• Systematic, structure-based design of multivariable control configurations for chemical/process plants, integrating process decomposition, task classification, and design-by-structure with Nyquist/Bode evaluation and synthesis frameworks [6], [17], [18], [19], [3], [5].

• Robustness- and sensitivity-oriented control design in multivariable settings, translating time-domain sensitivities to frequency-domain specifications, and addressing parameter variation and plant interactions [13], [15], [19], [16].

• State estimation and model-uncertainty handling through inferential control, orthogonal filters, and Kalman-based estimation to support robust regulation in the presence of unmeasured quantities and model errors [7], [12], [4], [16].

• Self-tuning/online control approaches complemented by software tools enabling rapid design iterations, including pole-assignment self-tuning regulators, Kalman-based online control studies, and MATRIXx for modeling and synthesis [1], [4], [14], [18].

• Discrete-time, deadbeat-oriented control in multivariable systems, exploring minimal-time response and stability constraints via geometric and algebraic deadbeat strategies [8], [11].