From the Editor-in-Chief

Appeal from the Third Judicial District Court of Salt Lake County honorable David Young District Judg

Thrust Vector Controller Comparison for a Finless Rocket

The paper focuses on comparing applicability, tuning, and performance of different controllers implemented and tested on a finless rocket during its boost phase. The objective was to evaluate the advantages and disadvantages of each controller, such that the most appropriate one would then be developed and implemented in real-time in the finless rocket. The compared controllers were Linear Quadratic Regulator (LQR), Linear Quadratic Gaussian (LQG), and Proportional Integral Derivative (PID). To control the attitude of the rocket, emphasis is given to the Thrust Vector Control (TVC) component (sub-system) through the gimballing of the rocket engine. The launcher is commanded through the control input thrust gimbal angle δ , while the output parameter is expressed in terms of the pitch angle θ . After deriving a linearized state–space model, rocket stability is addressed before controller implementation and testing. The comparative study showed that both LQR and LQG track pitch angle changes rapidly, thus providing efficient closed-loop dynamic tracking. Tuning of the LQR controller, through the Q and R weighting matrices, illustrates how variations directly affect performance of the closed-loop system by varying the values of the feedback gain (K). The LQG controller provides a more realistic profile because, in general, not all variables are measurable and available for feedback. However, disturbances affecting the system are better handled and reduced with the PID controller, thus overcoming steady-state errors due to aerodynamic and model uncertainty. Overall controller performance is evaluated in terms of overshoot, settling and rise time, and steady-state error

Evolucijski algoritam temeljen na off-line planeru putanje za navigaciju bespilotnih letjelica

An off-line path planner for Unmanned Air Vehicles is presented. The planner is based on Evolutionary Algorithms, in order to calculate a curved pathline with desired characteristics in a three-dimensional environment. The pathline is represented using B-Spline curves, with the coordinates of its control points being the genes of the Evolutionary Algorithm artificial chromosome. The method was tested in an artificial three-dimensional terrain, for different starting and ending points, providing very smooth pathlines under difficult constraints.Predstavljen je off-line planer putanje za bespilotne letjelice. Planer je temeljen na evolucijskim algoritmima za proračun zakrivljene putanje sa željenim karakteristikama u 3D prostoru. Putanja je predstavljena pomoću B-spline krivulja, gdje su koordinate kontrolnih točaka geni umjetnih kromosoma evolucijskih algoritama. Metoda je provjerena na umjetnom 3D prostoru s različitim početnim i konačnim točkama, gdje su dobivene vrlo glatke putanje uz zadovoljenje strogih ograničenja

Correction to the Euler Lagrange multirotor model with Euler angles generalized coordinates

This technical note proves analytically how the exact equivalence of the Newton-Euler and Euler-Lagrange modeling formulations as applied to multirotor UAVs is achieved. This is done by deriving a correct Euler-Lagrange multirotor attitude dynamics model. A review of the published literature reveals that the commonly adopted Euler-Lagrange multirotor dynamics model is equivalent to the Newton-Euler model only when it comes to the position dynamics, but not in the attitude dynamics. Step-by-step derivations and calculations are provided to show how modeling equivalence to the Newton-Euler formulation is proven. The modeling equivalence is then verified by obtaining identical results in numerical simulation studies. Simulation results also illustrate that when using the correct model for feedback linearization, controller stability at high gains is improved