A simplified linear iterative predictive functional control approach for chamber pressure of industrial coke furnace

Bias compensation based partially coupled recursive least squares identification algorithm with forgetting factors for MIMO systems: Application to PMSMs

“…As PMSMs are now widely used in many applications, further work is required. In our future work, based on the proposed identification algorithm, attempts will be made to the fault diagnosis control [32][33][34][35][36] and model predictive control [37][38][39][40][41] for PMSMs. The proposed algorithm in this paper can be extended to study identification problems of other linear systems [42,43] and nonlinear systems with colored noise [44][45][46][47].…”

RIMER and SA based thermal efficiency optimization for fired heaters

“…(2) Although advanced control has been recognized as an effective and feasible approach to the operation of fired heaters, and also model-based control strategies have been developed [7][8][9] for the purpose of optimal on-line operation of fired heaters. However, it still needs "upper-layer" optimization component to decide the best operating condition for the controller.…”

“…The feed oil (or other fluids to be heated) with the flow rate F and input temperature Tin is heated in the pipe around the chamber to a desired outlet temperature Tout. The emission of flue gas is realized by draught fan or outlet baffle, which also serves 9 as the action to adjust the chamber negative pressure P. An oxygen analyzer is installed to measure the oxygen concentration O2 as an indicator of combustion state. The objective is to find the corresponding operating condition for the optimal thermal efficiency.…”

A Multi-innovation Recursive Least Squares Algorithm with a Forgetting Factor for Hammerstein CAR Systems with Backlash

“…Since Ding et al introduced the multi-innovation identification idea into the parameter identification, the multi-innovation identification methods have been widely studied and used [8,30,33,51]. Recently, an auxiliary model-based multi-innovation extended stochastic gradient algorithm was proposed to identify output error systems with colored measurement noises [5]; an auxiliary model-based multi-innovation stochastic gradient algorithm was derived for the multi-input single-output systems [29]; and a multi-innovation stochastic gradient algorithm parameter estimation-based adaptive control scheme for discrete-time systems was presented [50].…”