Aerospace Science and Technology 104 (2020) 105945 Contents lists available at ScienceDirect Aerospace Science and Technology www.elsevier.com/locate/aescte Nonlinear control of aerial manipulation systems Z. Samadikhoshkho, S. Ghorbani, F. Janabi-Sharifi ∗ , K. Zareinia Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, Canada a r t i c l e i n f o a b s t r a c t Article history: Received 10 December 2019 Received in revised form 24 April 2020 Accepted 27 April 2020 Available online 15 June 2020 Communicated by Mehdi Ghoreyshi Keywords: Aerial manipulation Nonlinear control Dynamic inversion LQR Sliding mode This paper presents four effective control algorithms to overcome challenges in controlling Aerial Manipulation Systems (AMSs). Interaction with the environment, nonlinear couplings, and structural and non-structural uncertainties are some issues that make the AMS controller difficult to develop and implement. Because of the complexity in the control design process, many research studies employed simplified AMS dynamics in the design of the controller. In this study, all the proposed control algorithms, with the exception of the hierarchical LQR method, are designed considering complete dynamics of the system without any need for simplification. Proposed control methods include (i) inverse dynamic, (ii) hierarchical LQR, (iii) sliding mode, and (iv) semi-optimal nonlinear control, which show appropriate behavior in the presence of some of the above-mentioned challenges. In order to assess the effectiveness of the control methods, coupled dynamics of a quadcopter endowed with a robotic manipulator is modeled. These controllers are compared to identify their effectiveness in simultaneous control of the quadcopter and its manipulator in the context of control accuracy and control effort. Additionally, sensitivity of the proposed approaches to an increase in the uncertainty levels are determined.  2020 Elsevier Masson SAS. All rights reserved. 1. Introduction In the recent years, aerial manipulation has gained significant attention and become the subject of intensive research. This is mainly due to potential applications of aerial manipulation which could range from contactless missions (such as inspection [1], mapping, filming [2], remote monitoring [3], search and rescue [4]) to contact-based operations (e.g., perching, and manipulation [5,6]). The rapidly growing number of aerial manipulation applica- tions is a good indication of its potential. This particularly becomes important for a number of applications in which an aerial manip- ulation system (AMS) can replace humans in potentially hazardous or expensive operations. These systems could also enable tasks that are not currently possible to be performed by humans. A class of AMS efforts has been devoted to control of aerial suspension systems with suspended cables using single [7] or multiple un- manned aerial vehicles (UAVs) [8]. Modeling, estimation [9] and * Corresponding author. E-mail addresses: zahra.samadikhoshkho@ryerson.ca (Z. Samadikhoshkho), sghorbani@ryerson.ca (S. Ghorbani), fsharifi@ryersopn.ca (F. Janabi-Sharifi), kourosh.zareinia@ryerson.ca (K. Zareinia). control [7,10] of these systems are still a subject of interest for load transportation. Our focus, though, will be on the control of AMS where a robotic manipulator is attached to UAVs. It is distin- guished from other robotic systems in the sense that the maneu- verability and reach of UAVs along with dexterity of the attached arm would potentially enable a new range of reach and manipu- lation tasks such as sample collection from remote areas. Various types of UAVs have been used as a base platform of AMSs and, among those, the quadrotor is the popular configuration due to its simple structure and easy maintenance [11]. However, quadrotors are under-actuated systems which may lead to their instability. Also, when considered together, dynamics of UAV and manipula- tor become highly coupled. Therefore, the modeling and control of quadrotor-based AMSs are quite challenging and a subject of active research. Further challenges including potential interaction with the environment [12], structural and environmental uncer- tainties [13], system redundancy [14], singularity [15], and stability issues [16], could add to the difficulty of tackling the aforemen- tioned problems. Various control methods have been proposed in literature to overcome such problems. While a group of approaches have sim- plified the control design problem by considering decoupled dy- namics between UAV and manipulator(s) [17], a more realistic approach would be to consider the coupled system dynamics in control design [18]. Therefore, we will also consider coupled sys- tem dynamics in control design for quadrotor-based AMSs in this work. https://doi.org/10.1016/j.ast.2020.105945 1270-9638/ 2020 Elsevier Masson SAS. All rights reserved.