In this work, we propose an approximation-free adaptive performance control scheme for unknown high-relative degree, multi-input–multioutput (MIMO) nonlinear systems with saturation on the control input signal. We introduce a novel reconciling adaptive modification of the predefined performance specifications based on the input constraints of the controlled plant, providing the best-feasible output performance. The automatic gain tuning in combination with the simplicity of the proposed controller enhance its robustness and enable its easy deployment in practical scenarios. Notably, the introduced control methodology ensures the necessary compromise between input-output constraints on a semi-global sense for ISS systems. However, the stability attributes for general nonlinear systems are inevitably limited to compact domains due to the inherent conflict between performance demand and actuation capability. In this context, we provide a sufficient closed-loop stability criterion through Lyapunov analysis. Finally, illustrative simulation studies and experimental results clarify and verify the efficacy of the proposed controller.

A universal approximation-free adaptive prescribed performance control scheme is designed for unknown SISO nonlinear systems with input saturation. The proposed control method introduces a compromising relaxation of output performance specifications depending on the input limitations. Given the conflicting nature between input and output constraints, the stability properties are inevitably local. In this respect, a sufficient stability condition for the closed-loop system is provided through theoretical analysis. Owing to the adopted prescribed performance control technique, the satisfaction of the aforementioned stability properties guarantees the desired trade-off between input and output constraints. Moreover, no hard calculations are needed, neither for the controller nor for the adaptive law, maintaining the complexity of the control algorithm relatively low. Finally, the proposed approach is clarified and verified by various simulation studies.

A novel approximation-free adaptive prescribed performance control scheme for the longitudinal motion tracking of input and state constrained small fixed-wing UAVs is designed in this work. The proposed controller employs the adaptive prescribed performance technique to impose output performance specifications in accordance with actuation limitations regarding the amplitude and the rate of the control signal. Furthermore, state constraints are introduced to ensure the proper operation of the closed-loop system. The adoption of PPC methodology results in a low complexity control algorithm with easy gain selection which facilitates its practical implementation. Finally, a comprehensive simulation study as well as comparative simulation paradigms on an Aerosonde model clarifies and verifies the superiority and the effectiveness of the proposed controller to control the longitudinal motion of UAVs in the presence of wind gusts.

A decentralized robust control protocol addressing leader-follower formation control of unknown nonlinear input-constrained multi-agent systems with adaptive performance specifications is proposed in this paper. The performance characteristics predefined by the user are adaptively modified in order to comply with the actuation constraints of the agents regarding both the magnitude and the rate of the control signals, ensuring closed-loop stability. The proposed control protocol is characterized by easy gain tuning and low structural complexity which simplifies the integration to real systems. A thorough experiment involving a system of multiple quadrotors was conducted to clarify and verify the theoretical findings.

In this paper, we address the trajectory-/target-tracking and obstacle-avoidance problem for nonholonomic mobile robots subjected to diamond-shaped velocity constraints and predefined output performance specifications. The proposed scheme leverages the adaptive performance control to dynamically adjust the user-defined output performance specifications, ensuring compliance with input and safety constraints. A key feature of this approach is the integration of multiple constraints into a single adaptive performance function, governed by a simple adaptive law. Additionally, we introduce a robust velocity estimator with a priori-determined performance attributes to reconstruct the unmeasured trajectory/target velocity. Finally, we validate the effectiveness and robustness of the proposed control scheme, through extensive simulations and a real-world experiment.

This paper presents a novel robust reference governor (RG) for trajectory tracking of quadrotors. The proposed scheme is characterized by low computational complexity and straightforward gain selection. Moreover, it considers safety constraints regarding speed limits and ensures the stability and the proper operation of the closed-loop system. The proposed scheme imposes user-specified performance attributes on the evolution of the tracking error when the safety constraints allow it. When these constraints are at risk of violation, the proposed RG provides a relaxation of the predefined performance specifications to ensure the stability of the plant. Lyapunov analysis proves the boundedness of the closed-loop signals, while its efficacy is further clarified and verified via extensive comparative experimental results against a well-established PI regulator.