State constraints in nonlinear systems are commonly pursued by resorting to barrier functions,which enforce constraints over the entire duration of system operation.We propose a universal intermittent state-constraine...State constraints in nonlinear systems are commonly pursued by resorting to barrier functions,which enforce constraints over the entire duration of system operation.We propose a universal intermittent state-constrained solution,which not only offers flexibility by activating constraints just during specific time periods of interest to the user,but also successfully accommodates different types of constraint boundaries.The innovative shifting functions are proposed to facilitate seamless transitions between constrained and unconstrained operational phases,resulting in more user-friendly design and implementation.By blending an improved shifting transformation into intermittent constraint design,we construct a universal barrier function upon the constrained states,with which our control strategy removes the limitations on constraint functions and completely obviates the feasibility conditions.Furthermore,a modified fuzzy approximator driven by the prediction error rather than the tracking error achieves decoupling of the control and estimation loops,which not only ensures the estimation performance,but also facilitates proof of stability.Finally,the effectiveness of the proposed scheme is assessed by numerical simulation.展开更多
In this paper, we study numerical methods for an optimal control problem with pointwise state constraints. The traditional approaches often need to deal with the deltasingularity in the dual equation, which causes man...In this paper, we study numerical methods for an optimal control problem with pointwise state constraints. The traditional approaches often need to deal with the deltasingularity in the dual equation, which causes many difficulties in its theoretical analysis and numerical approximation. In our new approach we reformulate the state-constrained optimal control as a constrained minimization problems only involving the state, whose optimality condition is characterized by a fourth order elliptic variational inequality. Then direct numerical algorithms （nonconforming finite element approximation） are proposed for the inequality, and error estimates of the finite element approximation are derived. Numerical experiments illustrate the effectiveness of the new approach.展开更多
基金supported by the Fundamental Research Funds for the Central Universities(N2404005)the National Key Research and Development Program of China(2018YFA0702200)+2 种基金Liaoning Revitalization Talents Program(XLYC1801005)the National Natural Science Foundation of China(U23B20118)the Nature Science Foundation of Liaoning Province of China(2022JH25/10100008)。
文摘State constraints in nonlinear systems are commonly pursued by resorting to barrier functions,which enforce constraints over the entire duration of system operation.We propose a universal intermittent state-constrained solution,which not only offers flexibility by activating constraints just during specific time periods of interest to the user,but also successfully accommodates different types of constraint boundaries.The innovative shifting functions are proposed to facilitate seamless transitions between constrained and unconstrained operational phases,resulting in more user-friendly design and implementation.By blending an improved shifting transformation into intermittent constraint design,we construct a universal barrier function upon the constrained states,with which our control strategy removes the limitations on constraint functions and completely obviates the feasibility conditions.Furthermore,a modified fuzzy approximator driven by the prediction error rather than the tracking error achieves decoupling of the control and estimation loops,which not only ensures the estimation performance,but also facilitates proof of stability.Finally,the effectiveness of the proposed scheme is assessed by numerical simulation.
基金the National Natural Science Foundation of China (No.60474027 and 10771211)the National Basic Research Program under the Grant 2005CB321701
文摘In this paper, we study numerical methods for an optimal control problem with pointwise state constraints. The traditional approaches often need to deal with the deltasingularity in the dual equation, which causes many difficulties in its theoretical analysis and numerical approximation. In our new approach we reformulate the state-constrained optimal control as a constrained minimization problems only involving the state, whose optimality condition is characterized by a fourth order elliptic variational inequality. Then direct numerical algorithms （nonconforming finite element approximation） are proposed for the inequality, and error estimates of the finite element approximation are derived. Numerical experiments illustrate the effectiveness of the new approach.
