Echo-state network based adaptive fuzzy sliding-mode consensus control scheme for nonlinear multi-agent systems with external disturbances.

In this paper, an adaptive fuzzy sliding-mode control (AFSMC) system is investigated for an islanded inverter to achieve a high-performance power supply. A sliding mode control (SMC) law is designed initially to obtain both the voltage tracking error and the current tracking error of the inverter involved, to realize both the output-voltage regulation and the current protection with global stability. Moreover, to deal with uncertainties in the practical inverter system without the chattering phenomenon, an adaptive fuzzy system embedded with a self-adjustive translation width is developed to replace the switch term of the SMC. In addition, the adaptation laws, derived from the Lyapunov stability theorem, adjust the AFSMC parameters online to guarantee optimal and robust performance. Furthermore, the superior control performance of the proposed AFSMC is verified by a numerical simulation in MATLAB, producing experimental results on the prototype in comparison with the conventional SMC.

The increasing use of nonlinear loads entails serious electrical energy quality problems in power grids. Active power filter could lead to significant improvement in harmonic compensation performance. In this paper, an adaptive second-order sliding mode fuzzy control based on linear feedback strategy for a three-phase active power filter is proposed to eliminate harmonics. This scheme is constituted by adaptive controller, second-order sliding mode controller, fuzzy controller, and linear feedback controller. The linear feedback controller can compensate the system’s nonlinearities and make the new system have a linear behavior between the input and output. Moreover, the second-order sliding mode controller could transfer the discontinuities in the controller and reduce system chattering. Simulation results illustrate the proposed controller has better performance compared with fuzzy control and adaptive sliding mode fuzzy control.

EP-based kinematic control and adaptive fuzzy sliding-mode dynamic control for wheeled mobile robots

In this article, we propose a contribution to the control of a doubly fed induction motor by sliding mode with adaptive fuzzy logic. The technique of vector-control by classical field oriented applied to the doubly fed induction motor (DFIM) with mechanical sensors made it possible to have performances comparable with that of the direct current motor. However, it very sensitive to the parametric variations of the machine. The regulation speed by a classical regulator (PI) presents disadvantages: Poor robustness against parametric uncertainties of modeling and no the considering of the disturbances and little degree of freedom for the regulation. Because this effect, several robust controls were proposed in the technical literature to ensure the decoupling of the currents of the DFIM in a reference (d, q) leading to calculate simplified correctors. Among them, the variable structure control by sliding mode. It uses algorithms of regulations which ensure the robustness of the behavior of the process compared to the parametric variations and disturbances. Also, the impact of regulators based on artificial intelligence techniques such as adaptive fuzzy sliding mode controller are studied. In terms of results obtained, good dynamic performance and robustness with respect to load disturbances and parametric variation has been observed.

Chattering-free higher order sliding mode controller with a high-gain observer for the load following of a pressurized water reactor

This paper suggests a new hybrid control strategy, called Optimal Type II Fuzzy Sliding Mode (OT2FSM) control scheme, to realize the control of general uncertain chaotic systems. The proposed controller not only guaranties the stability and robustness against the lumped uncertainties caused by unmodeled dynamics and external disturbances, but also can significantly reduce the control chattering inherent in conventional sliding mode control. In the proposed controller, a novel heuristic algorithm namely particle swarm optimization with random inertia weight (RNW–PSO) is employed. To achieve an optimal performance, the parameters of the proposed controller as well as the input and output membership functions are optimized simultaneously by RNW–PSO. The globally asymptotic stability of the closed-loop system is mathematically proved. To evaluate the performance of the proposed controller, the results are compared with those obtained by Optimal H-infinity Adaptive PID (OHAPID) controller and an optimal Type-2 fuzzy proportional integral derivative (OT2FPID), which are the latest researches in the problem in hand. Simulation results show the effectiveness of the OT2FSM controller.

