Introduction to the special issue on intelligent control of high-performance engineering systems

The new challenges faced by high-performance and highprecision engineering in industries include maximising energy efficiency for sustainability, ensuring high product quality, as well as reducing the production cycle time while minimising the production cost and manpower overheads simultaneously. In the past decade, the technical requirements of engineering systems have become more stringent to be applicable to every aspect of human society ranging from automation, manufacturing, and military to electrical systems. The growing number of applications in engineering systems, along with the increasing requirements and demands for productivity, safety, system stability and reliability, are posing new and challenging theoretical and technological problems for modelling and control of these highly non-linear systems. One of the main challenges is the provision of innovative compensation methodologies to these realistic engineering applications. Intelligent control methodologies ensure that the industrial systems operate at high efficiencies, while undesirable effects such as excessive vibrations, underactuation, non-minimum phase error dynamics, external disturbances, noises, etc. are minimized. As such, novel intelligent control topologies are imperative with the advancement of high-performance engineering systems and corresponding technologies. Control of these complex systems is highly challenging due to the inherent non-linear behaviour and strong heterogeneity with the different components. System integration and sensor fusion are also among the major concerns. In this special issue, seven high-quality research articles representing the latest trends in intelligent control of high-performance engineering systems are presented. The various relevant topics are consolidated to provide the potential readers a broader perspective of this currently hot research topic as well as a comprehensive background of the state-of-the-art approaches to intelligent control for realistic industrial applications. With the diversity of application domains, high-performance engineering systems are required in mechatronics, robot manipulators, segmented mirror telescopes (SMTs), power systems, etc. in ascending order of volumetric magnitude. High-speed motion control in mechatronic systems has always been a challenge due to the precision required despite the presence of external disturbances and measurement noise. In Liu et al., an active vibration isolation methodology is proposed for model reference adaptive control to isolate base vibrations and reject payload disturbances. Together with conventional proportional-integralderivative (PID) control, the attitude jitters are reduced by more than 60 dB when using the proposed composite controller on a flexible spacecraft with a six-leg Stewart platform. On the other hand, Hong and Pang proposed a novel peak filter design to reject narrow-band disturbances for servo control in hard disk drives (HDDs). The proposed methodology yields improved transient responses using a phase-scheduling method in addition to varying gain and damping ratio, as well as enlarged stability margin during both transient and steady-state periods as compared to conventional peak filters. These advantages are verified with simulations and experiments on commercial HDDs. Tracking of robot manipulators is often encountered with unknown parameters and dynamic friction in the presence of disturbances and unmodelled dynamics. These underactuated systems have more degrees of freedom than the number of inputs, which stiffen the solution of the inverse kinematics. The Brockett theorem also states that non-holonomic systems with restricted mobility cannot be stabilised to a desired posture via differentiable or continuous pure state feedback, even if they are controllable. Motivated by these factors, advanced adaptive and robust control methodologies are proposed for the trajectory tracking problem in the presence of these uncertainties. In Jalani et al., novel robust and adaptive trajectory following methods are proposed to control underactuated fingers in the Bristol Elumotion Robot Hand. The PID control, adaptive control, conventional sliding mode control (SMC), and integral SMC (ISMC) are implemented on finger tracking and positioning controls empirically. Despite high levels of friction and stiction, the ISMC uses minimal control effort and achieves the best tracking and positioning performance against modelling uncertainties and nonlinearities. In general, the closed-loop systems using classical adaptive laws do not converge in the presence of time-varying parameters and periodic learning control laws are not smooth. As such, Wang et al. proposed an adaptive recurrent neural network control for a class of uncertain constrained mobile manipulators with unknown system dynamics. The proposed control strategies