Based on the Internal model control (IMC) structure, an iterative learning control (ILC) scheme is proposed for batch processes with model uncertainties including time delay mismatch An important merit is that the IMC design for the initial run of the proposed control scheme is independent of the Subsequent ILC for realization of perfect tracking Sufficient conditions to guarantee the convergence of ILC are derived. To facilitate the controller design. a unified controller form is proposed for implementation of both IMC and ILC in the proposed control scheme Robust tuning constraints of the Unified controller are derived in terms of the process uncertainties described ill a Multiplicative form To deal with process uncertainties, the unified...
The paper presents a new algorithm for iterative learning control (ILC) called “natural” ILC. ILC is...
This paper develops an iterative learning reliable control (ILRC) scheme for batch processes with un...
To improve stability and convergence, feedback control is often incorporated with iterative learning...
Based on a two-dimensional (2D) system description of a batch process in industry, a robust closed-l...
A robust iterative learning control (ILC) scheme for batch processes with uncertain perturbations an...
A robust feedback integrated with iterative learning control (FILC) scheme for batch processes with ...
This paper proposes the design of the integrated output feedback and iterative learning control (ILC...
In this paper, an optimal iterative learning control (ILC) algorithm based on a time-parametrized li...
Based on robust feedback incorporated with iterative learning control scheme, this paper proposes a ...
Convergence is an important issue in the design and application of iterative learning control (ILC) ...
In this paper, a set-point related indirect-type iterative learning control (ILC) design is proposed...
Based on the proportional-integral (PI) closed-loop control widely used in industrial engineering pr...
Based on a two-dimensional (2D) Fornasini-Marchsini system description of a batch process in industr...
An iterative learning reliable control (ILRC) scheme is developed in this paper for batch processes ...
Multi-phase batch process is common in industry, such as injection molding process, fermentation and...
The paper presents a new algorithm for iterative learning control (ILC) called “natural” ILC. ILC is...
This paper develops an iterative learning reliable control (ILRC) scheme for batch processes with un...
To improve stability and convergence, feedback control is often incorporated with iterative learning...
Based on a two-dimensional (2D) system description of a batch process in industry, a robust closed-l...
A robust iterative learning control (ILC) scheme for batch processes with uncertain perturbations an...
A robust feedback integrated with iterative learning control (FILC) scheme for batch processes with ...
This paper proposes the design of the integrated output feedback and iterative learning control (ILC...
In this paper, an optimal iterative learning control (ILC) algorithm based on a time-parametrized li...
Based on robust feedback incorporated with iterative learning control scheme, this paper proposes a ...
Convergence is an important issue in the design and application of iterative learning control (ILC) ...
In this paper, a set-point related indirect-type iterative learning control (ILC) design is proposed...
Based on the proportional-integral (PI) closed-loop control widely used in industrial engineering pr...
Based on a two-dimensional (2D) Fornasini-Marchsini system description of a batch process in industr...
An iterative learning reliable control (ILRC) scheme is developed in this paper for batch processes ...
Multi-phase batch process is common in industry, such as injection molding process, fermentation and...
The paper presents a new algorithm for iterative learning control (ILC) called “natural” ILC. ILC is...
This paper develops an iterative learning reliable control (ILRC) scheme for batch processes with un...
To improve stability and convergence, feedback control is often incorporated with iterative learning...