International Journal of Electrical and Computer Engineering (IJECE) Vol. 12, No. 1, February 2022, pp. 293~302 ISSN: 2088-8708, DOI: 10.11591/ijece.v12i1.pp293-302  293 Journal homepage: http://ijece.iaescore.com Optimal integral sliding mode controller controller design for 2-RLFJ manipulator based on hybrid optimization algorithm Randa Jalaa Yahya, Nizar Hadi Abbas Department of Electrical Engineering, College of Engineering, University of Baghdad, Baghdad, Iraq Article Info ABSTRACT Article history: Received Apr 24, 2021 Revised Jul 15, 2021 Accepted Aug 3, 2021 A newly hybrid nature-inspired algorithm called HSSGWOA is presented with the combination of the salp swarm algorithm (SSA) and grey wolf optimizer (GWO). The major idea is to combine the salp swarm algorithm's exploitation ability with the grey wolf optimizer's exploration ability to generate both variants' strength. The proposed algorithm uses to tune the parameters of the integral sliding mode controller (ISMC) that design to improve the dynamic performance of the two-link flexible joint manipulator. The efficiency and the capability of the proposed hybrid algorithm are evaluated based on the selected test functions. It is clear that when compared to other algorithms like SSA, GWO, differential evolution (DE), gravitational search algorithm (GSA), particles swarm optimization (PSO), and whale optimization algorithm (WOA). The ISMC parameters were tuned using the SSA, which was then compared to the HSSGWOA algorithm. The simulation results show the capabilities of the proposed algorithm, which gives an enhancement percentage of 57.46% compared to the standard algorithm for one of the links, and 55.86% for the other. Keywords: Flexible joint robot manipulator Grey wolf optimization HSSGWOA Integral sliding mode control Salp swarm algorithm This is an open access article under the CC BY-SA license. Corresponding Author: Randa Jalaa Yahya Department of Electrical Engineering, College of Engineering, University of Baghdad Al-Jadriya, Baghdad, Iraq Email: r.zaki1802m@coeng.uobaghdad.edu.iq 1. INTRODUCTION Robotic manipulators can be further categorized as rigid or flexible. The elastic properties of motor shafts, as well as harmonic drive transmission systems like gearboxes, straps, and pulleys, contribute to joint flexibility. A flexible-joint robot manipulator presents serious problems such as nonlinearity, largeness, coupling, uncertainty, and joint flexibility in modeling and control. This has led to much research into developing high-performance control approaches using state-of-the-art control theories [1]. For instance, proportional integral derivative (PID) controller [2]-[4], sliding mode control [5], fractional-order sliding mode controller [6], adaptive sliding mode control [7], fuzzy sliding mode control [8] have been dedicated to the study of flexible-joint robots. An integral sliding mode controller (ISMC) tracks a flexible joint manipulator driven by a direct current (DC) motor. It is an efficient control strategy for resolving many issues with the sliding mode control (SMC) approach, including the high-frequency chattering effect and insensitivity [9]. In this analysis, the ISMC controller parameters were tuned using the standard salp swarm algorithm (SSA) and a new hybrid nature-inspired algorithm named HSSGWOA. The SSA and the grey wolf optimizer (GWO) have been combined to create HSSGWOA GWO. The GWO is selected to be combined with SSA since it can converge to a higher-quality near-optimal solution, it is more suitable to converge in than any other common population-based method, such as genetic algorithm (GA), particles swarm optimization