The robot manipulator of the lunar rover is a crucial device in lunar exploration missions, capable of performing sampling, experimental operations, and environmental analysis. To meet different task requirements, opt...
详细信息
The robot manipulator of the lunar rover is a crucial device in lunar exploration missions, capable of performing sampling, experimental operations, and environmental analysis. To meet different task requirements, optimal trajectory planning is essential, and this planning relies on an accurate kinematic model. In the harsh environment of space, the kinematic parameters of the robot manipulator can change due to noise and structural damage, affecting the accuracy of trajectory planning. To address this, an energy-time-jerk optimal trajectory planning method for the robot manipulator with real-time parameter monitoring is proposed. The sequential quadratic programming (SQP) algorithm is utilized for trajectory planning. Building on this, a new algorithm that combines the Extended Kalman Filter (EKF) and SQP algorithm (EKF-SQP) is introduced. Simulation results demonstrate that the proposed algorithm significantly improves the accuracy of the robot manipulator's trajectory planning. Compared to existing methods, the integration of real-time parameter identification and compensation enhances precision by effectively reducing position errors of the end joint. By continuously updating the kinematic parameters in real-time, the algorithm ensures that the trajectory is dynamically re-planned, allowing the robot manipulator to reach the target position with higher accuracy.
To ensure safety and stability, it is optimal for nuclear power plants to operate at their nominal power level. However, to meet the needs of power systems, NPPs must also be able to adjust their output for load-follo...
详细信息
To ensure safety and stability, it is optimal for nuclear power plants to operate at their nominal power level. However, to meet the needs of power systems, NPPs must also be able to adjust their output for load-following purposes. This necessitates finding an effective control algorithm to maintain stable/safe operating conditions. The current study investigates the performance of PID controllers optimized using sequential quadratic programming algorithm and applied using two control techniques: control rod positioning and variable coolant flow rate. Simulation is done using model of four-loop Westinghouse PWR-1200 MW nuclear reactor. The proposed controller's performance is evaluated in three scenarios: sudden control rod withdrawal, sudden change in coolant inlet temperature, and linear load tracking. The influences of model parametric uncertainty are also investigated. Simulation results revealed that the performance of the control algorithm applied using variable coolant flow rate was superior to the one using control rod positioning.
To enable autonomous vehicles to generate smooth and collision-free trajectories and improve their driving performance on structured roads, this paper proposes a hierarchical trajectory planning algorithm based on an ...
详细信息
To enable autonomous vehicles to generate smooth and collision-free trajectories and improve their driving performance on structured roads, this paper proposes a hierarchical trajectory planning algorithm based on an improved artificial potential field method. To improve the applicability of the algorithm to complex scenarios, the Frenet coordinate system was established to address these limitations. First, the safety distance model is applied to the risk assessment of the improved artificial potential field method. Then, the hierarchical solution is carried out, and the road solvable convex space and the rough path solution are solved by combining the artificial potential field method. On this basis, the potential field term and the smoothing term cost function are established, and the sequential quadratic programming (SQP) algorithm is used to solve the exact path that meets the requirements of safety and smoothness. Hierarchical planning shortens the solution time by quickly determining the bounds of the convex space. Finally, in the speed planning, in order to take into account the comfort and safety of the occupants, the speed curve is solved by considering the dynamic constraints of the vehicle. The obstacle avoidance effects of the algorithm on static and dynamic obstacles are tested in different simulation scenarios. The results of the simulation experiment show that the proposed algorithm can successfully achieve obstacle avoidance on complex structured roads.
We propose a new method for linear second-order cone programs. It is based on the sequential quadratic programming framework for nonlinear programming. In contrast to interior point methods, it can capitalize on the w...
详细信息
We propose a new method for linear second-order cone programs. It is based on the sequential quadratic programming framework for nonlinear programming. In contrast to interior point methods, it can capitalize on the warm-start capabilities of active-set quadraticprogramming subproblem solvers and achieve a local quadratic rate of convergence. In order to overcome the nondifferentiability or singularity observed in nonlinear formulations of the conic constraints, the subproblems approximate the cones with polyhedral outer approximations that are refined throughout the iterations. For nondegenerate instances, the algorithm implicitly identifies the set of cones for which the optimal solution lies at the extreme points. As a consequence, the final steps are identical to regular sequential quadratic programming steps for a differentiable nonlinear optimization problem, yielding local quadratic convergence. We prove the global and local convergence guarantees of the method and present numerical experiments that confirm that the method can take advantage of good starting points and can achieve higher accuracy compared to a state-of-the-art interior point solver.
Shafts made of advanced composite materials and their applications in different fields are gaining momentum due to their optimized properties. This paper presents various multi-objective optimization (MOO) models for ...
