Sliding-mode control approach for faster tracking

Abstract

A new sliding-mode control method is presented in which the nominal control is derived from a manifold consisting of the standard sliding manifold expression and its derivative. It is shown that the new method yields a faster reach time. Simulation results also show that it performs with smaller error and less control effort compared to standard counterparts in tracking an autonomous nonlinear affine system. Introduction: Sliding-mode control (SMC) is an adaptive and robust variable-structure (VS) control method in tracking a specified target trajectory for a given plant model involving uncertainties and external disturbances [1]. It mainly consists of reaching and sliding-mode phases. In the former, the system trajectory launched from any initial condition is forced towards a sliding surface while the latter refers to dynamics on the sliding surface presumably reached [2]. The associated control law contains nominal and discontinuous control terms. The nominal control term in standard SMC is calculated by setting the time derivative of the sliding manifold expression to zero. A major problem in this approach is high-frequency chattering in tracking fast time-varying target trajectories due to lag between the control to be applied and the error dynamics.In this Letter, a new sliding manifold definition and associated control law are introduced to alleviate the above shortcoming. The new manifold consists of an exponentially stable combination of standard conventional sliding manifold and its time derivative. The new and standard approaches with associated control laws are applied to a second-order nonlinear system and their performances are presented.

Real Time Implementation of Adaptive Sliding Mode Controller for a Nonlinear System

“…A new method that yields a faster response time was proposed in (Temel & Ashrafiuon, 2012). Here, the control signal was derived from a manifold consisting of a sliding surface and its derivative.…”

“…Using (17) and (18), all the algorithms were simulated. By comparing the three algorithms for a step change in the input, from Figure 3 it becomes obvious that the adaptive SMC seems to settle much quicker than the other two algorithms.…”

Comparison of robot trajectory tracking efficiency using various nonlinear control methods

“…Variable-structure sliding-mode control is also often used for industrial robot motion control (Cavallo, Natale, 2004), (Chang, 2009), (Hwang, Wu, 2013), (Islam, Liu, 2011), (Šabanović, 2011) because of its robustness and simplicity of the control algorithm (Kardoš, 2007), (Kurfess, 2005), (Zeinali, Notash, 2010). If any deviation in robotic system variables occurs, this control method immediately pushes it back to the constraint by using sliding mode (Chen et al, 1990), (Edwards, Spurgeon, 1998), (Hirschorn, 2007), (Kurfess, 2005), (Morgan, Özguner, 1985), (Temel, Ashrafiuon, 2012). After reaching the sliding surface, the system behaves like a linear-time invariant robust system with a reduced order (Kardoš, 2007), (Perruquetti, Barbot, 2002).…”

A SMC method for A Class of Nonlinear Systems based on SVD technique

“…Since sliding mode control (SMC) possesses the strong robustness ability to eliminate or compensate the model uncertainties, parameter variations, and external disturbances [1][2][3][4][5], SMC is an effective control approach and is extensively researched. In [6], a novel SMC law is proposed to deliver the tip of a flexible asymmetric-tipped needle to a desired point or to track a desired trajectory within tissue.…”