The latest research on disturbance rejection mechanisms has shown active disturbance rejection control (ADRC) to be an effective controller for uncertainties and nonlinear dynamics embedded in systems to be controlled. The significance of the ADRC controller is its model-free nature, as it requires minimal knowledge of the system model. In addition, it can actively estimate and compensate for the impact of internal and external disturbances present, with the aid of its crucial subsystem called the extended state observer (ESO). However, ADRC controller design becomes more challenging owing to different system disturbances, such as output disturbances, measurement noise, and varying time-delays persistent in the system’s communication channels. Most disturbance rejection techniques aim to reduce internal perturbations and external disturbances (input and output disturbance). However, output disturbance rejection with measurement noise under time-delay control is still a challenging problem. This paper presents a novel predictive ESO-based ADRC controller for time-delay systems by employing predictive methods to compensate for the disturbances originating from time delay. The prediction mechanism of the novel (proposed) controller design is greatly attributed to the extended state predictor observer (ESPO) integrated with the delay-based ADRC inside the proposed controller method. Thus, the proposed controller can predict the unknown system dynamics generated during the delay and compensate for these dynamics via disturbance rejection under time-delay control. This approach uses the optimization mechanism to determine controller parameters, where the genetic algorithm (GA) is employed with the integral of time-weighted absolute error (ITAE) as the fitness function. The proposed controller is validated by controlling second-order systems with time delay. Type 0, Type 1, and Type 2 systems are considered as the controlled plants, with disturbances (unknown dynamics due to delay and external disturbance), along with measurement noise present. The proposed controller method is compared with state-of-the-art methods, such as the modified time-delay-based ADRC method and the ESPO-based controller method. The findings indicate that the method proposed in this paper outperforms its existing competitors by compensating for the dynamics during the time delay and shows robust behaviour, improved disturbance rejection, and a fair extent of resilience to noise.

Creating autonomous robots to assist humans in their daily activities has been one of the important innovations of robotic research. In this paper, a 2-dimensional movement platform of the haptic feedback interface for human machine systems is developed including DC motors and ball screws as the core components. The platform is inclusive in the complete haptic feedback teleoperation systems, which display remote sensing data to the operators in the forms of force and vibration. The remote objects/environment can be actual devices/machines or just computer simulations, such as virtual reality. The proposed platform helps to mimic various interactions between the concerned remote object and corresponding environment. Lagrange method is applied to model the mechanical-electrical system. The developed model is simulated and compared with the hardware platform. The time domain responses obtained from both mathematical models and platform validate the established prototype.

Lately, active disturbance rejection control (ADRC), a model-independent controller, has become popular for combating various forms of uncertain disturbances incurred in industrial applications. ADRC was validated for external disturbances, internal disturbances, and nonlinearities incurred under realistic scenarios. Time delay challenges all controllers, especially when it coexists with nonlinearities. This paper investigates the impacts of time delay and backlash-like hysteresis nonlinearity in ADRC-controlled systems. These impacts are analyzed, as in the case study, in two ADRC-based methods, namely the ADRC with delayed input method and the predictive extended state observer (PESO)-based ADRC (PESO-ADRC) method. To improve the system response and to attain a decent attenuation of uncertainties, the time-delay estimation (TDE) mechanism is introduced to the concerned ADRC-based methods. Experimental studies are conducted to verify the effectiveness and stability of the proposed TDE-ADRC methods. The results demonstrate the robustness and decent recovery of the transient response after the adverse impact of the backlash-like hysteresis on both concerned ADRC-controlled systems.

Nonlinearity and other existing uncertainties, such as time delay, are commonly found in systems involving realistic operations. Lately, the time-delay estimation (TDE) mechanism has been gaining popularity in various control theory-related fields concerning the compensation of uncertainties present in control systems. This paper examines the effects of nonlinear backlash-like hysteresis and system time delay using a proportional-integral-derivative (PID) controller, followed by introducing a TDE technique to a PID-controlled time-delay system. Experimental studies using simulation results are performed to validate the effectiveness of the proposed TDE-PID control method by emphasizing the estimation and attenuation of the nonlinearity effect present in a time-delay system. The results indicate an improved and robust transient system response under the impact of uncertainties like hysteresis and system disturbance present in a time-delay system. Further, the proposed TDE-PID control method is analysed for systems with varying time delays, and the simulation results further substantiate that the proposed method is effective. By considering various uncertainties, the proposed method can be used in different industrial applications, such as the frequency and voltage control in power systems.