This paper addresses the challenge of ever-smaller structures in the semiconductor industry and the resulting requirements for high-performance mechatronic systems, especially wafer scanners, in lithography processes in the context of mechatronic system design and analysis. As a result, the development of sophisticated methods for modeling, control, and analysis of control systems has become necessary. To meet this need, advanced analysis methods of multivariable control systems are investigated, in particular the combination of classical stability analysis methods like the Nyquist criteria and use of Individual Channel Analysis and Design (ICAD) methods. For this purpose, the requirements for the analysis of multivariable control systems are summarized and put in the context of classical methods of system analysis, for example, the use of Nyquist methods to evaluate the stability of the control loop. Subsequently, the paper provides a rationale for why the use of Single-Input Single-Output (SISO) methods to assess stability and robustness is not sufficient and how these can be extended to Multiple-Input Multiple Output (MIMO) methods to meet the requirements. A set of tailored Nyquist-like MIMO analysis methods are theoretically derived, including the ICAD method and classical Nyquist stability analysis and its use in the analysis of multivariable control system is explained. A coupling ratio parameter, quantifying the coupling of multivariable systems, is derived from the extended ICAD method. The iterative design process is explained, which allows conclusions to be drawn about individual system parameters and how to optimize them to achieve high performance. To compare the methods, a model of a mechanical payload with variable eigenfrequencies is derived. Subsequently, the suitability of the respective method for multivariable stability analysis is tested in different system configurations. In conclusion, this paper provides insight into the analysis of stability and robustness of multivariable control systems and presents the challenges and opportunities of using these advanced methods to design high-performance mechatronics in the context of increasing requirements due to the shrink in semiconductor manufacturing. This provides a valuable contribution to the design of high-performance mechatronic systems
