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Abstract Managing complex chemical processes is challenging due to multiple interdependent variables, time delays, and uncertainties, which can degrade performance. Traditional single-loop controllers such as PID, often fail to meet these demands. This study focuses on overcoming these challenges by exploring the Harris Hawks Optimization (HHO) technique for tuning a Tilt-Integral Derivative (TID) controller. The HHO algorithm, inspired by the cooperative hunting strategies of Harris hawks, is an effective metaheuristic approach for solving optimization problems. The TID controller is tuned by considering performance metrics such as settling time, overshoot, and steady-state error. Besides, constraints on gain and phase margins are introduced to ensure the controller maintains adequate stability. A key aspect of the study involves the use of singular value analysis for graphical stability as it gives an insight into its dynamic properties and stability under varying conditions. Through extensive simulation studies, the proposed TID controller tuned with HHO demonstrates significant improvements in system performance. Compared to existing methods, the controller exhibits reduced settling time, minimized overshoot, and overall enhanced transient response. Furthermore, robustness testing under scenarios including sensor faults, actuator faults, and fluctuating operational conditions demonstrates the controller’s capability to maintain stability and performance