his paper reports new design aspects of conventional cascade control systems and develops the basic cascade control structure into a multi-loop (single-input, multioutput or SIMO) topology to improve the system performance for process control applications. This SIMO control structure has several advantages such as an easy and simultaneous controller design procedure, which considers the inner process dynamics and disturbance rejection for on-line operation. The paper includes a sequential reduction algorithm using additive and multiplicative uncertainties to provide low order controllers and to improve the system robustness. Subsequently SIMO self-tuning cascade control is developed. Different design methods such as polynomial LQG or H-infinity are used in different cascade control loops. Parametrized dynamic weighting functions in the controller design theory are used to achieve stability robustness. Stability robustness theorems are applied to the model-order-reduced plant and the effect of strong inner process disturbance is attenuated. In the multi-loop explicit self-tuning control described, fast convergence and reliable parameter estimation is achieved using an unbiased recursive least squares algorithm. Simulated industrial examples, superheater temperature control and furnace temperature control show that the stability and time domain performance of conventional cascade and multi-loop processes are improved by the new design approaches and the use of adaptive control when appropriate.