A novel adaptive control approach for nonlinearly parameterized systems

Abstract

Nonlinearly parameterized systems are commonly encountered in control of practical systems. However, the conventional adaptive estimation and control strategies, based on the essential assumption of linear parameterization, are incapable of dealing with this class of systems. This incapability in turn becomes a bottleneck for prevalent applications of adaptive control. In literature, there have been some attempts to break through this bottleneck by investigating the characteristics of nonlinearities. However, it is still open for an implementable strategy that is powerful for nonlinearly parameterized systems as the certainty equivalence principle for linearly parameterized systems. This paper aims to contribute an attempt to this open problem by proposing a novel adaptive control approach. On the one hand, the controller is conceptually simple, and it does not explicitly rely on the expression of system nonlinearities. On the other hand, the controller is able to achieve system stability and parameter convergence.

Adaptive Control of Unmanned Aerial Vehicles with Varying Payload and Full Parametric Uncertainties

“…A disadvantage of this method is that the bound of uncertainty is required as prior information when designing the controller. Such bounded uncertainty robust control designs have been applied for both single UAV cases [9][10][11], and for multiple collaborative settings [12,13]. Sliding mode control (SMC) is one of the most popular robust control approaches, with implementations applied to UAVs in various settings [14,15].…”

Event-triggered neural network control of autonomous surface vehicles over wireless network

“…In [19,20], fuzzy logic systems were employed to estimate the lumped unknown functions. In [21][22][23][24], adaptive techniques were used to reject the model uncertainties and compensate the effects of external disturbances. Nevertheless, the above systems work with periodic sampling and controlling in these studies , known as periodic-triggered control systems.…”

Adaptive finite‐time stabilization of nonlinearly parameterized systems subject to mismatching disturbances

“…As a pioneering work, Kanellakopoulos et al first proposed the famous integrator backstepping to systematically solve the adaptive control problem for nonlinear systems in parametric strict‐feedback form. Later, the method of overcoming the drawback of overparameterization was given in the work of Krstić et al Since then, a series of stabilizing schemes involving nonlinear and adaptive control were well documented in other works and the references therein.…”