Continuity of the optimal value function and optimal solutions of parametric mixed-integer quadratic programs

To properly describe and solve complex decision problems, research on theoretical properties and solution of mixed-integer quadratic programs is becoming very important. We establish in this paper different Lipschitz-type continuity results about the optimal value function and optimal solutions of mixed-integer parametric quadratic programs with parameters in the linear part of the objective function and in the right-hand sides of the linear constraints. The obtained results extend some existing results for continuous quadratic programs, and, more importantly, lay the foundation for further theoretical study and corresponding algorithm analysis on mixed-integer quadratic programs.

Optimal Portfolio Selection with Delay under the Framework of Uncertainty Theory

This study focuses on investigating the optimal investment strategy for an optimization problem with delay using the uncertainty theory. The financial market is composed of a risk-free asset and a risk asset with an uncertain price process described by an uncertain differential equation. An optimization problem is assumed that its objective is a nonlinear function of decision variable. By deriving the equation of optimality, an analytical solution is obtained for the optimal delay investment strategy, and the optimal delay value function. Finally, an economic analysis and numerical sensitivity analysis are conducted to evaluate the research results.

Model predictive control of grid-connected PV power generation system considering optimal MPPT control of PV modules

Because of system constraints caused by the external environment and grid faults,the conventional maximum power point tracking(MPPT)and inverter control methods of a PV power generation system cannot achieve optimal power output.They can also lead to misjudgments and poor dynamic performance.To address these issues,this paper proposes a new MPPT method of PV modules based on model predictive control(MPC)and a finite control set model predictive current control(FCS-MPCC)of an inverter.Using the identification model of PV arrays,the module-based MPC controller is designed,and maximum output power is achieved by coordinating the optimal combination of spectral wavelength and module temperature.An FCS-MPCC algorithm is then designed to predict the inverter current under different voltage vectors,the optimal voltage vector is selected according to the optimal value function,and the corresponding optimal switching state is applied to power semiconductor devices of the inverter.The MPPT performance of the MPC controller and the responses of the inverter under different constraints are verified,and the steady-state and dynamic control effects of the inverter using FCS-MPCC are compared with the traditional feedforward decoupling PI control in Matlab/Simulink.The results show that MPC has better tracking performance under constraints,and the system has faster and more accurate dynamic response and flexibility than conventional PI control.

Optimal Configuration of a Redundant Robotic Arm: Compliance Approach

Applications of robots in tasks where the robot's end-effector bears loads, such as manipulating or assembling an object, picking-and-placing loads, grinding or drilling, demand precision. One aspect that improves precision is the limitation, if not elimination, of manipulator compliance. This paper presents a manipulator compliance optimization approach for determining an optimal manipulator configuration for a given position in the robot's task space. A numerical solution for minimal compliance, a nonlinear constrained optimization problem, is presented for an arbitrary position and illustrated by an example, using a model developed on ADAMS software and using MATLAB optimization tools. Also, this paper investigates the optimal value function for robot tasks in which the tool-point is subjected to applied force as it generates an important trajectory such as in grinding processes. The optimal value function is needed for optimal configuration control.

The Expansion of Dynamic Solving Process About a Class of Non-linear Programming Problems

In this paper, we research non linear programming problems which have a given special structure, some simple forms of this kind structure have been solved in some papers, here we focus on other complex ones.