检索结果-内蒙古大学图书馆

Stability Region Patterns in Dominant Pole Placement based PID controller Design for SOPTD Systems

Chemical Engineering Science 2025年

作者： Kaushik Halder Saptarshi Das School of Computing & Electrical Engineering Indian Institute of Technology Mandi Mandi Himachal Pradesh Kamand 175005 India Faculty of Environment Science and Economy Centre for Environmental Mathematics University of Exeter Penryn Campus Cornwall TR10 9FE United Kingdom Institute for Data Science and Artificial Intelligence University of Exeter North Park Road Exeter Devon EX4 4QE United Kingdom

This paper proposes a new analytical formulation to design dominant pole placement based proportional-integral-derivative (PID) controllers for handling second order retarded type delay differential equations (DDEs) or in the control systems community, commonly known as the second order plus time delay (SOPTD) systems. This proposed method does not need any finite term approximation like different orders of Pade approach to derive the quasi-polynomial characteristic equation for analytical stability analysis. Rather the proposed method uses a mapping by which the transcendental exponential delay terms in the characteristic polynomial is transformed into finite number of discrete time poles by a suitable choice of the sampling time. Here, we explore a specific case, where the choice of sampling time makes the order of characteristic polynomial in the discrete time or z -domain being an odd number. The PID controllers are discretized by both Euler’s and Tustin’s method for a comparison between these two approaches. The corresponding PID controller gains are obtained using the dominant pole placement criterion. Effectiveness of the proposed methodology are demonstrated on several SOPTD test-bench plants with different lag to delay ratios and open loop damping levels, using credible numerical simulations. Here, the novel finding is that we obtain irregular, discontinuous, multi-modal stability regions for the odd number of dominant pole placement problem through optimization whereas similar previous works have reported continuous stability regions when attempted for even number of non-dominant pole placement problems.

关键词： dominant pole placement PID controller SOPTD plant pole-zero matching Euler’s and Tustin’s discretization optimization-based control

来源：评论

学校读者我要写书评

暂无评论

Mission Planning and control of Multi-Aircraft Systems With Signal Temporal Logic Specifications

引用

IEEE ACCESS 2019年 7卷 155941-155950页

作者： Baspinar, Baris Balakrishnan, Hamsa Koyuncu, Emre Istanbul Tech Univ Dept Aeronaut Engn TR-34469 Istanbul Turkey MIT Dept Aeronaut & Astronaut Cambridge MA 02139 USA

This paper focuses on optimization-based control of multi-aircraft systems that have several mission objectives. Signal Temporal Logic (STL) is used to express the mission specifications that combine temporal and logical constraints. A methodology is presented to construct an optimization problem in the form of Mixed-Integer Linear Programming (MILP) by using the differential flatness property of a nonlinear dynamical system and STL specifications to generate feasible trajectories. Contrary to general implementations of Temporal Logic to discrete-time systems, the proposed method deals with continuous-time systems. It can be used to find optimal control strategies to achieve the assigned tasks for nonlinear dynamical systems without discretizing the system dynamics. As an illustration, we present an air traffic control example. The nonlinear dynamical model for the aircraft is represented as a partially differentially flat system, and the presented method is applied to manage approach control and to solve the arrival sequencing problem. The method is also applied with a quadrotor fleet to show that the method can be used with different multi-agent systems.

关键词： Trajectory Planning Aircraft Multi-agent systems System dynamics Mathematical model optimization Signal temporal logic multi-aircraft systems air traffic control optimization-based control differential flatness

来源：评论

学校读者我要写书评

暂无评论

Dynamic Active Constraints for Surgical Robots Using Vector-Field Inequalities

引用

IEEE TRANSACTIONS ON ROBOTICS 2019年第5期35卷 1166-1185页

作者： Marinho, Murilo Marques Adorno, Bruno Vilhena Harada, Kanako Mitsuishi, Mamoru Univ Tokyo Dept Mech Engn Tokyo 1138656 Japan Univ Fed Minas Gerais Dept Elect Engn BR-31270901 Belo Horizonte MG Brazil

Robotic assistance allows surgeons to perform dexterous and tremor-free procedures, but robotic aid is still under-represented in procedures with constrained workspaces, such as deep brain neurosurgery and endonasal surgery. In these procedures, surgeons have restricted vision to areas near the surgical tooltips, which increases the risk of unexpected collisions between the shafts of the instruments and their surroundings. In this paper, our vector-field-inequalities method is extended to provide dynamic active-constraints to any number of robots and moving objects sharing the same workspace. The method is evaluated with experiments and simulations in which robot tools have to avoid collisions autonomously and in real-time, in a constrained endonasal surgical environment. Simulations show that with our method the combined trajectory error of two robotic systems is optimal. Experiments using a real robotic system show that the method can autonomously prevent collisions between the moving robots themselves and between the robots and the environment. Moreover, the framework is also successfully verified under teleoperation with tool-tissue interactions.

