This paper introduces a hybrid control algorithm, the *Active Disturbance Rejection Control (ADRC)-Sliding Mode Control (SMC)*, which combines the strengths of ADRC and SMC to enhance the performance and stability of control systems. The ADRC-SMC algorithm is designed to address the limitations of traditional ADRC, such as the lack of clear guidelines for parameter tuning and the complexity of stability analysis. The parameters of the ADRC-SMC algorithm are optimized using a metaheuristic slime mould algorithm (SMAs), which reduces heuristics and ensures fair performance comparison with the standard ADRC algorithm. The paper outlines the design steps for both the second-order continuous-time ADRC and ADRC-SMC algorithms, emphasizing the inclusion of filter dynamics in the implementation. The ADRC-SMC algorithm is validated through experiments on a tower crane laboratory system, where the position of the cart, arm, and payload is controlled. The experimental results demonstrate the improved performance and stability of the ADRC-SMC algorithm compared to the ADRC algorithm. The paper concludes by highlighting the advantages of the ADRC-SMC algorithm, including its ability to guarantee system stability and improve control performance. Future research will focus on further stability analysis and the implementation of the control laws in discrete time, using different optimization algorithms.This paper introduces a hybrid control algorithm, the *Active Disturbance Rejection Control (ADRC)-Sliding Mode Control (SMC)*, which combines the strengths of ADRC and SMC to enhance the performance and stability of control systems. The ADRC-SMC algorithm is designed to address the limitations of traditional ADRC, such as the lack of clear guidelines for parameter tuning and the complexity of stability analysis. The parameters of the ADRC-SMC algorithm are optimized using a metaheuristic slime mould algorithm (SMAs), which reduces heuristics and ensures fair performance comparison with the standard ADRC algorithm. The paper outlines the design steps for both the second-order continuous-time ADRC and ADRC-SMC algorithms, emphasizing the inclusion of filter dynamics in the implementation. The ADRC-SMC algorithm is validated through experiments on a tower crane laboratory system, where the position of the cart, arm, and payload is controlled. The experimental results demonstrate the improved performance and stability of the ADRC-SMC algorithm compared to the ADRC algorithm. The paper concludes by highlighting the advantages of the ADRC-SMC algorithm, including its ability to guarantee system stability and improve control performance. Future research will focus on further stability analysis and the implementation of the control laws in discrete time, using different optimization algorithms.