详细信息
Shafts made of advanced composite materials and their applications in different fields are gaining momentum due to their optimized properties. This paper presents various multi-objective optimization (MOO) models for the structural design of slender, thin-walled spinning shafts made of advanced composite materials. The proposed mathematical formulation ensures the attainment of simultaneous and balanced improvements in the major design objectives, including minimal mass and maximum stability against whirling and torsional buckling under behavioral and side constraints. A hybrid genetic algorithm (GA) and sequential quadratic programming (SQP) are implemented to find the needed optimal solutions. Design variables encompass the fiber volume fraction, orientation angle, and thickness of each layer of the cross-section. A case study that addresses the optimization of a pinned-pinned slender shaft made of carbon/epoxy composites is presented. The new approach exhibited its capacity to overcome the uncertainty in ranking and selecting a solution from the set of Pareto-optimal solutions as it determines a unique optimal solution that has a nearly equal optimization gains for the selected design objectives.
PurposeThis study aims to develop a machining path posture optimization algorithm for robotic wood processing systems, integrating global path smoothing metrics and local constraint metrics, and refines the overall pr...
详细信息
PurposeThis study aims to develop a machining path posture optimization algorithm for robotic wood processing systems, integrating global path smoothing metrics and local constraint metrics, and refines the overall processes of pose optimization, path generation and interpolation, thereby enhancing machining ***/methodology/approachThis study begins by analyzing the redundancy in robotic wood processing systems and provides a parametric description based on five-axis linear paths from computer-aided manufacture (CAD/CAM). Global performance metrics are introduced to smooth joint velocity and acceleration, minimizing oscillations. Local constraints are incorporated to ensure path feasibility. A hybrid algorithm combining segmented dynamic programming and sequential quadratic programming (SQP) is proposed to improve computational efficiency. Finally, the smoothing and interpolation steps following pose-optimized path generation are *** and experimental results demonstrate the effectiveness of the proposed method in improving efficiency, motion smoothness and satisfying performance ***/valueThis study provides a systematic process for path generation and optimization method to robotic wood machining systems. By integrating tool posture constraints and proposing a hybrid optimization algorithm, it offers a novel solution to enhance path planning efficiency and practicality, contributing valuable insights for similar robotic applications.
As the penetration level of renewable energy sources (RESs) increases, the output power of RESs needs to be curtailed to balance the power supply and load demand. Nevertheless, depending on the curtailment control str...
详细信息
As the penetration level of renewable energy sources (RESs) increases, the output power of RESs needs to be curtailed to balance the power supply and load demand. Nevertheless, depending on the curtailment control strategy for wind power plants (WPPs), while the total amount of output power curtailment remains the same, the overall stored inertial energy within WPPs may vary. Furthermore, this stored inertial energy within WPPs can be used during disturbances to enhance frequency stability. This paper proposes a novel curtailment control strategy based on the sequential quadratic programming (SQP) optimization algorithm to effectively curtail WPPs and increase the overall stored inertial energy within WPPs. Then, the proposed solution can enhance frequency stability by providing a more inertial response from WPPs during disturbances. To verify the effectiveness of this novel curtailment control strategy, several case studies are conducted using the IEEE 39-bus system. The results show that the proposed curtailment control strategy effectively increases the stored inertial energy within WPPs while satisfying the required output power curtailment.
This paper proposes a distributed model predictive control (DMPC) algorithm for dynamic decoupled discrete-time nonlinear systems subject to nonlinear (maybe non-convex) coupled constraints and costs. Solving the resu...
详细信息
This paper proposes a distributed model predictive control (DMPC) algorithm for dynamic decoupled discrete-time nonlinear systems subject to nonlinear (maybe non-convex) coupled constraints and costs. Solving the resulting nonlinear optimal control problem (OCP) using a DMPC algorithm that is fully distributed, termination-flexible, and recursively feasible for nonlinear systems with coupled constraints and costs remains an open problem. To address this, we propose a fully distributed and globally convergence-guaranteed framework called inexact distributed sequential quadratic programming (IDSQP) for solving the OCP at each time step. Specifically, the proposed IDSQP framework has the following advantages: (i) it uses a distributed dual fast gradient approach for solving inner quadraticprogramming problems, enabling fully distributed execution;(ii) it can handle the adverse effects of inexact (insufficient) calculation of each internal quadraticprogramming problem caused by early termination of iterations, thereby saving computational time;and (iii) it employs distributed globalization techniques to eliminate the need for an initial guess of the solution. Under reasonable assumptions, the proposed DMPC algorithm ensures the recursive feasibility and stability of the entire closed-loop system. We conduct simulation experiments on multi-agent formation control with non-convex collision avoidance constraints and compare the results against several benchmarks to verify the performance of the proposed DMPC method.
暂无评论