Control Schemes for Quadrotor UAV: Taxonomy and Survey

Quadrotor Unmanned Aerial Vehicle (UAV) is an unstable system, so it needs to be controlled efficiently and intelligently. Moreover, due to its non-linear, coupled, and under-actuated nature, the quadrotor has become an important research platform to study and validate various control theories. Different control approaches have been used to control the quadrotor UAV. In this context, a comprehensive study of different control schemes is presented in this research. First, an overview of the working and different applications of quadrotor UAVs is presented. Second, a mathematical model of the quadrotor is discussed. Later, the experimental results of various existing control techniques are discussed and compared. The various control schemes discussed and described for quadrotors are; Proportional Integral and Derivative (PID), Linear Quadratic Regulator (LQR), H-infinity ( H ∞ ), Sliding Mode Control (SMC), Feedback Linearization (FBL), Model Predictive Control (MPC), Fuzzy Logic Control (FLC), Artificial Neural Network (ANN), Iterative Learning Control (ILC), Reinforcement Learning Control (RLC), Brain Emotional Learning Control (BELC), Memory Based Control (MBC), Nested Saturation Control (NSC), and Hybrid Controllers (HC). Comparison is done among all the control techniques and it is concluded that the hybrid control method gives improved results. This survey presents a broad overview of the state-of-the-art in UAV design, control, and implementation for real-life applications.

Robust servo linear quadratic regulator controller based on state compensation and velocity feedforward of the spherical robot: Theory and experimental verification

There are few studies on the lateral motion of spherical robots. In this article, a new algorithm is proposed to solve the problem of low control accuracy of the lateral motion. A single lateral motion model is established, and the optimal solution of the linear quadratic regulator in infinite time domain is obtained. Aiming at the problems of longitudinal velocity and lateral angle coupling and low control precision, state compensation and velocity feedforward are carried out, and an improved robust servo linear quadratic regulator control algorithm is proposed. Experiments show that the proposed lateral control algorithm has strong adaptability and robustness to changing speeds and lateral angles, and the control effect is stable and reliable.

HD Camera-Equipped UAV Trajectory Planning for Gantry Crane Inspection

While Unmanned Aerial Vehicles (UAVs) can be a valuable solution for the damage inspection of port machinery infrastructures, their trajectories are still prone to collision risks, trajectory non-smoothness, and large deviations. This research introduces a trajectory optimization method for inspecting vulnerable parts of a gantry crane by a UAV fitted with a high-definition (HD) camera. We first analyze the vulnerable parts of a gantry crane, then use the A* algorithm to plan a path for the UAV. The trajectory optimization process is divided into two steps, the first is a trajectory correction method and the second is an objective function that applies a minimum snap method while taking into consideration flight corridor constraints. The experimental simulation results show that, compared with previous methods, our approach can not only generate a collision-free and smooth trajectory but also shorten the trajectory length significantly while substantially reducing the maximum deviation average deviation distances. The simulation results show that this modelling approach provides a valuable solution for UAV trajectory planning for gantry crane inspection.

Modified Infinite-Time State-Dependent Riccati Equation Method for Nonlinear Affine Systems: Quadrotor Control

This paper presents modeling and infinite-time suboptimal control of a quadcopter device using the state-dependent Riccati equation (SDRE) method. It establishes a solution to the control problem using SDRE and proposes a new procedure for solving the problem. As a new contribution, the paper proposes a modified SDRE-based suboptimal control technique for affine nonlinear systems. The method uses a pseudolinearization of the closed-loop system employing Moore–Penrose pseudoinverse. Then, the algebraic Riccati equation (ARE), related to the feedback compensator gain, is reduced to state-independent form, and the solution can be computed only once in the whole control process. The ARE equation is applied to the problem reported in this study that provides general formulation and stability analysis. The effectiveness of the proposed control technique is demonstrated through the use of simulation results for a quadrotor device.

AUV Trajectory Tracking Models and Control Strategies: A Review

Autonomous underwater vehicles (AUVs) have been widely used to perform underwater tasks. Due to the environmental disturbances, underactuated problems, system constraints, and system coupling, AUV trajectory tracking control is challenging. Thus, further investigation of dynamic characteristics and trajectory tracking control methods of the AUV motion system will be of great importance to improve underwater task performance. An AUV controller must be able to cope with various challenges with the underwater vehicle, adaptively update the reference model, and overcome unexpected deviations. In order to identify modeling strategies and the best control practices, this paper presents an overview of the main factors of control-oriented models and control strategies for AUVs. In modeling, two fields are considered: (i) models that come from simplifications of Fossen’s equations; and (ii) system identification models. For each category, a brief description of the control-oriented modeling strategies is given. In the control field, three relevant aspects are considered: (i) significance of AUV trajectory tracking control, (ii) control strategies; and (iii) control performance. For each aspect, the most important features are explained. Furthermore, in the aspect of control strategies, mathematical modeling study and physical experiment study are introduced in detail. Finally, with the aim of establishing the acceptability of the reported modeling and control techniques, as well as challenges that remain open, a discussion and a case study are presented. The literature review shows the development of new control-oriented models, the research in the estimation of unknown inputs, and the development of more innovative control strategies for AUV trajectory tracking systems are still open problems that must be addressed in the short term.