Robust constrained iterative learning predictive fault-tolerant control of uncertain batch processes

This paper focuses on particle swarm optimization algorithm (PSOA)-based H∞ tracking fault-tolerant control for batch processes to resist the influence of actuator faults and unknown disturbances. First, according to a given actual process model, by introducing output tracking error, state difference and new states including output tracking error, an extended equivalent model is constructed. Then, a linearquadratic performance function is introduced. By using the PSOA to adjust those parameters in the function , a new state space H ∞ tracking fault-tolerant control law is proposed under optimal control theory. Actuator faults are regarded as uncertainties here. The Lyapunov stability theory is used to solve the allowable disturbances in a certain range. The greatest merit of this design is that it has better tracking performance and stronger anti-fault and interference ability. Finally, the injection molding process and nonlinear batch reactor are taken as examples to compare with the genetic algorithm method (GA) and the traditional control method (TC), which shows that the method proposed is more practical and effective.INDEX TERMS Batch processes, new extended state space model, particle swarm optimization algorithm, linear-quadratic H∞ tracking fault-tolerant control, actuator fault.

Section: Introductionmentioning

confidence: 99%

Particle Swarm Optimization-Based H∞ Tracking Fault Tolerant Control for Batch Processes

Wang

2021

“…In order to solve the problem of disturbance and uncertainty, reference [13] proposed a new state space structure improved MPC, and applied it to the temperature control of industrial coke oven. For actuator failures, robust constrained iterative learning model predictive faulttolerant control methods (IL-MPFTC) for uncertain batch processes were proposed in [14]. Considering the interval time-varying time delay and unknown disturbance, the references [15][16] constructed a robust constrained MPFTC method for discrete systems with interval time-varying time delay and unknown disturbance.…”

Section: Introductionmentioning

confidence: 99%

A Systematic Optimization Design of New Constrained Robust Model Predictive Fault-Tolerant Control for Industrial Processes

Chen

2021

A comprehensive optimization design method of new constrained robust model predictive fault-tolerant control is proposed for industrial processes with partial actuator failures and unknown disturbances. A new state space model which is composed of differential state variables, output tracking errors, and new state variables related to output tracking errors is first constructed according to the multiple single-input single-output (SISO) models. Considering the uncertainties existing in the system, the reproduced model is represented by a discrete switched model with polytopic uncertainties. Subsequently, the model predictive controller with min-max optimization is designed to ensure the performance improvement and solve the drawback that the controller gain is not adjustable. To further enhance the system performance, the designed controller is optimized in two steps based on the switching strategy. In addition, the corresponding switching strategy is designed to realize the mutual switching between different models of the system. Finally, taking continuous stirred tank and injection molding processes as examples, the effectiveness of the proposed method is verified by comparing with the traditional control method.INDEX TERMS Constrained robust model predictive fault-tolerant control, polytopic discrete switched system, partial actuator failures, state-space model, industrial processes

“…In references [15]- [23], a set of control strategies that combine ILC with MPC are proposed. Recently, MPC was combined with fault-tolerant control (FTC) and applied [24]. Most research results focus on 2D systems theory.…”

Section: Introductionmentioning

confidence: 99%

Improved H-Infinity Hybrid Model Predictive Fault-Tolerant Control for Time-Delayed Batch Processes Against Disturbances

Chen

2020

An H-infinity model predictive fault-tolerant control strategy is proposed for multi-phase batch processes with interval delay and actuator failures. First, state variables, state errors and output tracking errors are introduced to establish an extended-state-space switched system model. Then, based on this model, a predictive fault-tolerant control law is designed for tracking the set point by the output that satisfies the requirements of the optimal performance index under input and output constraints. The feasibility conditions for the solvability of the control law are presented in the form of linear matrix inequalities. In addition, the designed switching law is constructed, and the gain of the control law is obtained via the optimization algorithm. This design has several advantages: the output tracking is faster, the tracking performance is superior, and the trace is smoother at the switching time. Finally, through a comparison with traditional methods, the effectiveness and feasibility of this method are demonstrated via injection molding simulation. INDEX TERMS Batch production systems, added delay, fault tolerant control, linear matrix inequalities, Lyapunov methods, predictive models, switching systems, predictive control.