Robust Adaptive Cerebellar Model Articulation Controller for 1-DOF Nonlaminated Active Magnetic Bearings

This paper presents a robust adaptive cerebellar model articulation controller (RACMAC) for 1-DOF nonlaminated active magnetic bearings (AMBs) to achieve desired positions for the rotor using a robust sliding mode control based. The dynamic model of 1-DOF nonlaminated AMB is introduced in fractional order equations. However, it is challenging to design a controller based on the model\u27s parameters due to undefined components and external disturbances such as eddy current losses in the actuator, external disturbance, variant parameters of the model while operating. In order to tackle the problem, RACMAC, which has a cerebellar model to estimate nonlinear disturbances, is investigated to resolve this problem. Based on this estimation, a robust adaptive controller that approximates the ideal and compensation controllers is calculated. The online parameters of the neural network are adjusted using Lyapunov\u27s stability theory to ensure the stability of system. Simulation results are presented to demonstrate the effectiveness of the proposed controller.The simulation results indicate that the CMAC multiple nonlinear multiple estimators are close to the actual nonlinear disturbance value, and the effectiveness of the proposed RACMAC method compared with the FOPID and SMC controllers has been studied previously

Iterative Learning Control for V-Shaped Electrothermal Microactuator

The paper introduces a modified version of a Proportional Integral Derivative (PID)-type iterative learning algorithm, which is very simple to implement on a digital control device for tracking control of a continuous-time system. The simulative application of it is for controlling a V-shaped electrothermal microactuator (VEM) and is carried out by using a Simscape model of VEM for the purpose that the asymptotic tracking behavior of system output to desired trajectory will be verified in a virtually real environment. Obtained simulation results confirm that the introduced iterative learning algorithm has not only provided a good output tracking behavior, as expected, but also is robust in the sense of reducing external disturbance effects

Inversed Model-Based Disturbance Observer Base on Adaptive Fast Convergent Sliding Mode Control and Fixed-Time State Observer for Slotless Self-Bearing Motor

The slotless self-bearing motor (SSBM) is a motor with its self-bearing function. The mechanical structure of the motor is six symmetrical hexagonal shapes. The main control problem for this motor is disturbance and uncertainty rejection. Therefore, this paper proposes a new disturbance observer (DOB) based on an optimal fixed-time state observer (OFTSOB) and adaptive sliding mode control (SMC) for the motor. Firstly, the optimal state observer was used to construct to obtain the information of the states of the bearing-less motor system. Second, a new disturbance observer base on the fast speed reaching law is proposed for estimating the unknown dynamics and unpredicted uncertainty of the motor system. Third, the adaptive fast-reaching law-sliding mode control is designed to control the positions and rotational speed. Fourth, the proposed control system is proved via the Lyapunov theorem. Finally, the corrections of proposed method once again tested by using MATLAB simulation. The obtained results figured out that the proposed method is good at rejection disturbance and uncertainty and precision in control the movement and rotation. The novelties of the proposed method are that the gains of fixed-time observer were met by the support of optimal pole placement method, the disturbances were mostly rejected by a new reaching law of unknown input observer

Electrocardiogram Signal Secure Transmission via a Wireless Communication Protocol of Chaotic Systems Based on Adaptive Sliding Mode Control and Disturbance Observer

This paper presents a new application of the encryption and decryption techniques for securing the electrocardiogram (ECG) signal. The secure communication system (SCS) is embedded two Chen chaotic systems with different initial conditions, which were named master and slave, respectively. An ECG signal is encrypted by using master chaotic system. Which can be sent to the far destination to serving the heath care monitoring process. To obtain the original data, the state of the slave system is used to decrypt the signal. To obtain the goal, the master and slave need to be synchronized. Therefore, to softening the calculation of synchronization control design, the Takagi-Sugeno fuzzy (TSF) was used to remodel the master and slave into the fuzzy format, which are consists of the sublinear systems and fuzzy outer membership functions. Second, the disturbance observer (DOB) was proposed on slave system, which is used to reject the parameters variations and disturbances during the transmission. Third, the sliding mode control (SMC) was designed to synchronize the master and slave systems. Fourth, the stability of SCS is proved based on the Lyapunov condition. Finally, the simulation by using MATLAB software on computer and experiment by using the WIFI microchip ESP8266 were provided to show the power of the proposed methods

Robust Adaptive Cerebellar Model Articulation Controller for 1-DOF Nonlaminated Active Magnetic Bearings

This paper presents a robust adaptive cerebellar model articulation controller (RACMAC) for 1-DOF nonlaminated active magnetic bearings (AMBs) to achieve desired positions for the rotor using a robust sliding mode control based. The dynamic model of 1-DOF nonlaminated AMB is introduced in fractional order equations. However, it is challenging to design a controller based on the model's parameters due to undefined components and external disturbances such as eddy current losses in the actuator, external disturbance, variant parameters of the model while operating. In order to tackle the problem, RACMAC, which has a cerebellar model to estimate nonlinear disturbances, is investigated to resolve this problem. Based on this estimation, a robust adaptive controller that approximates the ideal and compensation controllers is calculated. The online parameters of the neural network are adjusted using Lyapunov's stability theory to ensure the stability of system. Simulation results are presented to demonstrate the effectiveness of the proposed controller.The simulation results indicate that the CMAC multiple nonlinear multiple estimators are close to the actual nonlinear disturbance value, and the effectiveness of the proposed RACMAC method compared with the FOPID and SMC controllers has been studied previously

A Novel Disturbance Rejection Method Based on Robust Sliding Mode Control for the Secure Communication of Chaos-Based System

This paper mainly proposes a new disturbance observer (DO) for a secure communication system (SCS) of the chaos-based system (CBS). First, the fractional-order (FO) Chen chaotic system is remodeled by a Takagi–Sugeno (T–S) fuzzy system with the aim of softening in calculation. Second, the robust fixed-time was designed to synchronize two nonidentical chaotic systems. Third, a new disturbance observer was proposed to compensate for the disturbance and uncertainty of the secure communication system. Fourth, the proof of the proposed method based on Lyapunov condition together with simulation are given to illustrate the correctness and effectiveness of the proposed theory. The tested disturbance on the public channel was mostly compensated by the appropriately estimated disturbance value. The states of master and slave systems (MSSs) were closed to each other in fixed-time. These factors are used to confirm that the symmetry of two chaotic systems were obtained by the proposed control methods