Intelligent control of complex industrial processes requires that knowledge from a variety of sources be used to maintain control over an extended set of operating conditions. It is asserted that to maintain the integrity of such heterogeneous knowledge, it should be encoded in distinct models. Control then consists of selecting and executing the most appropriate model for a given situation. Adaptive intelligent control can then be implemented by developing switching strategies that allow a trade-off between the various model properties. A prototype system (MuRaLi) is presented that has multiple models based on three primitive dimensions: precision, scope and generality. Generality is realised through three different knowledge representation mechanisms: procedures, rules and equations. Homogeneous control consists of constant generality and variable precision and scope to generate the most appropriate control action. Heterogeneous control consists of potential variations in all three dimensions. Simple switching strategies are investigated for both forms of control. The system has been applied to the control of a simulated 800 MW thermal power plant. Examples of homogeneous and heterogeneous control are given, with experimental results of adaptation based on the proposed switching strategies.