Most Of The Chemical Processes Are Tend To Be Nonlinear In Nature. Distillation, Polymerization Etc. Are The Example Of A Few Of Them Which Shows Considerable Nonlinearity In Its Operation. Apart From Structural Complexity Tight Scheduling And Higher Output Specification Makes The Overall Process More Difficult To Control. Ordinary Conventional Control Techniques Can Not Always Cope With The External Requirement. This Brings The Use Of Advanced Control Techniques For Maintaining The Requirement. Recent Advances In Differential Geometry Have Spurred Renewed Interest On Design And Development Of Nonlinear Control Strategies. Input Output Linearization Based Control Strategy Is The Example Of The Above Mentioned Strategies. Basic Philosophy Of IOL Strategy Is To Develop A Nonlinear Control Law Which Eliminates The Process Nonlinearity And Keep The Overall Output Input Relation As A Linear One. The Major Constraint In Use Of The IOL Algorithm Is The Available Output Measurement. Most Of The Chemical Processes Are Limited By Its Measurement. So This Partial Knowledge On State Is Not Adequate For Using The IOL Algorithm. A Suitable Nonlinear Observer Is Required For Reconstruction Of All The States. This Raises The Importance Of The Studies Of Different Observation Schemes. The Final Problem Of Using IOL Law Is Uncertainty Of The Process. Simplifying Model Representation And Unknown Parameter Information And Sometimes Process Constraint Induces Strong Nonlinearity In The Process. So For Imperfect Constrained Model An Adaptive Estimation Is Required For Estimating The Unknowns. Finally A Robust Criterion Is