An effective method, adaptive fuzzy sliding-mode (SM) PI Control to design full-bridge inverter is proposed in this paper. For practical applications, sliding mode control (SMC) with chattering phenomenon is a large hindrance. The modified model of the PI controller is built by the plant extension scheme, in order to relieve the chattering. Also, the fuzzy logic is applied to find the appropriate parameter values of the PI controller, and can adapt to plant parameter variations and external load disturbances. The proposed method has been realized for the actual full-bridge inverters controlled by DSP and CPLD. Simulation and experimental results of the closed-loop system show that the proposed method yields system performance improvement, such as low total harmonic distortion (THD), fast dynamic response, reduced steady-state error, and reduced chattering.

This article presents an original motion control strategy for robot manipulators based on the coupling of the inverse dynamics method with the so-called second-order sliding mode control approach. Using this method, in principle, all the coupling non-linearities in the dynamical model of the manipulator are compensated, transforming the multi-input non-linear system into a linear and decoupled one. Actually, since the inverse dynamics relies on an identified model, some residual uncertain terms remain and perturb the linear and decoupled system. This motivates the use of a robust control design approach to complete the control scheme. In this article the sliding mode control methodology is adopted. Sliding mode control has many appreciable features, such as design simplicity and robustness versus a wide class of uncertainties and disturbances. Yet conventional sliding mode control seems inappropriate to be applied in robotics since it can generate the so-called chattering effect, which can be destructive for the controlled robot. In this article, this problem is suitably circumvented by designing a second-order sliding mode controller capable of generating a continuous control law making the proposed sliding mode controller actually applicable to industrial robots. To build the inverse dynamics part of the proposed controller, a suitable dynamical model of the system has been formulated, and its parameters have been accurately identified relying on a practical MIMO identification procedure recently devised. The proposed inverse dynamics-based second-order sliding mode controller has been experimentally tested on a COMAU SMART3-S2 industrial manipulator, demonstrating the tracking properties and the good performances of the controlled system.

The angular velocity of the input link of a mechanism fluctuates due to the inertia of links and the external forces, although it is generally assumed constant in design. The control of the crank angular velocity of a four-bar mechanism driven by a DC motor by moving sliding mode control is considered in this study. A time-varying slope is proposed based on the error state. The mathematical model of the motor-mechanism system is derived using Eksergian’s equation of motion. First, the state space equations are solved numerically for constant motor voltage to show the velocity fluctuations of the crank. Then both the conventional sliding mode control method and the proposed moving sliding mode control method are applied to obviate this unwanted velocity fluctuation. The method is verified by numerical simulations as well as experimental studies. The results of both the sliding mode control and the moving sliding mode control methods are compared. It is shown that a moving sliding surface in the sliding mode control increases the robustness of conventional sliding mode control by decreasing the reaching time. Also, the performance of the moving sliding mode control against parametric variations and external disturbances is experimentally investigated by adding a mass and applying an unexpected force on one of the links of the mechanism.

In this paper a trajectory tracking control law for an arm manipulator of three degrees of freedom is developed using an adaptive fuzzy sliding mode control (AFSMC) with a proportional integral derivative (PID) sliding surface. The introduction of this controller in the control loop permits that the joints track the desired trajectory despite external disturbances. The developed control laws enable us to note that the trajectories tracking performances of the manipulator are directly related to the choice of the used adjustable parameter values. For that a genetic algorithm optimization is used for the determination of the PID surface parameters and the normalization gains of the fuzzy controllers. This approach allows us not only to force the behavior system to a desired state very fast, but makes also the torques functions smooth without chattering. The obtained results show an improvement of the trajectory tracking with this approach and implied that this strategy is feasible, effective and robust with regard to disturbances.

