This paper presents a new adaptive sliding-mode control (ASMC) scheme that uses the time-delay estimation (TDE) technique, then applies the scheme to robot manipulators. The proposed ASMC uses a new adaptive law to achieve good tracking performance with small chattering effect. The new adaptive law considers an arbitrarily small vicinity of the sliding manifold, in which the derivatives of the adaptive gains are inversely proportional to the sliding variables. Such an adaptive law provides remarkably fast adaptation and chattering reduction near the sliding manifold. To yield the desirable closed-loop poles and simplify a complicated system model by adapting feedback compensation, the proposed ASMC scheme works together with a pole-placement control (PPC) and a TDE technique. It is shown that the tracking errors of the proposed ASMC scheme are guaranteed to be uniformly ultimately bounded (UUB) with arbitrarily small bound. The practical effectiveness and the fast adaptation of the proposed ASMC are illustrated in simulations and experiments with robot manipulators, and compared with those of an existing ASMC.

This article presents a practical synthesized sliding-mode control (SSMC) scheme and, then, applies it to quadrotor unmanned aerial vehicle (UAV) systems. A new adaptive law is developed to be suitable for real applications with small moment of inertia such as quadrotor UAV systems that become more sensitive to abrupt and external disturbances. Since it is designed to respond to both sliding variables and time-delayed estimation errors, it makes the switching gains provide remarkably fast convergence rate and high robustness while compensating for abrupt and external disturbances. Besides, the proposed SSMC scheme works together with the pole-placement control to enhance the system stability while yielding the desirable closed-loop dominant poles. Also, the proposed control scheme employs one-sample delayed information to cancel out the system uncertainties and disturbances so that it makes a simple and compact structure. It is shown that attitude trajectory tracking errors of the proposed SSMC scheme are guaranteed to be bounded by the bounded-input bounded-output stability theory. The practical effectiveness and feasibility of the proposed control scheme are illustrated in real implementation with a quadrotor UAV system, which are compared with those of the existing control schemes.

This paper presents a practical adaptive time-delay control scheme (ATDC) and then applies it to robot manipulators. The proposed ATDC uses a time-delayed signal to cancel complex nonlinear dynamics and disturbances, and hence to provide a simple structure. The adaptive law of the proposed ATDC is developed to adjust the control gains appropriately while in operation and then to achieve good tracking performance with tolerant fluctuation and fast convergence speed. Such adaptive control gains are shown to have an effect of adding an adaptive auxiliary control to a conventional time-delay control (TDC). Moreover, the proposed ATDC includes a typical sliding-mode control as a second auxiliary control to suppress the time-delay estimation (TDE) errors caused by the time-delayed signal so that robust performance can be achieved. It is shown by the bounded input bounded output stability theory and a Lyapunov approach that the TDE errors are bounded and the tracking errors are uniformly ultimately bounded, respectively. The practical effectiveness of the proposed ATDC, or the synergistic effect of two auxiliary controls, is illustrated in simulations and experiments with robot manipulators.

This paper presents a widely-adaptive time-delayed control (WATDC) without imposing any restrictions on allowable control gains to make the most of the advantages of time-delayed control (TDC), then applies the WATDC to robot manipulators. Since the proposed WATDC can provide arbitrarily high gains by using the time-varying bounds of time-delayed estimation errors, it has a room for improving the tracking performance and robustness of the existing stabilizing TDCs that have narrow range of control gains depending on system parameters comprising the inertia of a robot manipulator. Furthermore, the proposed WATDC employs a fast adaptive law to generate wide-ranging and well-timed control gains that depend the magnitude of tracking errors. In other words, timely adaptation over a wide range of control gains makes the WATDC provide suitable control effort for desirable output responses. Additionally,to suppress unfavorable inherent time-delayed estimation errors arising from one sample delayed measurements, the proposed WATDC works together with a sliding-mode control that has switching gains based on the time-varying bounds of time-delayed estimation errors. In simulations and experiments with robot manipulators, the proposed WATDC has better tracking performance and robustness than the existing TDCs due to a wide range of adaptive control gains and the time-delayed estimation error dependent switching gains.

This study proposes a new adaptive law for a sliding mode control (SMC) scheme to achieve effective switching gain tuning near the sliding surface. The proposed adaptive law makes the switching gains rapidly and effectively decrease near the sliding surface to provide well-functioning adaptation while avoiding the sign changes caused by excessive adaptation. Such an adaptation mechanism contributes to chattering reduction and fast adaptation of switching gains without temporary large tracking errors. The proposed adaptive SMC (ASMC) works together with a time-delay controller (TDC) for a more practical implementation based on a model-free controller. Fortunately, the proposed ASMC has an additional benefit of suppressing time-delay estimation (TDE) errors inherently arising from the TDC. In other words, the proposed ASMC acts in synergy with the TDC. Simulations are performed, and comparisons are made with existing control schemes to illustrate the good tracking performance of the proposed ASMC. These simulations have shown that with a 2 degree-of-freedom robot manipulator, the proposed ASMC has a good nominal and robust performance with a very strategic adaptive law.