**6. Conclusions**

In this research, inverse kinematics problem for a 7 degree of freedom serial robot manipulator was implemented to prove the accuracy and efficiency of the self-adaptive control parameters in Differential Evolution (ISADE) and the ISADE algorithm with searching space improvement (Pro-ISADE) algorithm. To evaluate the effectiveness of the two algorithms above, the results obtained from the ISADE algorithm as well as Pro-ISADE were compared with the results from the PSO (Pro-PSO) and DE (Pro-DE) algorithm. Experiments were performed with three Scenarios. In the first Scenario, an endpoint in the workspace is randomly selected. The purpose of this Scenario is to compare the convergence speed of the three algorithms. In the second Scenario, algorithm was used to calculate inverse kinematics of the robot for 100 points randomly selected in the working space. The aim of this Scenario 2 is to test the accuracy and efficiency of the algorithm when the end effector started at the same position, it went to any point in working space. Meanwhile, in the third Scenario, the algorithms solved the inverse kinematics problem when the end effector of the robot moved point to point that are located on a spiral trajectory in the workspace. The implementation experiments have shown, the ISADE algorithm gave much better results than other algorithms in term of: accuracy, execution time and number of generation. Besides, by improving the searching boundary for joints' variable, the Pro-ISADE, Pro-DE and Pro-PSO also improve the accuracy as well as processing speed and especially the quality of the value of the joints variable compared to the ISADE, DE and PSO, respectively. These optimal joints' values ensure the feasibility of the dynamic and control problem in the future. In short, with ISADE algorithm as well as Pro-ISADE, they have handled the inverse kinematic requirement very effectively both in term of accuracy and computation time. The Pro-ISADE algorithm not only improves the above two factors, but also improves the quality of the joints' variables.

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