Feasibility analysis of soft constraints for input and output variables is critical for model predictive control (MPC). When encountering the infeasible situation

some way should be found to adjust the constraints to guarantee that the optimal control law exists. For MPC integrated with soft sensor

considering the soft constraints for critical variables additionally makes it more complicated and difficult for feasibility analysis and constraint adjustment. Therefore

the main contributions are that a linear programming approach is proposed for feasibility analysis

and the corresponding constraint adjustment method and procedure are given as well. The feasibility analysis gives considerations to the manipulated

secondary and critical variables

and the increment of manipulated variables as well. The feasibility analysis and the constraint adjustment are conducted in the entire control process and guarantee the existence of optimal control. In final

a simulation case confirms the contributions in this paper.