首页> 外文会议>Annual ISA POWID symposium >RATE-CONSTRAINED WAVELET MULTIRESOLUTIONMODEL-BASED PREDICTIVE CONTROL FOR HYBRID COMBUSTION-GASIFICATION CHEMICAL LOOPING PROCESS
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RATE-CONSTRAINED WAVELET MULTIRESOLUTIONMODEL-BASED PREDICTIVE CONTROL FOR HYBRID COMBUSTION-GASIFICATION CHEMICAL LOOPING PROCESS

机译:基于速率约束的小波多分辨率模型 - 用于混合燃烧 - 气化化学循环过程的预测控制

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Chemical looping process is a novel technology to separate oxygen from nitrogen using solid oxygen carrier to facilitate carbon dioxide capture in the design of next generation clean coal power plants. The chemical looping process involves multi-phase gas-solid flows that have a highly challenging uncertain nonlinear multi-scale dynamics with jumps, not captured well by traditional single-scale models and as a result not amenable to tight control through traditional approaches. As a consequence, there exists a need for developing model-based advanced control solutions to tightly and robustly operate and control the chemical looping process. In an effort to model and control such a complex system, singleinput- single-output NARX models developed based on the temporal multi-resolution wavelet decompositions are presented. First, the NARX model, nonlinear in the wavelet basis, but linear in parameters, is obtained as a model identifier that well characterizes the nonlinear dynamics of single loop gas/solid flow behavior. Then, this model is approximated via Taylor expansion to obtain a linearized NARMA-L1 model. Based on the linear model, one-step ahead predictive control laws are designed. To reduce the excessive aggressiveness of the resulting control signals, ad hoc input constraints are designed and applied to limit the rate of control signal. Next, the one-step-head predictive control is extended to multistep adaptive generalized predictive control (GPC) scheme based on online identification of multi-resolution wavelet model structure. The control inputs and wavelet model parameters are calculated by optimizing the cost function using gradient descent methods. The convergence and stability of the proposed GPC scheme are shown using Lyapunov stability theorem. The real-time implementation results of the one-step-ahead predictive control law with rate constraint on the single loop configuration of Alstom’s cold solid flow chemical loop test facility in Windsor, Connecticut, are presented. The tracking performance of the real-time controller is presented in this paper.
机译:化学循环过程是一种新颖的技术,用于使用固体氧载体将氧气分离氧气,促进二氧化碳在下一代清洁煤发电厂的设计中捕获。化学循环过程涉及多相气体固体流动,具有高度挑战的不确定非线性多尺度动态,具有跳跃,而不是通过传统的单尺度模型捕获,因此通过传统方法不适合控制。因此,需要开发基于模型的先进控制解决方案,以紧密和鲁棒地操作和控制化学循环过程。在努力模拟和控制这样一个复杂的系统中,介绍了基于时间多分辨率小波分解开发的单次算 - 单输出NARX模型。首先,NARX模型,非线性在小波的基础上,但参数中的线性是作为模型标识符,该模型标识良好表征了单环气体/固体流动行为的非线性动态。然后,通过泰勒展开近似该模型以获得线性化的Narma-L1模型。基于线性模型,设计了一步的预测控制法。为了降低所产生的控制信号的过度攻击性,设计并应用了临时输入约束以限制控制信号的速率。接下来,基于多分辨率小波模型结构的在线识别,扩展了一步头预测控制到多步自适应通用预测控制(GPC)方案。通过使用梯度下降方法优化成本函数来计算控制输入和小波型参数。所提出的GPC方案的收敛性和稳定性显示使用Lyapunov稳定性定理。提出了一步的一步预测控制法的实时实施结果,康塞汀在Windsor,康涅狄格州的Alstom冷固流化学回忆测试设施的单环形配置的速率约束。本文提出了实时控制器的跟踪性能。

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