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A flexible prescribed performance control (FPPC) approach for input saturated nonlinear systems (ISNSs) with unmeasurable states is first presented in this article. Compared to the standard prescribed performance control (SPPC) or funnel control methods for ISNSs, the “flexibility” of the proposed FPPC algorithm is reflected in two aspects: 1) the proposed FPPC algorithm simultaneously considers multiple key indicators (including the steady state accuracy, convergence time, and overshoot), which are widely demanded in industrial production; 2) the proposed FPPC algorithm achieves a tradeoff between performance constraint and input saturation, i.e., the performance boundary can adaptively increase when the control input exceeds the saturation threshold, effectively avoiding singularity; conversely, when the control input is within the saturation threshold range, the performance constraint boundary can adaptively revert back to the original performance boundary. In addition, the unmeasured states are observed by the state observer, and the unknown nonlinear functions are approximated by fuzzy logic systems. The results demonstrate that the proposed output feedback control algorithm can ensure that all closed-loop signals are semiglobally bounded, the system output can track the desired signal within a prescribed time, and the tracking error is consistently maintained within flexible performance boundaries that depend on input and output constraints. The developed algorithm is exemplified through simulation instances.
Yao et al. (Tue,) studied this question.