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This paper presents the design of a novel continuous robust controller for a nonholonomic mobile manipulator in the task space. The main objective of the designed controller is to compensate for the disturbance caused by an unknown time-varying input delay, while the end-effector of the manipulator accurately tracks the reference position trajectory. Notably, the designed robust controller is model-independent; thus, it does not rely on the nominal values of dynamic parameters. Moreover, the control development considers the uncertainties in the parameters of the mobile manipulator dynamics via an unknown time-varying additive disturbance in the dynamics. To guarantee the uniformly ultimate boundedness of the tracking error, the paper utilizes a novel Lyapunov-based stability analysis incorporating Lyapunov–Krasovskii functionals. The effectiveness of the designed controller for a mobile manipulator, composed of a differential drive mobile platform and a two-degree-of-freedom robot manipulator, has been confirmed via simulation results.

In the current era, renewable energy has emerged as a vital alternative to fossil fuels, driven by the repercussions of global warming and the depleting supply of fossil fuels. Among these alternative energies, wind energy is particularly noteworthy due to its minimal greenhouse gas emissions, cost-effectiveness, and widespread availability. Nonetheless, achieving efficient extraction of wind energy requires precise control of wind turbine operations to optimize power generation. This involves the utilization of different maximum power point tracking (MPPT) algorithms. This review paper extensively examines a variety of MPPT algorithms, classifying them into four main categories: indirect power control (IPC) algorithm, direct power control (DPC) algorithm, hybrid algorithm, and intelligent algorithm control techniques. The review explores the performance of conventional IPC and DPC algorithms, discussing and comparing them with modified conventional methods. Additionally, the hybrid approach, combining multiple MPPT algorithms to leverage benefits while mitigating drawbacks, is examined. Intelligent MPPT algorithms are discussed both independently and in hybrid configurations. The paper introduces a hybrid fractional-order intelligent MPPT algorithm, offering a detailed discussion and comparison with other intelligent algorithms. A meticulous comparison is conducted based on key parameters such as adaptability, computational complexity, efficiency, oscillation, overall expense, robustness, speed of convergence, storage, time response, wind speed measurement, and wind turbine characteristics. Acknowledging the exponential growth in wind energy systems and their increasing significance, this review paper aims to be an indispensable and technically advanced reference for future studies in the dynamic domain of MPPT algorithm control techniques for wind energy systems.