关键词： Collision avoidance dual quaternions optimization-based control virtual fixtures

来源：评论

学校读者我要写书评

暂无评论

Multi-vehicle coordination based on hierarchical quadratic programming

引用

control ENGINEERING PRACTICE 2020年 94卷 104206-000页

作者： Perez-Villeda, Hector M. Arechavaleta, Gustavo Morales-Diaz, America Ctr Invest & Estudios Avanzados IPN Robot & Adv Mfg Grp Saltillo Coahuila Mexico Introid Inc SA CV Ramos Arizpe Coah Mexico

This paper presents an optimization-based control scheme for generating online multi-vehicle coordination behaviors to accomplish missions in indoor environments. The proposed control scheme relies on the use of hierarchical task functions in terms of the multi-vehicle configuration variables. The task functions are related to individual and group obstacle avoidance, reaching fixed targets, group trajectory tracking, maintaining formations, enclosing the group within a geometric area, among others. The stack of hierarchical tasks automatically handles possible conflicts between them. Quadratic programs are formulated for explicitly solving inequality and equality task constraints at any hierarchy. In addition, a finite state machine is employed to build complex group behaviors for successfully fulfilling group missions. The proposed control scheme is demonstrated on two experiments with static and moving obstacles where a group composed by six vehicles tracks a predefined trajectory for the center of mass of the group. In the second experiment, the group is asked to clean the workspace by pushing movable objects.

关键词： Multi-vehicle systems optimization-based control Hierarchical quadratic programming

来源：评论

学校读者我要写书评

暂无评论

Distributed Frequency and Voltage control for AC Microgrids based on Primal-Dual Gradient Dynamics ⁎

引用

IFAC-PapersOnLine 2020年第2期53卷 12229-12236页

作者： Lukas Kölsch Katharina Wieninger Stefan Krebs Sören Hohmann Institute of Control Systems Karlsruhe Institute of Technology Karlsruhe Germany

With the gradual transformation of power generation towards renewables, distributed energy resources are becoming more and more relevant for grid stabilization. In order to involve all participants in the joint solution of this challenging task, we propose a distributed, model-based and unifying controller for frequency and voltage regulation in AC microgrids, based on steady-state optimal control. It not only unifies frequency and voltage control, but also incorporates the classic hierarchy of primary, secondary and tertiary control layers with each closed-loop equilibrium being a minimizer of a user-defined cost function. By considering the individual voltage limits as additional constraints in the corresponding optimization problem, no superordinate specification of voltage setpoints is required. Since the dynamic model of the microgrid has a port-Hamiltonian structure, stability of the overall system can be assessed using shifted passivity properties. Furthermore, we demonstrate the effectiveness of the controller and its robustness against fluctuations in active and reactive power demand by means of numerical examples.

关键词： distributed control optimization-based control electric power systems microgrids frequency regulation voltage regulation

来源：评论

学校读者我要写书评

暂无评论

A Strategy for the Exact Solution of Multiparametric/Explicit Quadratically Constrained NMPC Problems ⁎

引用

IFAC-PapersOnLine 2020年第2期53卷 11380-11385页

作者： Iosif Pappas Nikolaos A. Diangelakis Efstratios N. Pistikopoulos Artie McFerrin Department of Chemical Engineering and Texas A&M Energy Institute Texas A&M University College Station TX 77845 USA

Multiparametric programming has proven to be an efficient strategy to alleviate the computational burden of solving model predictive control problems online. Recently, it has been shown that through a second-order Taylor approximation to the Basic Sensitivity Theorem, the exact solution of multiparametric/explicit quadratically constrained nonlinear model predictive control problems is enabled. As a result, the state space is nonlinearly partitioned, and the optimal control actions are expressed as nonlinear functions of the states of the system. In this work, an algorithm for the complete exploration of the parameter space and the derivation of the parametric solution of the aforementioned problem is provided. The proposed strategy is utilized to implicitly explore the parameter space by identifying the unique and optimal active sets which describe the parametric solution. The applicability of the presented methodology is demonstrated on a regulation problem of a nonisothermal continuously-stirred tank reactor near an unstable steady-state.

