# Review of Fault-Tolerant Control Systems Used in Robotic Manipulators
## 1 Introduction
In the described solution, the combination of an advanced autonomous supervision system was combined with a sensor-guided action generator. Experimental tests were conducted using a mobile two-arm robot system. [PERSON] et al. [15] described the real-time fault-tolerant control developed for a kinematically redundant manipulator. The authors used a fault-tolerance measure to enable the end effector of the manipulator to continuously follow a given trajectory. Finally, an algorithm was developed and used in real time for the control of a seven-degree-of-freedom commercially available manipulator. The purpose of using FTC systems is to assure reliability, which should be maintained despite the occurrence of faults of an acceptable nature. Intensive work is currently underway to develop this type of control in equipment used during manufacturing processes. One of the advantages of using this type of control in the production process is not only the safety of critical equipment but also cost reduction. The reduction in production costs is influenced by the continued operation of the devices used. At the time of an acceptable FTC failure, there is no need to stop production for maintenance purposes. This results in a reduction in the costs associated with service calls and also saves time by preventing a halt in the production process. [PERSON] and [PERSON] [16] presented a robust fault-tolerant control system, which can be used to overcome the failure of the robot manipulator actuators. The controller uses the algorithms for normal control (non-failed), fault detection, and control in case of faults to achieve the assumed task completion. Fault-tolerant control systems can be divided into three main categories: passive FTCS (PFTCS), active FTCS (AFTCS), and hybrid FTCS (HFTCS). PFTCS are characterized by the fact that they operate offline and are only able to adapt to faults that are defined at the design stage. Passive fault-tolerant steer systems do not require fault detection and isolation and are less computationally complex than active systems. AFTCS consist of a reconfiguration mechanism and a fault defection identification (FDI) mechanism. The FDI subsystem provides information to the controller about the fault and the controller responds by reconfiguring itself or the controlled device. The FDI subsystem is a key component of an active FTCS as it detects the fault and immediately sends information to the controller. The immediate reconfiguration of the controller upon receiving information from the FDIallows this method to be called active. There are also hybrid HFTCS controllers, which are a combination of PFTCS and AFTCS. In this paper, all the above-mentioned methods used in applications for robotic arm steering are reviewed. The methodology for selecting articles for this paper was limited to the time frame of the proposed solutions, that is, mainly the last 20 years. In addition, it was decided to place the main emphasis only on solutions that use artificial intelligence and sliding-mode controllers. Furthermore, all the selected papers deal with the use of FTC methods in robot control. In addition, the papers that focus on the control of manipulators with up to 7 degrees of freedom were chosen for our review. Articles about other robots such as hexapods or mobile robots were excluded from this review. This review is presented in six chapters, covering the available solutions of various FTC systems used to control robotic arms. In Section 1, the history and background of FTC systems are described. Section 2 is devoted to presenting the state-of-the-art FTCS that use artificial intelligence methods. Section 3 presents the variants of FTCS that use sliding-mode control. Section 4 deals with other FTCS used in robots that have been developed in recent years. Section 5 presents the summary and Section 6 presents the conclusions.