<p>The paper suggests a new method for controller design and order reduction of LTI higher-order systems (HOSs). This research uses the model dominance index to determine pole dominance. This metric identifies the dominant poles, even if they are not the slowest. An improved generalized pole clustering method is used to get the reduced model denominator, considering the relative distance from the first dominant pole in a cluster. It distinguishes itself from existing clustering approaches and represents the HOSs performance more precisely than previous methods. The suggested method uses a straightforward technique in the reduced model numerator to preserve the initial Markov parameters (MPs) and time moments (TMs). It does away with the requirement to compute them in advance, solve Pade equations, or create Routh-type tables. The method preserves the HOSs dominant poles, stability, TMs, MPs, and other essential properties. The desired method was then applied to design controllers that stabilize the closed-loop control system (CLCS) and enable faster response times through a simple mathematical methodology. The reference plant’s and CLCS responses are the same when the estimated model controller is applied to the HOS. Frequency and step responses, along with time-domain parameters, demonstrate the effectiveness of the proposed method. In addition, various system performance analysis measures were computed and compared with existing methods to test the adequacy of the proposed algorithm. For better comprehension and visualization, the respective bar charts are drawn to support the tabulated values. The graphical and tabulated results demonstrate that the proposed algorithm generates enhanced reduced systems for diverse systems. A simulation environment built in MATLAB is used for all case studies.</p>