An indirect adaptive fuzzy sliding mode control scheme for a class of discrete-time systems with model uncertainty and external disturbance is developed. In this approach, a discrete-time exponential reaching law is used to obtain the ideal sliding mode control law. Then, two fuzzy systems and a third one are used to approximate unknown functions of the system and the switch-type control in the ideal control law, respectively, wherein the consequent parameters are adjusted by an on-line adaptation law with parameter projection. Towards to Tank pressurization system, experiment results have shown the effectiveness of the algorithm.

This paper tries to enhance the performance of torque, speed, and stator current of three-phase induction motor drive (IMD) using adaptive fuzzy sliding mode (AFSM) controllers. The direct torque control (DTC) of IMD is widely used in industry due to its simple operation, minimum response time, and robustness. Operation with Classical DTC using PI controller has difficulties with low operating speed and demerits like high noise level, high ripple in torque, and variable switching frequency. Therefore, to resolve these problems, space vector modulation (SVM) is implemented in classical DTC with PI controller. Further, PI controller is less effective to adapt the speed variations, load changes, and parameter variations that are established by using AFSM control. Therefore, fast speed response and good disturbance rejection are achieved. Much research has been done for AFSM speed controller based DTC IMD. But, in this paper, the DTC-SVM of IMD is developed using AFSM torque controller along with the speed controller and is simulated in MATLAB/Simulink platform. Further, the results are experimentally verified and are compared with that of PI controller based drive so as to show the superiority of the presented controller.

Fixed wing Unmanned Aerial Vehicles (FWUAVs) are widely utilized in both military and civilian sectors due to their ability to perform risky, inaccessible operations. The mathematical model of FWUAVs is complex, incorporating physical laws and coordinate systems with transformation matrices. In addition, controlling FWUAVs is challenging due to their nonlinear and coupled dynamics. This paper focuses on tracking trajectories for fixed wing unmanned aerial vehicles (FWUAVs) using a Robust Fractional Order Sliding Mode Controller (RFOSMC). An RFOSMC, which combines a conventional Sliding Mode Controller (SMC) with flexible fractional calculus, is proposed in this paper. Particle Swarm Optimization (PSO) is used to tune the control gains of RFOSMC. External disturbances and parameter variation are added to evaluate the controller’s performance. Comparative studies have been done with Linear Quadratic Regulator (LQR), Fractional Order PID (FOPID), SMC, and robust FOSMC. RFOSMC performs better than LQR, FOPID, and SMC in tracking accuracy, response speed, and overshoot. In addition, the performance comparison of RFOSMC and conventional SMC has been done based on performance index values of errors (ITAE), and RFOSMC showed a 76.5918% improvement. For a step input, RFOSMC showed the smallest settling time of 0.835s compared with 2.724s for SMC and 4.8573s for FOPID. Open-loop model verification and overall control system of FWUAV are done using MATLAB/Simulink software.

This paper proposed a sliding mode angle control with neural network estimator design for a fan-plate system. The neural network estimator is based on radial basis function and it estimates the unknown lumped bounded uncertainty of parameter variations and external disturbances in real-time. The abilities of anti-disturbance and anti-chattering are better than conventional sliding mode controller and adaptive sliding mode controller. The Lyapunov stability theorem is employed to ensure the stability of the proposed controller. The convergence and signal tracking properties are better than the conventional sliding mode controller. Finally, we employed the experiment to validate the proposed method is feasible.

This paper presents a conventional sliding mode control (SMC) and chattering free improved sliding mode control design strategy for nonlinear systems. In this paper, theoretical and mathematical concept of variable structure control (VSC) system and sliding mode control has been discussed. The modelling of conventional sliding mode controller as well as chattering free improved sliding mode controller for sample nonlinear equation and robotic vehicle located underwater, forming a single direction motion is the main motive of this paper. Chattering in conventional sliding mode controller can be easily removed by using continuous function in place of discontinuous sign function. The Lyapunov stability criterion is used for nonlinear system control giving a simple control algorithm. Simulation result depicts the feasibility and satisfactory performance of chattering free improved sliding mode control as compared to conventional sliding mode control.