Optimizing PID controller gains to model the performance of a quadcopter

Optimised Tuning of a PID-Based Flight Controller for a Medium-Scale Rotorcraft

“…The goal of each optimisation strategy is to find s ∈ S such that it minimises the objective function given in Equation (25). This is given mathematically as finding the solution ∀s ∈ S : f (ś) ≤ f (s) in finite time.…”

“…Each optimisation technique is used to find s i = {K p , K d , K i , } and s = {s 1 ∪ s 2 ∪ s 3 ∪ s 4 ∪ s 5 ∪ s 6 }, called the candidate solution, iteratively. At each iteration, the candidate solution is evaluated with respect to the objective function in Equation (25). Since the optimisation is done after the initial tuning via trial and error, this solution is used to initialise the search algorithms, which means that even when optimisation tools outperform manual tuning, this result is still useful towards the final optimisation outcome.…”

“…This study used the ISE perfomance function, which was proven to give an acceptable rise time and overshoot. In another similar study, Cedro et al [25] used an SAE performance function including the input signals scaled by a penalty factor ρ.…”

Real Time Optimal Tuning of Quadcopter Attitude Controller Using Particle Swarm Optimization

“…The literature shows that PID controllers have been applied successfully to quadrotors with some limitations [7,9,10]. However, the tuning of the PID controller may present challenges as it has to provide effective quadcopter dynamical behavior around the balance point.…”

“…These vehicles are found in many important applications, including for military and surveillance purposes of great importance [1][2][3][4]. The control of the UAV's attitude, altitude and position poses many difficulties and challenges and it has been the subject of numerous studies [3,[5][6][7][8][9][10][11][12][13][14]. Researchers and engineers are overwhelmed by the number of advanced algorithms that have been proposed to address the quadcopter control problem in particular.…”