Hybrid nature-inspired optimization for stability and disturbance rejection in tethered unmanned aerial vehicles.

The study proposes a new hybrid optimization model that is intended to be used in the design of a high-level attitude control system to be applied in tethered Unmanned Aerial Vehicles (UAVs). The suggested solution is based on a Fractional-Order Proportional-Derivative-Integral (FOPDD-I) controller alongside a hybrid optimum algorithm that will be a fusion of Harris Hawks Optimization, the Eagle Strategy, and Particle Swarm Optimization (HHHO-ES-PSO). A systematic comparison of the optimized FOPDD-I controller performance with a number of benchmark control schemes is made, such as the Conventional PID, Cascade PID, classical Active Disturbance Rejection Control (ADRC), and Advanced ADRC. Extensive simulations with MATLAB indicate that the HHHO-ES-PSO-tuned FOPDD-I controller has a better dynamic behavior, which is characterized by higher stability, quicker transient response, and better disturbance rejection than the traditional ones. The quantitative results of optimization show an increase in the proportional gain (K_p) by 56.5% and in the integral (K_i) gain by 65.2% and a reduction in the derivative gain (K_d) by 98.4% effectively reducing the yaw overshoot and oscillatory behavior. In addition, the parameters of the fractional-order were also adjusted in an adaptive manner, which resulted in adaptability gains of 12.5% and 14.7% in nonlinear dynamic conditions. Conversely, traditional PID and Cascade PID controllers only offered small gains in tuning, whereas classical and improved ADRC methods demonstrated moderate, but relatively small, gains in performance. The results of the study have also demonstrated that a significant portion of the value of applying a fractional-order control in conjunction with hybrid metaheuristic optimization lies in the fact that the suggested model, FOPDD-I controller, is a powerful and adaptable approach to tethered UAV attitude control in highly complex and uncertain operating conditions.