<p>This study proposes a novel adaptive sliding mode control (SMC) method for manipulating robotic motion. Our approach incorporates an adjustable-gain double power reaching law, which provides a significant advantage over traditional methods with fixed gains. By allowing the gains to self-adjust, our method eliminates the need for predefined values based on uncertain system knowledge. This key feature prevents overestimation of gains, which in traditional methods often leads to excessive chattering and can cause structural integrity issues during prolonged operation. The stability of this dynamic system is confirmed using the Lyapunov direct method. Additionally, an integral sliding surface is incorporated into our proposed algorithm to ensure that the manipulator’s joint tracking errors converge to zero. This ensures that the proposed method is stable and can maintain a precise tracking trajectory. The performance of this algorithm is then validated through a computational study and compared against traditional SMC methods.</p>