of fully-actuated and under-actuated systems, including ball and plate, inverted pendulum, and ball and beam systems are carried out. The simulation and experimental results demonstrate the superiority of the IT2FFOSTA in reducing the amount of chattering, tracking error, and control effort compared to those of the other control methods.

Smart greenhouse fuzzy logic based control system enhanced with wireless data monitoring

Greenhouse climate control is complicated procedure since the number of variables involved on it and which are dependent on each other. This paper presents a contribution to integrate greenhouse inside climate key's parameters, leading to promote a comfortable micro-climate for the plants growth while saving energy and water resources. A smart fuzzy logic based control system was introduced and improved through specific measure to the temperature and humidity correlation. As well, the system control was enhanced with wireless data monitoring platform for data routing and logging, which provides real time data access. The proposed control system was experimentally validated. The efficiency of the system was evaluated showing important energy and water saving.