关键词： Model predictive optimization-based control Real time optimization control Nonlinear process control

来源：评论

学校读者我要写书评

暂无评论

Deterministic Global Nonlinear Model Predictive control with Neural Networks Embedded

引用

IFAC-PapersOnLine 2020年第2期53卷 5273-5278页

作者： Danimir T. Doncevic Artur M. Schweidtmann Yannic Vaupel Pascal Schäfer Adrian Caspari Alexander Mitsos Aachener Verfahrenstechnik - Process Systems Engineering RWTH Aachen University Aachen Germany Institute of Energy and Climate Research - Energy Systems Engineering (IEK-10) Forschungszentrum Jülich GmbH Wilhelm-Johnen-Straβe 52425 Jülich Germany JARA - Jülich Aachen Research Alliance Center for Simulation and Data Science

Nonlinear model predictive control requires the solution of nonlinear programs with potentially multiple local solutions. Here, deterministic global optimization can guarantee to find a global optimum. However, its application is currently severely limited by computational cost and requires further developments in problem formulation, optimization solvers, and computing architectures. In this work, we propose a reduced-space formulation for the global optimization of problems with recurrent neural networks (RNN) embedded, based on our recent work on feed-forward artificial neural networks embedded. The method reduces the dimensionality of the optimization problem significantly, lowering the computational cost. We implement the NMPC problem in our open-source solver MAiNGO and solve it using parallel computing on 40 cores. We demonstrate real-time capability for the illustrative van de Vusse CSTR case study. We further propose two alternatives to reduce computational time: i) reformulate the RNN model by exposing a selected state variable to the optimizer; ii) replace the RNN with a neural multi-model. In our numerical case studies each proposal results in a reduction of computational time by an order of magnitude.

关键词： Nonlinear process control Model predictive optimization-based control Global optimization Recurrent neural networks Neural networks in process control

来源：评论

学校读者我要写书评

暂无评论

control of interacting vehicles using model-predictive control, generalized Nash equilibrium problems, and dynamic inversion

引用

IFAC-PapersOnLine 2020年第2期53卷 15146-15153页

作者： Andreas Britzelmeier Matthias Gerdts Thomas Rottmann Bundeswehr University Munich 85577 Germany

The paper presents a control concept for interacting vehicles in a road network. The approach combines a high-level controller for the generation of collision-free trajectories and a low-level dynamic inversion controller for path tracking. The high-level controller uses model-predictive control for generalized Nash equilibrium problems, which are used to coordinate the vehicles. The control concept was implemented and validated on scale robots and experimental results are discussed.

关键词： multi-vehicle systems motion planning decision making dynamic games model predictive optimization-based control trajectory tracking path following

来源：评论

学校读者我要写书评

暂无评论

Nonlinear Model Predictive control of the Hydraulic Fracturing Process

引用

IFAC-PapersOnLine 2020年第2期53卷 11428-11433页

作者： Kuan-Han Lin John P. Eason Zhou (Joyce) Yu Lorenz T. Biegler Department of Chemical Engineering Carnegie Mellon University Pittsburgh PA 15213 USA

Hydraulic fracturing has drawn significant attention over the past decade, as it can recover crude oil and natural gas from shale deposits previously considered inaccessible, which brings considerable economic benefits. However, hazardous operating conditions of extremely high pressure and environmental concerns require us to control this process carefully. Unfortunately, nonhomogeneous rock properties make this process difficult to control. Therefore, an accurate dynamic model and a well-designed controller are needed. In this work, we use the well-known Perkins-Kern-Nordgren (PKN) model with reformulation to solve the moving boundary problem. Next, the process is controlled by a standard Nonlinear Model Predictive controller (NMPC) and multistage NMPC. We find that the process performance deteriorates under the influence of uncertainty with standard NMPC. When we control the process with standard NMPC, the pressure violation happens in one of the parameter mismatch cases. Nonetheless, when we apply multistage NMPC and consider the uncertainty evolution with a scenario tree, no constraint violations occur for all cases for both time-invariant and time-varying uncertainties. We also discuss the computational performance of different robust horizons for multistage NMPC. Our results demonstrate that the multistage NMPC is a promising approach to handle uncertainty caused by nonhomogeneous rock properties in the hydraulic fracturing process.

关键词： Model Predictive optimization-based control Hydraulic Fracturing Dynamic optimization Optimal control Robust Nonlinear Model Predictive control

来源：评论

学校读者我要写书评

暂无评论

Sampling variance update method in Monte Carlo Model Predictive control ⁎

引用

IFAC-PapersOnLine 2020年第2期53卷 1274-1281页

作者： Shintaro Nakatani Hisashi Date Graduate School of Systems and Information Engineering University of Tsukuba Ibaraki Japan Faculty of Engineering Information and SystemsUniversity of Tsukuba Ibaraki Japan

This study describes the influence of user parameters on control performance in a Monte-Carlo model predictive control (MCMPC). MCMPC based on Monte-Carlo sampling depends significantly on the characteristics of sampling distribution. We quantified the effect of user determinable parameters on control performance uisng the relatonship between the algorithm of MCMPC and convergence to the optimal solution. In particular, we investigated the limitations associated with the variance of sampling distribution causing a trade-off relationship with the convergence speed and accuracy of estimation. To overcome this limitation, we proposed two variance updating methods and new MCMPC algorithm. Furthermore, the effectiveness of the numeriacl simulation was verified.

关键词： Optimal control theory Monte-Carlo methods Randomized methods Model predictive optimization-based control

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：