工业应用中的先进离散时间控制方法
Advanced Discrete-Time Control Methods for Industrial Applications
AI总结：
本文提出两种工业系统中的先进离散时间控制方法，通过电池储能系统优化风力发电调度，并设计基于独立关节控制策略的起重机控制系统，以实现高精度和低负载摆动。
摘要：
本文提出两种先进的离散时间控制方法，用于工业系统的应用。第一部分针对电力网络中的风电调度，利用电池储能系统（BESS）进行优化，开发了一种基于离散时间模型预测控制（MPC）的新控制方案，以确保在存在实际约束的情况下BESS的最优运行。该控制方案遵循决策策略，在高峰需求时间出售更多能量，在非高峰时间储存能量，符合澳大利亚国家电力市场规则。通过模拟环境使用实际风电场和电力价格数据，在不同场景下评估了控制系统的性能。第二部分考虑了起重机系统的自动操作，为实现高速负载运输、高精度和最小负载摆动，开发了一种基于独立关节控制策略的新建模方法，将执行器视为主要被控对象。起重机动态的非线性特性被视为作用于每个执行器的扰动。所得到的模型使我们能够估计系统的未知参数，包括库仑摩擦常数。还设计了一种基于被动控制的新型负载摆动控制，以抑制负载摆动。然后基于MPC和状态反馈控制开发了两个离散时间控制器，以跟踪参考轨迹，并结合前馈控制来补偿扰动，使用计算扭矩控制和新型扰动观测器。在实验起重机设置上的实际结果展示了所设计控制系统的高性能。
英文摘要：
This thesis focuses on developing advanced control methods for two industrial systems in discrete-time aiming to enhance their performance in delivering the control objectives as well as considering the practical aspects. The first part addresses wind power dispatch into the electricity network using a battery energy storage system (BESS). To manage the amount of energy sold to the electricity market, a novel control scheme is developed based on discrete-time model predictive control (MPC) to ensure the optimal operation of the BESS in the presence of practical constraints. The control scheme follows a decision policy to sell more energy at peak demand times and store it at off-peaks in compliance with the Australian National Electricity Market rules. The performance of the control system is assessed under different scenarios using actual wind farm and electricity price data in simulation environment. The second part considers the control of overhead crane systems for automatic operation. To achieve high-speed load transportation with high-precision and minimum load swings, a new modeling approach is developed based on independent joint control strategy which considers actuators as the main plant. The nonlinearities of overhead crane dynamics are treated as disturbances acting on each actuator. The resulting model enables us to estimate the unknown parameters of the system including coulomb friction constants. A novel load swing control is also designed based on passivity-based control to suppress load swings. Two discrete-time controllers are then developed based on MPC and state feedback control to track reference trajectories along with a feedforward control to compensate for disturbances using computed torque control and a novel disturbance observer. The practical results on an experimental overhead crane setup demonstrate the high performance of the designed control systems.
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