Interval arithmetic-based fuzzy discrete-time crane control scheme design

Abstract

Abstract. In many manufacturing segments, container terminals and shipping yards the automation of material handling systems is an important element of enhancing productivity, safety and efficiency. The fast, precise and safe transfer of goods in crane operations requires a control application solving the problems, including non-collision trajectory planning and limitation of payload oscillations. The paper presents the interval arithmetic-based method of designing a discrete-time closed-loop anti-sway crane control system based on the fuzzy interpolation of linear controller parameters. The interval analysis of a closed-loop control system characteristic polynomial coefficients deviation from their nominal values is proposed to define a minimum number of fuzzy sets on the scheduling variables universe of discourse and to determine the distribution of triangular-shaped membership functions parameters, which satisfy the acceptable range of performances deterioration in the presence of the system's parameters variation. The effectiveness of this method was proved in experiments conducted using the PAC system on the laboratory scaled overhead crane.

Design of simultaneous input-shaping-based SIRMs fuzzy control for double-pendulum-type overhead cranes

“…They are one of the most important elements in global industrialization and play an irreplaceable role in economic development. Structurally, a common characteristic among overhead cranes is that their payloads are supported via suspension cables, the cables are hanged on trolleys [3]. Although it provides the hoisting/lowering and moving functionalities of overhead cranes, such a characteristic also presents several challenges.…”

“…Various methods concerning the control problem have been presented, i.e., fuzzy logic control [1][2][3], energy-based control [4], adaptive control [5], trajectory planning [6], input shaping [7], sliding mode control [8][9][10], to name but a few. See [11] for a review of these efforts in the crane control problem.…”

Higher order fuzzy logic in controlling selective catalytic reduction systems

“…Examples of fuzzy logic systems applications are broadly known, e.g. [3][4][5]. Another work on FLSs in the industry and the environment is [6].…”

P1-TS fuzzy scheduling control system design using local pole placement and interval analysis

“…The fuzzy model based design of scheduling control scheme proposed in [27,28] is in this paper presented in more feasibly form through applying the analytical theory and fundamental matrix recursion method proposed in [29][30][31] for fuzzy rule-based system interpretation, that results in reduction of the computational complexity of multidimensional scheduling control scheme synthesis. Thus, incorporating the advantages of P1-TS theory into interval arithmetic and local pole placement based synthesis of scheduling control scheme, the iterative procedure is developed for multi-input fuzzy scheduler design.…”

“…In [25,26] the EA is employed to minimize the number of fuzzy sets specified for scheduling variables, rope length and mass of a payload, and design a TS fuzzy controller for an anti-sway crane control system. In [27,28] the iterative procedure utilizing the interval analysis of closed-loop polynomial coefficients is developed for fuzzy interpolation based discrete-time control scheme implemented on a laboratory scaled overhead crane. However, the mentioned methods does not show directly a general solution for multi-input multi-output (MIMO) fuzzy scheduler design.…”