Improve Feedback Linearization Control For SISO Nonlinear Systems

Abstract

Feedback linearization is a powerful technique used in control systems to transform the dynamics of nonlinear systems into a linear form, making them easier to analyze and control. However, dealing with highly nonlinear systems can be challenging and complicated. This paper aims to address this issue by proposing an improved approach to the feedback linearization method. To enhance the feedback linearization control of single-input single output (SISO) nonlinear systems, the paper explores two main strategies. The first approach involves adjusting the control gains in conjunction with other parameters to optimize the control performance. This allows for fine-tuning the system’s behavior and response to achieve desired objectives. The second approach focuses on evaluating the performance of the feedback linearization control through simulations under diverse scenarios, disturbances, and reference inputs. By conducting these simulations, the researchers can thoroughly analyze how the system behaves and performs under various conditions. Importantly, throughout these adjustments and simulations, ensuring system stability remains a crucial consideration. The paper delves into two specific techniques for designing feedback linearization control: input-output linearization and input-state linearization. Both techniques offer distinct advantages and trade-offs depending on the system requirements and characteristics. By employing these techniques, the designer aims to achieve the desired behavior and performance of the SISO nonlinear system.