Fuzzy surface-based sliding mode control

Dual-Mode Based Sliding Mode Control Approach for Nonlinear Chemical Processes

This paper synthesizes a new sliding mode controller (SMC) approach to enhance tracking and regulation tasks by following dual-mode concepts. The new control law consists of two distinct types of operation, using the combination of higher gain to large error signals (transient) and lower gain to small error signals (the region around the set point). The design is presented from a dual-mode (PD-PID) sliding surface operating in concert, fulfilling desired control objectives to ensure stability and performance. Therefore, a new controller was established, and we called it a dual-mode based SMC. The proposed controller is tested by computer simulations applied to two nonlinear processes, a continuous stirred-tank reactor (CSTR) and a mixing tank with a variable dead time. The results are compared with two different alternatives of SMC. In addition, the merits and drawbacks of the control schemes are analyzed using radial graphs, comparing the control methods with various performance measures for set points and disturbances changes. The ITSE (integral of time multiplied by the squared error), TVu (total variation of control effort) indices, Mp (maximum overshoot), and ts (settling time) were the indices used for performance analysis and comparisons.

Hybrid Approaches-Based Sliding-Mode Control for pH Process Control

This paper presents two hybrid control topologies; the topologies are designed by combining artificial intelligence approaches and sliding-mode control methodology. The first topology mixes the learning algorithm for multivariable data analysis (LAMDA) approach with sliding-mode control. The second offers a Takagi-Sugeno multimodel approach, internal model, and sliding-mode control. The process under study is a nonlinear pH neutralization process with high nonlinearities and time-varying parameters. The pH process is simulated for multiple reference changes, disturbance rejection, and noise in the transmitter. Performance indices are used to compare the proposed approaches quantitatively. The hybrid control topologies enhance the performance and robustness of the pH process under study.

H∞ output-feedback fuzzy proportional-integral control of fully delayed input/output systems

This paper presents the output-feedback fuzzy proportional-integral (PI) controller design for uncertain nonlinear systems with both fully delayed input and output. Based on the Takagi-Sugeno (T-S) fuzzy model representation, the output-feedback PI control is realized via parallel distributed PI compensation and novel LMI gain design. Although the T-S fuzzy PI controller is simple, asymptotic output regulation is assured to overcome the effect of uncertainty, state delay, and full input/output delays. When considering disturbance and measurement noise, the control performance is achieved by robust gain design. Furthermore, state observers and bilinear matrix inequality conditions are removed in this paper. Finally, time-delay Chua׳s circuit system and a continuous-time stirred tank reactor are taken as applications to show the expected performance.

Parameter estimation and interval type-2 fuzzy sliding mode control of a z-axis MEMS gyroscope

This paper reports a hybrid intelligent controller for application in single axis MEMS vibratory gyroscopes. First, unknown parameters of a micro gyroscope including unknown time varying angular velocity are estimated online via normalized continuous time least mean squares algorithm. Then, an additional interval type-2 fuzzy sliding mode control is incorporated in order to match the resonant frequencies and to compensate for undesired mechanical couplings. The main advantage of this control strategy is its robustness to parameters uncertainty, external disturbance and measurement noise. Consistent estimation of parameters is guaranteed and stability of the closed-loop system is proved via the Lyapunov stability theorem. Finally, numerical simulation is done in order to validate the effectiveness of the proposed method, both for a constant and time-varying angular rate.

Type-2 fuzzy model based controller design for neutralization processes

In this study, an inverse controller based on a type-2 fuzzy model control design strategy is introduced and this main controller is embedded within an internal model control structure. Then, the overall proposed control structure is implemented in a pH neutralization experimental setup. The inverse fuzzy control signal generation is handled as an optimization problem and solved at each sampling time in an online manner. Although, inverse fuzzy model controllers may produce perfect control in perfect model match case and/or non-existence of disturbances, this open loop control would not be sufficient in the case of modeling mismatches or disturbances. Therefore, an internal model control structure is proposed to compensate these errors in order to overcome this deficiency where the basic controller is an inverse type-2 fuzzy model. This feature improves the closed-loop performance to disturbance rejection as shown through the real-time control of the pH neutralization process. Experimental results demonstrate the superiority of the inverse type-2 fuzzy model controller structure compared to the inverse type-1 fuzzy model controller and conventional control structures.