Optimisation and Sensitivity analysis studies the sensitivity of the model by how much and/or what will be the proportion (or role) of the input parameters (reduced set of important variables) that cause significant influence on the output of the model. In short, analysing the contribution of input parameters on the output variability of the model. Generally (mathematically), it is used to determine the effect on optimal solutions of changes in parameter values of the objective function. They are computationally in-depth in the application of high dimensional functions. Optimisation algorithm can greatly improve the dynamic performance of the control system. A model is designed for its effective usefulness, so that its outcome will be efficient. Identifying the parameters, analysing the model and applying various optimisation algorithms and sensitivity algorithms on a model for increase of its efficiency is the prime motto of the project. These algorithms can be applied in various fields such as engineering, medical, economics etc., Structuring the project tasks into analytical (mathematical formulation), parameterization, applying optimisation and sensitivity algorithms by using the sofware OptiSlang (Software for Optimisation and Sensitivity Analysis) will be work flow of the project. The analysis will be applied either on vertically inverted oscillating pendulum or on the control of spring-mass systems.