Key Laboratory of Advanced Design and Intelligent Computing, School of Software Engineering, Dalian University, Dalian 116622, Liaoning, China.
School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1010, New Zealand.
Comput Biol Med. 2024 Mar;171:108213. doi: 10.1016/j.compbiomed.2024.108213. Epub 2024 Feb 27.
The nonlinearity and non-separability of the antithetic PID (aPID) controller have provided greater flexibility in the design of biochemical reaction networks (BCRNs), resulting in significant impacts on biocontrol-systems. Nevertheless, the dilution of control species is disregarded in designs of aPID controllers, which would lead to the failure of inhibition mechanism in the controller and loss of robust perfect adaptation (RPA)-the biological counterpart of robust steady-state tracking. Here, the impact of dilution processes on the structure of aPID is investigated in this study. It is discovered that the proportional and low-pass filters are altered when the dilution processes is present in control species, which increases the coupling between the controller parameters. Moreover, additional integrations for the reference signal and control output generated by control species dilution further leads to the loss of RPA. Subsequently, a novel aPID controller represented by BCRNs, termed quasi-aPID, has been designed to eliminate the detrimental effects of the dilution processes. In an effort to ameliorate the interdependencies among controller parameters, a degradation inhibition mechanism is employed within this controller. Furthermore, this work establishes the limiting relationship between the controller's reaction rates in order to guarantee RPA, while abstaining from the introduction of supplementary species and biochemical reactions. By using the quasi-aPID controller in both the Escherichia coli gene expression model and the whole-body cholesterol metabolism model, its effectiveness is confirmed. Simulation results demonstrate that, the quasi-aPID exhibits a smaller absolute steady-state error in both models and guarantees the RPA property.
反相加性 PID(aPID)控制器的非线性和不可分离性为生化反应网络(BCRN)的设计提供了更大的灵活性,对生物控制系统产生了重大影响。然而,在 aPID 控制器的设计中忽略了控制物种的稀释,这将导致控制器抑制机制的失效和鲁棒完美适应(RPA)的丧失——这是鲁棒稳定跟踪的生物学对应物。在这项研究中,研究了稀释过程对 aPID 结构的影响。研究发现,当控制物种中存在稀释过程时,比例和低通滤波器会发生变化,这增加了控制器参数之间的耦合。此外,由于控制物种稀释而产生的参考信号和控制输出的额外积分进一步导致 RPA 的丧失。随后,设计了一种由 BCRNs 表示的新型 aPID 控制器,称为拟 aPID,以消除稀释过程的不利影响。为了改善控制器参数之间的相互依赖性,该控制器采用了降解抑制机制。此外,这项工作建立了控制器反应速率之间的限制关系,以保证 RPA,同时避免引入补充物种和生化反应。通过在大肠杆菌基因表达模型和全身胆固醇代谢模型中使用拟 aPID 控制器,验证了其有效性。仿真结果表明,拟 aPID 在两个模型中都表现出较小的绝对稳态误差,并保证了 RPA 特性。